The Rainbow Books The Rainbow BooksNATIONAL COMPUTER SECURITY CENTER
FORT GEORGE G. MEADE, MARYLAND 20755-6000
NCSC-TG-030
Library No. S-240,572
Version 1
This guide is the latest in a series of technical guidelines published by the National Computer Security Center. These publications provide insight to the TCSEC requirements for the computer security vendor and technical evaluator. The goals of the Technical Guideline Program are to discuss each feature of the TCSEC in detail and to provide the proper interpretations with specific guidance.
The National Computer Security Center has established an aggressive program to study and implement computer security technology. Our goal is to encourage the widespread availability of trusted computer products for use by any organization desiring better protection of its important data. One way we do this is by supporting the Trusted Product Evaluation Program. This program focuses on the security features of commercially produced and supported computer systems. We evaluate the protection capabilities against the established criteria presented in the TCSEC. This program, and an open and cooperative business relationship with the computer and telecommunications industries, will result in the fulfillment of our country's information systems security requirements. We resolve to meet the challenge of identifying trusted computer products suitable for use in processing information that requires protection.
I invite your suggestions for revising this technical guide. We will review this document as the need arises.
_________________________________ November 1993
Patrick R. Gallagher, Jr.
Director
National Computer Security Center
We wish to thank the many members of the computer security community who enthusiastically gave their time and technical expertise in reviewing this guide and providing valuable comments and suggestions.
The TCSEC was originally published on 15 August 1983 as CSC-STD-001-83. In December 1985, the Department of Defense adopted it, with a few changes, as a Department of Defense Standard, DoD 5200.28-STD. DoD Directive 5200.28, Security Requirements for Automated Information Systems (AISs) [DoD Directive], requires the TCSEC be used throughout the Department of Defense. The TCSEC is the standard used for evaluating the effectiveness of security controls built into DoD AISs.
The TCSEC is divided into four divisions: D, C, B, and A. These divisions are ordered in a hierarchical manner, with the highest division (A) being reserved for systems providing the best available level of assurance and security. Within divisions C and B are subdivisions known as classes, which are also ordered in a hierarchical manner to represent different levels of security in these divisions.
An important set of TCSEC requirements, which appears in classes B2 to A1,is that of covert channel analysis (CCA). The objectives of CCA are:
This document provides guidance to vendors on what types of analyses they should carry out for identifying and handling covert channels in their systems, and to system evaluators and accreditors on how to evaluate the manufacturer's analysis evidence. Note, however, that the only measure of TCSEC compliance is the TCSEC. This guide contains suggestions and recommendations derived from TCSEC objectives but which are not required by the TCSEC.
This guide is not a tutorial introduction to any topic of CCA. Instead, it is a summary of analysis issues that should be addressed by operating systems designers, evaluators, and accreditors to satisfy the requirements of the B2-A1 classes. Thus, we assume the reader is an operating system designer or evaluator already familiar with the notion of covert channels in operating systems. For this reader, the guide defines a set of baseline requirements and recommendations for the analysis and evaluation of covert channels. For the reader unfamiliar with CCA techniques used to date, the following areas of further documentation and study may be useful:
This guide refers to covert channel identification and handling methods which help assure that existent covert channels do not compromise a system's secure operation. Although the guide addresses the requirements of systems supporting the TCSEC mandatory policy, the analysis and handling methods discussed apply equally well to systems supporting any nondiscretionary (e.g., mandatory) security policy [Saltzer and Schroeder75]. We make additional recommendations which we derive from the stated objectives of the TCSEC. Not addressed are covert channels that only security administrators or operators can exploit by using privileged (i.e., trusted) software. We consider use of these channels an irrelevant threat because these administrators, who must be trusted anyway, can usually disclose classified and sensitive information using a variety of other more effective methods.
This guide applies to computer systems and products built with the intention of satisfying TCSEC requirements at the B2-A1 levels. Although we do not explicitly address covert channels in networks or distributed database management systems, the issues we discuss in this guide are similar to the ones for those channels.
Covert channel analysis is one of the areas of operational assurance. As such, its control objective is that of assurance. The assurance objective provided in [NCSC TCSEC] is the following:
Systems that are used to process or handle classified or other sensitive information must be designed to guarantee correct and accurate interpretation of the security policy and must not distort the intent of that policy. Assurance must be provided that correct implementation and operation of the policy exists throughout the system's life-cycle.This objective affects CCA in two important ways. First, covert channels are the result of an implementation of a nondiscretionary security policy at the operating system level; therefore, depending on how this policy is implemented within a given system, the resulting system will have fewer or more covert channels. Second, the existence of covert channels poses a potential threat to the use of the mandatory policy throughout the system's life cycle. Thus, the identification and handling of covert channels represents an important tenet of mandatory policy support in B2-A1 systems.
This guide contains seven chapters, a glossary, a bibliography, and two appendices. Chapter 2 reviews various definitions of covert channels, presents the policy implications of those definitions, and classifies channels. Chapter 3 presents various sources of covert channel information and identification methods, and discusses their relative practical advantages. Chapter 4 describes bandwidth estimation and illustrates a technique based on standard information theory that can be applied effectively in practice. Chapter 5 reviews various covert channel handling methods and policies that are consistent with the TCSEC requirements. Chapter 6 discusses covert channel testing and test documentation. Chapter 7 presents TCSEC requirements for CCA, and includes additional recommendations corresponding to B2-A1 evaluation classes. The glossary contains the definitions of the significant terms used herein. The bibliography lists the references cited in the text. Appendix A cites some examples of storage and timing channels. Appendix B describes the capabilities of several tools for covert channel identification.
In this chapter we provide several definitions of covert channels and discuss the dependency of these channels on implementations of nondiscretionary access control policies (i.e., of policy models). Also, we classify channels using various aspects of their scenarios of use.
The notion of covert communication was introduced in [Lampson73] and analyzed in [Lipner75, Schaefer77, Huskamp78, Denning83, Kemmerer83], among others. Several definitions for covert channels have been proposed, such as the following:
(1) Irrelevance of Discretionary Policy Models
The above definition implies that covert channels depend only on the interpretation of nondiscretionary security models. This means the notion of covert channels is irrelevant to discretionary security models.
Discretionary policy models exhibit a vulnerability to Trojan Horse attacks regardless of their interpretation in an operating system [NCSC DAC, Gasser88]. That is, implementations of these models within operating systems cannot determine whether a program acting on behalf of a user may release information on behalf of that user in a legitimate manner. Information release may take place via shared memory objects such as files, directories, messages, and so on. Thus, a Trojan Horse acting on behalf of a user could release user-private information using legitimate operating system requests. Although developers can build various mechanisms within an operating system to restrict the activity of programs (and Trojan Horses) operating on behalf of a user [Karger87], there is no general way, short of implementing nondiscretionary policy models, to restrict the activity of such programs. Thus, given that discretionary models cannot prevent the release of sensitive information through legitimate program activity, it is not meaningful to consider how these programs might release information illicitly by using covert channels.
The vulnerability of discretionary policies to Trojan Horse and virus attacks does not render these policies useless. Discretionary policies provide users a means to protect their data objects from unauthorized access by other users in a relatively benign environment (e.g., an environment free from software containing Trojan Horses and viruses). The role of nondiscretionary policies is to confine the activity of programs containing Trojan Horses and viruses. In this context, the implementation of mandatory policies suggested by the TCSEC, which forms an important subclass of nondiscretionary security policies, must address the problem of unauthorized release of information through covert channels.
(2) Dependency on Nondiscretionary Security Policy Models
A simple example illustrates the dependency of covert channels on the security policy model used. Consider a (nondiscretionary) separation model M that prohibits any flow of information between two subjects Sh and Si Communication in either direction, from Sh to Si and vice versa, is prohibited. In contrast, consider a multilevel security model, M', where messages from Sh to Si are allowed only if the security level of Si dominates that of Sh. Here, some communication between 5h and Si may be authorized in M'.
The set of covert channels that appears when the operating system implements model M' may be a subset of those that appear when the same operating system implements model M. The covert channels allowing information to flow from Sh to Si in interpretations of model M could become authorized communication channels in an interpretation of model M'.
The dependency of covert channels on the (nondiscretionary) security policy models does not imply one can eliminate covert channels merely by changing the policy model. Certain covert channels will exist regardless of the type of nondiscretionary access control policy used. However, this dependency becomes important in the identification of covert channels in specifications or code by automated tools. This is the case because exclusive reliance on syntactic analysis that ignores the semantics of the security model implementation cannot avoid false illegal flows. We discuss and illustrate this in sections 3.2.2 and 3.3.
(3) Relevance to Both Secrecy and Integrity Models
In general, the notion of covert channels is relevant to any secrecy or integrity model establishing boundaries meant to prevent information flow. Thus, analysis of covert channels is equally important to the implementation of both nondiscretionary secrecy (e.g., [Bell and La Padula76, Denning76, Denning77, Denning83, NCSC TCSEC]) and integrity models (e.g., [Biba77, Clark and Wilson87]). In systems implementing nondiscretionary secrecy models, such as those implementing the mandatory security policies of the TCSEC at levels B2-A1, CCA assures the discovery of (hopefully all) illicit ways to output (leak) information originating from a specific secrecy level (e.g., "confidential/personnel files/") to a lower, or incomparable, secrecy level (e.g., "unclassified/telephone directory/"). Similarly, in systems implementing nondiscretionary integrity models, such analysis also assures the discovery of (hopefully all) illicit ways to input information originating from a specific integrity level (e.g., "valued/personnel registry/") to a higher, or incomparable, integrity level (e.g., "essential/accounts payable/"). Without such assurances, one cannot implement appropriate countermeasures and, therefore, nondiscretionary security claims become questionable at best. Figures 2-1(a) and 2-1(b) illustrate the notion of illegal flows in specific nondiscretionary secrecy and nondiscretionary integrity models.
FIGURE MISSING
Figure 2-1. Legal and Illegal Flows
FIGURE MISSING
Figure 2-2. Relevance of Covert Channels to an Integrity Model
The presence of untrusted software in the above example should not be surprising. Most application programs running on trusted computing bases (TCBs) supporting nondiscretionary secrecy consist of untrusted code. Recall that the ability to run untrusted applications on top of TCBs without undue loss of security is one of the major tenets of trusted computer systems. Insisting that all applications that might contain a Trojan Horse, which could use covert channels affecting integrity, be included within an integrity TCB is analogous to insisting that all applications that might contain a Trojan Horse, which could use covert channels affecting secrecy, be included within a secrecy TCB, and would be equally impractical.
If the untrusted accounts payable application contains a Trojan Horse, the Trojan Horse program could send a (legal) message to a user process running at a lower integrity level IL2, thereby initiating the use of a covert channel. In this covert channel, the Trojan Horse is the receiver of (illegal) lower integrity-level input and the user process is the sender of this input.
The negative effect of exploiting this covert channel is that an untrusted user logged in at a lower integrity level could control the accounts payable application through illegal input, thereby producing checks for questionable reasons. One can find similar examples where covert channels help violate any nondiscretionary integrity boundary, not just those provided by lattice-based integrity models (e.g., [Biba77]). Similar examples exist because, just as in the case of TCBs protecting sensitive information classified for secrecy reasons, not all applications running on trusted bases protecting sensitive information for integrity reasons can be verified and proved to be free of miscreant code.
(4) Dependency on TCB Specifications
To illustrate the dependency of covert channels on a system's TCB specifications (Descriptive or Formal Top-Level), we show that changes to the TCB specifications may eliminate existent, or introduce new, covert channels. The specifications of a system's TCB include the specifications of primitives which operate on system subjects, objects, access privileges, and security levels, and of access authorization, object/subject creation/destruction rules, for example. Different interpretations of a security model are illustrated in [Honeywell85a, Honeywell85b, Luckenbaugh86]. Changes to a TCB's specifications may not necessarily require a change of security model or a change of the security model interpretation.
Though this example illustrates the dependency of covert channels on TCB specifications, it is not a general solution for eliminating covert channels. In fact, we can find other examples to show that changing a TCB's specifications may actually increase the number of covert channels.
In such a system, whenever a user attempts to remove an upgraded directory from level Lh > Li where he is authorized to read and write it (as in Figure 2-3(c)), the remove operation fails because it violates the mandatory authorization check (the level of the removing process, Lh, must equal that of the parent directory, Li). In contrast, the same remove operation invoked by a process at level Li < Lh succeeds (Figure 2-3(d)).
However, a covert channel appears because of the specification semantics of the remove operation in UNIX "rmdir." This specification says a nonempty directory cannot be removed. Therefore, if the above user logs in at level Li and tries to remove the upgraded directory from the higher level Lh, the user process can discover whether any files or directories at level Lh > Li are linked to the upgraded directory. Thus, another process at level Lh can transmit a bit of information to the user process at level Li < Lh by creating and removing (e.g., unlinking) files in the upgraded directory. Figure 2-4 illustrates this concept.
Figure Missing
Figure 2-3. Creation and Destruction of an Upgraded Directory at Level Lh > Li
Figure Missing
Figure 2-4. Covert Channel Caused by (UNIX) TCB Interface Conventions (where Lh > Li)
This covert channel would not appear if nonempty directories, and the directory subtree started from them, could be removed (e.g., as in Multics [Whitmore73, Bell and La Padula76]). However, if the specification of directory removal is changed, disallowing removal of nonempty directories (as in UNIX), the covert channel appears. One cannot eliminate the channel without modifying the UNIX user-visible interface. This is an undesirable alternative given that user programs may depend on the interface convention that nonempty UNIX directories cannot be removed. One cannot invent a new TCB specification under which either directories are not user-visible objects or in which the notion of upgraded directories disappears for similar reasons; that is, the UNIX semantics must be modified.
In practice, when covert channel scenarios of use are constructed, a distinction between covert storage and timing channels [Lipner75, Schaefer77, NCSC TCSEC, Hu91, Wray91] is made even though theoretically no fundamental distinction exists between them. A potential covert channel is a storage channel if its scenario of use "involves the direct or indirect writing of a storage location by one process [i.e., a subject of I(M)] and the direct or indirect reading of the storage location by another process." [NCSC TCSEC] A potential covert channel is a timing channel if its scenario of use involves a process that "signals information to another by modulating its own use of system resources (e.g., CPU time) in such a way that this manipulation affects the real response time observed by the second process." [NCSC TCSEC] In this guide, we retain the distinction between storage and timing channels exclusively for consistency with the TCSEC.
In any scenario of covert channel exploitation, one must define the synchronization relationship between the sender and the receiver of information. Thus, covert channels can also be characterized by the synchronization relationship between the sender and the receiver. In Figure 2- 5, the sender and the receiver are asynchronous processes that need to synchronize with each other to send and decode the data. The purpose of synchronization is for one process to notify the other process it has completed reading or writing a data variable. Therefore, a covert channel may include not only a covert data variable but also two synchronization variables, one for sender- receiver synchronization and the other for the receiver-sender synchronization. Any form of synchronous communication requires both the sender-receiver and receiver-sender synchronization either implicitly or explicitly [Haberman72]. Note that synchronization operations transfer information in both directions, namely from sender to receiver and vice versa and, therefore, these operations may be indistinguishable from data transfers. Thus, the synchronization and data variables of Figure 2-5 may be indistinguishable.
Some security models, and some of their interpretations, allow receiver-sender communication for subsets of all senders and receivers supported in the system. For example, all mandatory security models implemented in commercial systems to date allow information to flow from a low security level to a higher one. However, sender-receiver synchronization may still need a synchronization variable to inform the receiver of a bit transfer. A channel that does not include sender-receiver synchronization variables in a system allowing the receiver-sender transfer of messages is called a quasi-synchronous channel. The idea of quasi-synchronous channels was introduced by Schaefer in 1974 [Reed and Kanodia78].
Figure Missing
Figure 2-5. Representation of a Covert Channel between Sender S and Receiver R (where Lh > Li or Lh * * Li)
In all patterns of sender-receiver synchronization, synchronization data may be included in the data variable itself at the expense of some bandwidth degradation. Packet-formatting bits in ring and Ethernet local area networks are examples of synchronization data sent along with the information being transmitted. Thus, explicit sender-receiver synchronization through a separate variable may be unnecessary. Systems implementing mandatory security models allow messages to be sent from the receiver to the sender whenever the security level of the sender dominates that of the receiver. In these cases, explicit receiver-sender synchronization through a separate variable may also be unnecessary.
The representation of a covert channel illustrated in Figure 2-5 can also be used to distinguish between scenarios of storage and timing channels. For example, a channel is a storage channel when the synchronization or data transfers between senders and receivers use storage variables, whereas a channel is a timing channel when the synchronization or data transfers between senders and receivers include the use of a common time reference (e.g., a clock). Both storage and timing channels use at least one storage variable for the transmission/sending of the information being transferred. (Note that storage variables used for timing channels may be ephemeral in the sense that the information transferred through them may be lost after it is sensed by a receiver. We discuss this in more detail in Appendix A.) Also, a timing channel may be converted into a storage channel by introducing explicit storage variables for synchronization; and vice versa, a storage channel whose synchronization variables are replaced by observations of a time reference becomes a timing channel.
Based on the above definitions of storage and timing channels, the channels of Examples 1 and 2 are storage channels. Examples 3 and 4 below illustrate scenarios of timing channels. Appendix A presents additional examples of both storage and timing channels.
Figure Missing
Figure 2-6. Two CPU Timing Channels
In the second example of Figure 2-6, the sender transmits information to the receiver by encoding symbols, say 0s and 1s, in the time between two successive CPU quanta. This channel is called the "interquantum-time channel" [Huskamp78], and is shown in Figure 2-6(b) for the case where only the sender and the receiver appear in the system. To send information, the sender and the receiver agree on set times for sending the information. The transmission strategy is for the sender to execute at time "ti" if the i-th bit is 1, and to block itself if the i-th bit is 0. The receiver can tell whether the sender executes at time ti because the receiver cannot execute at the same time.
Whenever two processes at two different levels execute concurrently on two separate processors, a covert channel appears that is similar to the CPU interquantum channel presented in Example 3. That is, the sender and the receiver processes establish by prior agreement that the sender process executes at time"ti"if the i-th bit is a 1 and does not execute (or at least does not execute memoryreferencing instructions) at time "ti" if the i-th bit is a 0. The receiver can execute a standard set of memory-referencing instructions and time their execution. Thus, the receiver can discover whether the sender executes at time "ti" by checking whether the duration of the standard set of timed instructions was the expected 1 or longer. As with the CPU channels of Example 3, these channels appear in any multiprocessor system regardless of the nondiscretionary model interpretation. Note that adding per-processor caches, which helps decrease interprocessor contention to shared hardware resources, cannot eliminate these channels. The sender and receiver processes can fill up their caches and continue to exploit interprocessor contention to transmit information.
Appendix A provides other examples of timing channels, which also appear due to the sharing of other hardware resources.
Figure Missing
Figure 2-7. Examples of Shared Hardware Resources in Multiprocessor Architectures
As with any communication channel, covert channels can be noisy or noiseless. A channel is said to be noiseless if the symbols transmitted by the sender are the same as those received by the receiver with probability 1. With covert channels, each symbol is usually represented by one bit and, therefore, a covert channel is noiseless if any bit transmitted by a sender is decoded correctly by the receiver with probability 1. That is, regardless of the behavior of other user processes in the system, the receiver is guaranteed to receive each bit transmitted by the sender.
The covert channel of Example 2 is a noiseless covert channel. The sender and receiver can create and remove private upgraded directories, and no other user can affect in any way whether the receiver receives the error/no_error signal. Thus, with probability 1, the receiver can decode the bit value sent by the sender. In contrast, the covert channels of Examples 3 and 4 are noisy channels because, whenever extraneous processes-not just the sender and receiver-use the shared resource, the bits transmitted by the sender may not be received correctly with probability 1 unless appropriate error-correcting codes are used. The error-correcting codes used depend on the frequency of errors produced by the noise introduced by extraneous processes (shown in Figure 2- 5) and decrease the maximum channel bandwidth. Thus, although error-correcting codes help change a noisy channel into a noiseless one, the resulting channel will have a lower bandwidth than the similar noise-free channel.
We introduce the term "bandwidth" here to denote the rate at which information is transmitted through a channel. Bandwidth is originally a term used in analog communication, measured in hertz, and related to information rate by the "sampling theorem" (generally attributed to H. Nyquist although the theorem was in fact known before Nyquist used it in communication theory [Haykin83]). Nyquist's sampling theorem says that the information rate in bits (samples) per second is at most twice the bandwidth in hertz of an analog signal created from a square wave. In a covert channel context, bandwidth is given in bits/second rather than hertz, and is commonly used, in an abuse of terminology, as a synonym for information rate. This use of the term "bandwidth" is also related to the notion of "capacity." The capacity of a channel is its maximum possible error-free information rate in bits per second. By using error-correcting codes, one can substantially reduce the error rates of noisy channels. Error-correcting codes decrease the effective (i.e., error-free) information rate relative to the noisy bit rate because they create redundancy in the transmitted bit stream. Note that one may use error-detecting, rather than error-correcting, codes in scenarios where the receiver can signal the sender for retransmissions. All of these notions are standard in information theory [Gallager68].
Synchronization variables or information used by a sender and a receiver may be used for operations on multiple data variables. Multiple data variables, which could be independently used for covert channels, may be used as a group to amortize the cost of synchronization (and, possibly, decoding) information. We say the resulting channels are aggregated. Depending on how the sender and receiver set, read, and reset the data variables, channels can be aggregated serially, in parallel, or in combinations of serial and parallel aggregation to yield optimal (maximum) bandwidth.
If all data variables are set, reset, and read serially, then the channel is serially aggregated. For example, if process Ph of Example 2 (Figure 2-4) uses multiple upgraded directories designated "empty/nonempty" before transferring control to process Pi, the signaling channel will be serially aggregated. Similarly, if all data variables are set, reset, and read in parallel by multiple senders and receivers, then the channel is aggregated in parallel. Note that combinations of serial/parallel aggregaton are also possible. For example, the data variables may be set in parallel but read serially and vice versa. However, such combinations do not maximize bandwidth and are, therefore, of limited interest.
Parallel aggregation of covert channel variables requires, for bandwidth maximization reasons, that the sender and receiver pairs be scheduled on different processors at the same time as a group, as illustrated in Figure 2-8 and in [Gligor86]. Otherwise, the bandwidth of the parallel aggregation degrades to that of a serially aggregated channel. The application programmer can strictly control group scheduling of senders and receivers in multiprocessor operating systems such as Medusa or StarOS [Osterhout80, Jones79], which use "coscheduling" [Osterhout82]. Also group scheduling may be possible in multiple workstation systems such as those used in LOCUS [Walker83] or Apollo [Leach83] whenever multiple workstatons are available to a single application. In such systems, the analysis of individual covert channels is insufficient to determine the maximum covert channel bandwidth.
Figure Missing
Figure 2-8. Example of n Channels Aggregated in Parallel
Parallel aggregation of covert channels also requires, for bandwidth maximizaton reasons, that the synchronization messages between all senders, and those between all receivers, be transmitted at a much higher speed than those between senders and receivers. In practice, messages sent among senders, and those sent among receivers, have negligible transmission delays compared to those used by covert channels between senders and receivers. (Also, note that all messages among senders and those among receivers are authorized messages.)
An unresolved issue of covert channel definition is whether one can make a distinction between a covert channel and a flaw introduced by the implementation of the security models. In other words, one would like to differentiate between implementation flaws and covert channels, if possible, for practical reasons. For example, both implementors and evaluators of systems supporting mandatory access controls in class B1 could then differentiate between flaws and covert channels. They could determine whether instances of leakage of classified information must be eliminated or otherwise handled or ignored until the B2 level and above.
The covert communication Definition 5 does not differentiate between covert channels and interpretation or TCB specification flaws. This definition implies that, in a fundamental sense, covert channels are in fact flaws of nondiscretionary access control policy implementations, which are sometimes unavoidable in practice regardless of the implementors' design (e.g., Example 3). However, the focus of that definition on the notion of model implementation may help provide a criterion for distinguishing between different types of covert channels or implementation flaws.
To define a distinguishing criterion, let us review Examples 1-4. Examples 1 and 2 show that a change of the TCB specification can, in principle, eliminate the existent covert channels in the specific systems under consideration. In contrast, Examples 3 and 4 show that as long as any system allows the sharing of the CPUs, busses, memory, input/output (I/O) and other hardware resources, covert channels will appear for any TCB specification. Furthermore, Example 2 illustrates that, in many systems, a change of TCB specification that would eliminate a covert channel may sometimes be impractical. That is, evidence may exist showing that contemplated changes of the TCB specification would cause a significant loss of compatibility with existing interfaces of a given system. Similar examples can be found to illustrate that changes of TCB specifications may help eliminate other covert channels (or flaws) at the expense of loss of functionality or performance in a given system (e.g., Example 1).
The following criterion may help distinguish between different types of covert channels (or flaws) in practice, thereby providing the necessary input for covert channel, or flaw, handling at levels B1 versus levels B2-A1:
The above criterion for distinguishing different types of covert channels (or flaws) suggests the following differentiation policy for B1 and B2-A1 systems. For B1 systems, there should be no handling obligation of fundamental covert channels; specific TCB channels should be handled under the policies in force for classes B2-A1 (as recommended in Chapter 5 of this guide); unjustifiable channels should be eliminated by a change of TCB specification or model implementation for any B-rated systems.
We discuss in this chapter the representation of a covert channel within a system, the sources of information for covert channel identification, and various identification methods that have been used to date and their practical advantages and disadvantages. We also discuss the TCSEC requirements for covert channel identification and make additional recommendations.
A covert channel can be represented by a TCB internal variable and two sets of TCB primitives, one for altering (PAh) and the other for viewing (PVi) the values of the variable in a way that circumvents the system's mandatory policy. Multiple primitives may be necessary for viewing or altering a variable because, after viewing/altering a variable, the sender and/or the receiver may have to set up the environment for sending/reading the next bit. Therefore, the primary goal of covert channel identification is to discover all TCB internal variables and TCB primitives that can be used to alter or view these variables (i.e., all triples < variable; PAh, PVi>). A secondary, related goal is to determine the TCB locations within the primitives of a channel where time delays, noise (e.g., randomized table indices and object identifiers, spurious load), and audit code may be placed for decreasing the channel bandwidth and monitoring its use. In addition to TCB primitives and variables implemented by kernel and trusted processes, covert channels may use hardware-processor instructions and user-visible registers. Thus, complete covert channel analysis should take into account a system's underlying hardware architecture, not just kernels and trusted processes.
The primary sources of information for covert channel identification are:
The advantage of using system reference manuals for both TCB-primitive and processor- instruction descriptions is the widespread availability of this information. Every implemented system includes this information for normal everyday use and, thus, no added effort is needed to generate it. However, there are disadvantages to relying on these manuals for covert channel identification. First, whenever system reference manuals are used, one can view the TCB and the processors only as essentially "black boxes." System implementation details are conspicuous by their absence. Thus, using system reference manuals, one may not attain the goal of discovering all, or nearly all, channels. Whenever these manuals are the only sources of information, the channel identification may only rely on guesses and possibly on analogy with specifications of other systems known to contain covert channels. Second, and equally important, is the drawback that analysis based on system reference information takes place too late to be of much help in covert channel handling. Once a system is implemented and the manuals written, the option of eliminating a discovered covert channel by removing a TCB interface convention may no longer be available. Third, few identification methods exist that exhibit any degree of precision and that can rely exclusively on information from system reference manuals. The inadequacy of using only system reference manuals for CCA is illustrated in Example 6 of Section 3.2.3.
Most identification methods developed to date have used formal top-level TCB specifications as the primary source of covert channel identification. The use of top-level specifications has significant advantages. First, these specifications usually contain more detailed, pertinent information than system reference manuals. Second, use of top-level specifications helps detect design flaws that may lead to covert channels in the final implementation. Early detection of design flaws is a useful prerequisite for correct design because one can minimize efforts expended to correct design flaws. Third, tools aiding the identification process exist for the FTLS and thus one gains additional assurance that all channels appearing within the top-level specifications are found (see Appendix B).
However, total reliance on analysis of top-level specifications for the identificaton of covert channels has two significant disadvantages. First, it cannot lead to the identification of all covert channels that may appear in implementation code. Formal methods for demonstrating the correspondence between information flows of top-level specifications and those of implementation code do not exist to date. Without such methods, guarantees that all covert storage channels in implementation code have been found are questionable at best. The only significant work on specification-to-code correspondence on an implemented system (i.e., the Honeywell SCOMP [Benzel84]) reported in the literature to date has been thorough but informal. This work shows that, in practice, a significant amount of implementation code has no correspondent formal specifications. Such code includes performance monitoring, audit, debugging, and other code, which is considered security-policy irrelevant but which, nevertheless, may contain variables providing potential storage channels.
Second, formal/descriptive top-level specifications of a TCB may not include sufficient specification detail of data structures and code to detect indirect information flows within TCB code that are caused by the semantics of the implementation language (e.g., control statements, such as alternation statements, loops, and so on; pointer assignments, variable aliasing in structures [Schaefer89, Tsai90]). Insufficient detail of specifications used for information flow and storage channel analysis may also cause inadequate implementation of nondiscretionary access controls and channel-handling mechanisms. This is the case because, using the results of top- level specification analysis, one cannot determine with certainty the placement of code for access checks, channel use audits, and time delays to decrease channel bandwidth within TCB code.
In contrast with the significant efforts for the analysis of design specifications, little practical work has been done in applying CCA to implementation code or to hardware. Identifying covert storage channels in source code has the advantages that (1) potentially all covert storage channels can be found (except those caused by hardware), (2) locations within TCB primitives for placement of audit code, de-lays, and noise can be found, and (3) adequacy of access-check placement within TCB primitives could be assessed [Tsai90]. However, analysis of TCB source code is very labor- intensive, and few tools exist to date to help alleviate the dearth of highly skilled personnel to perform such labor-intensive activity.
All of the widely used methods for covert channel identification are based on the identification of illegal information flows in top-level design specifications and source code, as first defined by [Denning76, 77, 83] and [Millen76]. Subsequent work by [Andrews and Reitman80] on information-flow analysis of programming language statements extended Denning's work to concurrent-program specifications.
In all flow-analysis methods, one attaches information-flow semantics to each statement of a specification (or implementation) language. For example, a statement such as "a := b" causes information to flow from b to a (denoted by b -> a) whenever b is not a constant. Similarly, a statement such as "if v = k then w := b else w := c" causes information to flow from v to w. (Other examples of flows in programming-language statements are found in [Denning83, Andrews and Reitman80, Gasser88]). Furthermore, one defines a flow policy, such as "if information flows from variable x to variable y, the security level of y must dominate that of x." When applied to specification statements or code, the flow policy helps generate flow formulas. For exampIe, the flow formula of "a: = b" is security level(a) > security_level(b). Flow formulas are generated for complete program and TCB-primitive specifications or code based on conjunctions of all flow formulas of individual language statements on a flow path. (Formula simplifications are also possible and useful but not required.) These flow formulas must be proven correct, usually with the help of a theorem prover. If a pro-gram flow formula cannot be proven, the particular flow can lead to a covert channel flow and further analysis is necessary. That is, one must perform semantic analysis to determine (1) whether the unproven flow is real or is a false illegal flow, and (2) whether the unproven flow has a scenario of use (i.e., leads to a real-not just a potential- channel). Example 5 of this section and Examples 7 and 8 of Section 3.3 illustrate the notion of false illegal flow and the distinction between real and potential channels.
Various tools have been built to apply syntactic flow analysis to formal specifications. For example, the SRI Hierarchical Development Methodology (HDM) and Enhanced HDM (EHDM) tools [Feiertag80, Rushby84] apply syntactic analysis to the SPECIAL language. Similarly, the Ina Flo tool of the Formal Development Methodology (FDM) [Eckmann87] and the Gypsy tools [McHugh and Good85, McHugh and Ackers87] have been used for syntactic information-flow analyses. Appendix B reviews these tools. Experience with information-flow analysis in practice is also reported in references [Millen78, MiIlen81].
Syntactic information-flow analysis has the following advantages when used for covert channel identification:
Practical examples of false illegal flows appear in all covert channel analyses relying exclusively on syntactic flow analysis. For example, sixty-eight formulas that could not be proven have been found in the SCOMP analysis using the Feiertag Flow tool [Benzel84, Millen89b]. Only fourteen of these flows caused covert channels; the balance were all false illegal flows. Similar examples can be given based on experience with other flow tools. For instance, even in a small (twenty-line) program written in Ina Jo, the lna Flow tool discovered one hundred-seventeen illegal flows of which all but one were false [Cipher90].
Information-flow analysis does not lend itself to use on informal (e.g., English language) specifications. This means that, if one uses information-flow analysis for B2-B3 class systems, one should apply it to source code. Furthermore, discovery of illegal flows in formal top-level specifications (for class A1 systems) offers little help for identifying TCB locations where covert channel handling code may be necessary. The identification of such locations requires semantic analysis of specifications and code.
Figure Missing
Figure 3-1. An Example of a False Illegal Flow Caused by Syntactic Flow Analysis
Reference [Tsai90] presents a method for identification of potential storage channels based on (1) the analysis of programming language semantics, code, and data structures used within the kernel, to discover variable alterability/visibility; (2) resolution of aliasing of kernel variables to determine their indirect alterability; and (3) information-flow analysis to determine indirect visibility of kernel variables (e.g., the "msgque Æ mode" variable in Figure 3-1). These steps precede the application of the nondiscretionary (secrecy or integrity semantic) rules specified in the interpretation of the security model, and implemented in code, to the shared variables and kernel primitives. This last step helps distinguish the real storage channels from the legal or inconsequential ones. The delay in the application of these rules until the security levels of shared variables can be determined with certainty (i.e., from the levels of the objects included in the flows between variables) helps avoid additional (manual) analysis of false illegal flows. Furthermore, discovery of all locations in kernel code where shared variables are altered/viewed allows the correct placement of audit code and time-delay variables for channel-handling mechanisms, and of access checks for nondiscretionary policy implementation.
A disadvantage of this method is that its manual application to real TCBs requires extensive use of highly skilled personnel. For example, its application to the Secure Xenix system required two programmer-years of effort. Thus, using this method in real systems requires extensive use of automated tools. Although the method is applicable to any implementation language and any TCB, its automation requires that different parser and flow generators be built for different languages.
The addition of an automated tool for semantic information-flow analysis to syntactic analysis is reported in [He and Gligor90]. The semantic component of this tool examines all flows visible through a TCB interface and separates the legal from the illegal ones. Since this analysis uses the interpretation of a system's mandatory security model in source code, false illegal flows are not detected. Although one can apply this method to any system, the tool component for semantic analysis may differ from system to system because the interpretation of the mandatory security model in a system's code may differ from system to system. The separation of real covert channels from the potential ones, which requires real scenarios of covert channel use, must still be done manually. Compared to the separation of all potential channels from flows allowing a variable to be viewed/altered through a TCB interface, the separation of real channels from potential channels is not a labor-intensive activity since the number of potential channels is typically several orders of magnitude smaller than the number of flows through a TCB interface.
The SRM method for identifying covert channels was proposed by [Kemmerer83], and used in several projects [Haigh87]. When applied to TCB specifications or code, this method requires the following four steps:
The major advantage of the SRM method over syntactic information flow analysis, namely its applicability to informal TCB top-level specifications, is diminished to some extent by the fact that informal top-level specifications lack sufficient detail. We illustrate this observation (1) by showing the results of applying the SRM method to a UNIX TCB specification as found in the Xenix reference manuals [IBM87] using three internal variables of the file subsystem (i.e., "mode," "lock," and "file_table") as the target of CCA, and (2) by comparing this analysis with the automated analysis performed for the same three variables and the Secure Xenix TCB source code with the tool presented in [He and Gligor90].
Figure 3-2 illustrates the results of this comparison. In this figure, the bold-faced matrix entries denote the information added to the original SRM matrix as a result of the automated analysis. This figure shows that about half of the relevant primitives were missed for one of the variables (i.e., "mode") and a third were missed for another variable (i.e., "file_table").
Furthermore, more than half of the R/M entries constructed for the primitives found to reference the three variables in system manuals were added R/M designators by the automated analysis of source code. Although different results can be obtained by applying the SRM method to different informal specifications, this example illustrates that the application of SRM (and of any other method) to informal specification can be only as good as the specifications.
Figure Missing
Figure 3-2. Shared Resource Matrix for Three Variables
Noninterference analysis of a TCB requires one to view the TCB as an abstract machine. From the point of view of a user process, a TCB provides certain services when requested. A process' requests represent the abstract machine's inputs, the TCB responses (e.g., data values, error messages, or positive acknowledgements) are its outputs, and the contents of the TCB internal variables constitute its current state. Each input results in a (TCB) state change (if necessary) and an output. Each input comes from some particular process running at a particular security level, and each output is delivered only to the process that entered the input that prompted it.
[Goguen and Meseguer82] formulated the first general definition of information transmission in the state-machine view of a TCB, generalizing on an earlier but more restricted definition by [Feiertag80]. They defined the concept of noninterference between two user processes. The definition was phrased in terms of an assumed initial or start-up state for the machine. It stated, in effect, that one user process was noninterfering with another when the output observed by the second user process would be unchanged if all inputs from the first user process, ever since the initial state, were eliminated as though they had never been entered. Goguen and Meseguer reasoned that if inputs from one user process could not affect the outputs of another, then no information could be transmitted from the first to the second. (One can verify this property using Shannon's definition of information transmission [Millen 89b].)
To define noninterference precisely, let X and Y be two user processes of a certain abstract- machine TCB. If w is a sequence of inputs to the machine, ending with an input from Y, let Y(w) be the output Y receives from that last input (assuming the machine was in its initial state when w was entered). To express noninterference, w/X is the subsequence that remains of w when all X- inputs are deleted, or "purged," from it. Then X is noninterfering with Y if, for all possible input sequences w ending with a Y-input, Y(w) = Y(w/X).
It is somewhat unintuitive that noninterference relates a whole sequence of inputs, including, perhaps, many X-inputs, to a single Y-output. In CCA, the traditional view is that whenever a covert channel exists between X and Y, each individual X-input has an effect on the next Y-output. Noninterference analysis suggests another view may be appropriate, however. Note that user process Y might enter an input to request an output at any time. Suppose, in fact, that Y enters an input every time X did. Ignoring other inputs, the overall input sequences looks like: x1y1x2y2 . . . xnyn. The definition of noninterference applies not only to the whole sequence, but to all the initial segments of it ending in a Y-input, namely: (x1y1), (x1y1x2y2), . . . ` (x1y1 xnyn). Noninterference requires that every Y output is unaffected by all previous X inputs. Thus, it seems necessary to analyze all past X inputs because of the following: Suppose each X input is reported as a Y output after some delay; a covert channel arises just as it would if the X input came out immediately in the next Y output.
In practice, it is cumbersome to analyze the entire history of inputs to the machine since its initial state. However, this analysis is unnecessary because the current state has all the information needed to determine the next Y-output. Thus, noninterference of X with Y can be expressed in terms of the current state instead of the whole prior input history.
Clearly, if X is noninterfering with Y, an X input should have no effect on the next Y output. Noninterference is actually stronger than this, however, since it requires that an X input has no effect on any subsequent Y output. To avoid analyzing unbounded input sequences, it is useful to partition TCB states into equivalence classes that are not distinguishable using present or subsequent Y outputs. That is, two states are Y-equivalent if (1) they have the same Y output in response to the same Y input, and (2) the corresponding next states after any input are also Y- equivalent. (This definition is recursive rather than circular; this is computer science!) [Goguen and Meseguer84] proved a theorem, called the "Unwinding Theorem," which states that X is noninterfering with Y if and only if each X input takes each state to a Y-equivalent state; a simpler version of this theorem was given by [Rushby85].
Unwinding is important because it leads to practical ways of checking noninterference, especially when given a formal specification of a TCB that shows its states and state transitions. The multilevel security policy requires that each process X at a given security level should interfere only with a process Y of an equal or higher security level. To apply this requirement in practice, the TCB states must be defined, and the Y-equivalent states must be determined. A straightforward way of identifying Y-equivalent states in a multilevel secure TCB is to label state variables with security levels. If Y is cleared for a Security level s, then the two states are Y-equivalent if they have the same values in those state variables having a security level dominated by s. A less formal way of expressing this statement is that Y has (or should have) a blind spot when it tries to observe the current state. Y can observe state variables at or below its own level, but state variables at a higher level are in the blind spot and are invisible. So two states are Y-equivalent if they look the same under Y's "blind spot" handicap.
The state-variable level assignment must have the property that the effect of any input turns equivalent states into equivalent states. This means that invisible variables cannot affect the visible part of the state. This property is one of three that must be proved in a noninterference analysis. The other two properties are that (1) any return values reported back to Y depend only on variables visible to Y, and (2) an input from a higher level user process X cannot affect the variables visible to user process Y.
Noninterference analysis has the following important advantages:
Covert channel identification methods applied statically to top-level specifications or to code produce a list of potential covert channels. Some of the potential covert channels do not have scenarios of real use. These potential channels are artifacts of the identification methods. However, false illegal flows do not necessarily cause these potential channels. As illustrated in Figure 3-1(b), all flows have a condition that enables the flow to take place as the system runs (e.g., dynamically). A general reason why a potential covert channel may not necessarily be a real covert channel is that, at run time, some flow conditions may never become true and, thus, may never enable the illegal flow that could create a covert channel. Another reason is that the alteration (viewing) of a covert channel variable may not be consistent with the required alteration (viewing) scenario. For example, a field of the variable may be altered but it could not be used in the scenario of the covert channel. Similarly, not all TCB primitives of a channel can be used in real covert channel scenarios. The ability to use some TCB primitives of a channel to transfer information may depend on the choice of the primitive's parameters and the TCB state. Examples 7, 8, and 9 illustrate these cases. To determine whether a potential covert channel is a real covert channel, one must find a real-time scenario enabling an illegal flow.
Figure 3-3(a) illustrates the difference between potential and real covert channels. Two UNIX TCB primitives "read" and "write" share the same internal function "rdwr" but pass different values to the parameter of this function. CCA on the internal function "rdwr" reveals all possible information flows within "rdwr" (i.e., both flows that lead to real channels and flows that only lead to potential channels). Among the latter are flows with the condition "mode = FWRlTE." These flows cannot be exploited by TCB primitive "read" because it can never enable this condition. Similarly, TCB primitive "write" cannot exploit those flows with the condition "mode = FREAD."
Figure Missing
Figure 3-3. Potential and Real Covert Channels Corresponding to Different Flow Partitions
Thus, among the potential covert channels arising from the invocation of the internal function "rdwr," those with condition "mode = FWRlTE" cannot be real covert channels for the "read" primitive, and those with the condition "mode = FREAD" cannot be real covert channels for the "write" primitive. Real-time scenarios do not exist for those potential covert channels. Figure 3-3 (b) shows the partitioning of flows in internal function "rdwr" based on whether a flow can be exploited by the "read" and "write" primitives.
Figure Missing
Figure 3-4. Examples of Potential and Real Channels
Figure 3-4 illustrates examples of real and potential covert channels of Secure Xenix. The two tables shown in Figure 3-4 contain two basic types of covert storage channels: resource-exhaustion and event-count channels. Resource-exhaustion channels arise wherever system resources are shared among users at more than one security level. To use a resource-exhaustion channel, the sending process chooses whether or not to exhaust a system resource to encode a signal of a 0 or 1. The receiving process detects the signal by trying to allocate the same system resource. Depending on whether the resource can be allocated, the receiving process can determine the value of the signal from the sending process.
In event-count channels, the sending process encodes a signal by modifying the status of a shared system resource (but not exhausting the resource). By querying the status of the resource, either through TCB primitives returning the resource status explicitly or by observing the return result of some TCB primitives that allocate the resource, the receiving process can detect the signal from the sending process.
In the tables of Figure 3-4, each row is marked with a TCB primitive and each column with a shared global variable. Entries in the tables indicate whether a TCB primitive can alter (A or a) and/or view (V or v) the corresponding global variable. An upper-case A in an entry indicates that the TCB primitive can alter the global variable as the means of encoding and transferring information through the variable. Similarly, an upper-case V in an entry indicates that the TCB primitive can view the value of the global variable and detect the signal transmitted by sending user processes. Thus, for any shared global variable, the set of TCB primitives that have a capital A and those that have a capital V constitute a real covert channel. For example, TCB primitives "creat" and "open" can be used by the sending and the receiving processes to transfer information through the shared global variable representing the "file_table" in the system. On the other hand, a lower- case a in an entry means that, although the TCB primitive can alter the global variable, the alteration cannot be used for encoding information in the global variable. For example, the execution of the TCB primitive "fork" alters the "file_table" because it increments the file reference count for the child process it creates. This alteration, however, is different from that of allocating a file-table entry and, thus, it does not provide a real scenario for sending a signal. Similar reasoning explains why the entries marked with a lower-case v in Figure 3-4 cannot be used in real scenarios of covert channels.
The distinction between an alteration of a global variable that can be used to encode information (i.e., entry denoted by A) and one that cannot (i.e., entry denoted by a) can be eliminated if a finer partitioning of the "file table" structure is performed. That is, if the file reference count of the "file_table" is viewed as a separate variable within the "file_table" structure, then the TCB primitive "fork" would not appear to alter the "file_table" structure. Instead, "fork" would alter only the new variable, namely, the file reference count. In either case, however, the covert channel analysis should yield the same results.
The covert channel examples of Figure 3-5 illustrate both system-state and parameter dependencies found in UNIX systems. For example, the primitive "creat" can alter (i.e., decrement) the total number of free inodes (nfi) only if the object to be created does not exist. If the object exists, "creat" has no effect on nfi. In addition, the primitive "creat" can be used to alter (i.e., increment) the total number of free blocks (nfb) in the system if the file being created currently exists. That is, if the file exists, "creat" truncates the file, and as a result increments nfb. Otherwise, "creat" has no effect on nfb. (The disk-block-space channel is also affected by this condition.) Furthermore, the alteration of the disk-block-space channel, and of the nfi and nfb channels by the primitive "creat," is determined by the file system specified in the parameter of the "creat" invocation.
Figure Missing
Figure 3-5. An Example of the Use of Multiple Channels by Three Processes
The example of Figure 3-5 also illustrates the combined state and parameter dependencies. Consider again the channel that modulates the nfb and the disk-block-space channel. Primitive "chsize" can be used to alter these channel variables (i.e., deallocate memory and increase the total number of free blocks) only if the file on which it is applied exists, and only if its parameter indicates file shrinkage. When used to expand the size of an existing file, primitive "chsize" does not alter the channel variables but merely changes the ip-i_size field of the inode.
Other examples of parameter dependency and combined state and parameter dependencies, unrelated to those of Figure 3-5, can be found. For example, the primitive "semget(key, nsems, semflg)" can affect the semaphore-identifier channel and the semaphore-map exhaustion channel. Within this primitive, if parameter "key" is equal to IPC_CREAT, thereby denoting the creation of a semaphore, a semaphore identifier, its associated semaphore data structure, and a set containing "nsems" semaphores are created for key. In contrast, if parameter key is not equal to IPC_CREAT, nothing is created.
Furthermore, if parameter key does not already have a semaphore identifier associated with it, and if the Boolean expression (semflg and IPC_CREAT) is true, a "semget" call creates for parameter key a semaphore identifier, its associated data structure, and the set containing "nsems" semaphores. If parameter key already has a semaphore identifier associated with it, a new semaphore structure is not created.
Covert channel identification requirements appear for the classes B2-A1 of the [NCSC TCSEC]. The B2 requirements of CCA state that the "system developer shall conduct a thorough search for storage channels...."
For class B2, the search for covert storage channels should be conducted on system reference manuals and on the DTLS of the TCB. Although the TCSEC does not require storage channel identification in the TCB source code and in hardware (microcode) specifications, such a search would ensure the completeness of the identification results. Although no specific identification method is required, arbitrary, ad hoc, undocumented methods, which system evaluators cannot repeat on independently selected test cases, are unacceptable. This nonacceptance is justified by the notion that system developers must conduct a thorough search for covert channels and an evaluation team must evaluate the search.
Use of any identification method on informal top-level specifications may yield incomplete results, as illustrated in Example 6 of this section in the context of the SRM method. For this reason, it seems important to apply the storage channel identification method to the TCB source code. Otherwise, the thoroughness of the covert channel identification search may be in doubt. Furthermore, source-code analysis may be useful in the definition of covert channel scenarios that help distinguish real and potential channels. Therefore, we recommend analyzing both the DTLS and the source code for covert channel identification at class B2.
The B3-class requirement of the TCSEC extends the above B2-class requirement to all covert channels (i.e., to timing channels). Although this extension imposes no added requirement in terms of the identification method used, timing channel scenarios should be developed. These scenarios should include all system sources of independent timing such as the CPU and the I/O processors. Inclusion of all these sources will provide additional assurance that classes of timing channels are not overlooked. [Huskamp78] provides an example of complete timing channel analysis for the CPU scheduling channels.
The A1-class requirement of CCA includes all the B2-B3-class requirements and extends them by stating, "Formal methods shall be used in analysis."
One may apply CCA methods to both formal specifications and source code of the TCB. Examples of such methods include syntactic information-flow analysis (with or without the use of semantic analysis), SRM, and noninterference analysis. Other formal methods for covert channel identification may exist and may be equally suitable at level A1. The identification method chosen by the developer should be applied to the FTLS. Unless the identification of covert channels is made a part of the specification-to-code correspondence, in which case source-code analysis is included, we recommend complementing FTLS analysis with formal or informal source-code analysis. Otherwise, covert channels may remain undetected.
In this chapter we discuss various factors that affect the covert channel bandwidth computation, including TCB primitive selection, parameter and state dependencies, and channel aggregation. We also present both information-theory-based and informal methods for maximum bandwidth estimation, and discuss various factors that degrade the covert channel bandwidth. The TCSEC requirements and recommendations are also discussed.
The computation of covert channel bandwidths is one of the key aspects of covert channel analysis. This is the case because most decisions about how to handle identified channels rely on the determination of channel bandwidth. Therefore, it is important to examine briefly the factors that primarily affect the computation of covert channel bandwidth.
Two of the most important factors affecting the bandwidth of a covert channel in any operating system or hardware platform are the presence of noise and the delays experienced by senders and receivers using the channel. The primary sources of noise and delay are the processes Up, . . . ,Uq shown in Figure 2-5, which can interpose themselves due to scheduling of various hardware resources between senders and receivers. Although these processes can degrade the maximum attainable bandwidth of a channel significantly (e.g., up to about 75% [Tsai and Gligor88]), the degradation is not certain in all architectures and at all times since it depends on the nature of the multiprogrammed system (e.g., single user, multiprocess workstation, multiuser time sharing system) and on the system load. Thus, while the noise and delay factors are significant, the computation of the maximum attainable bandwidth of any channel must discount both noise and delays, and must assume that only the senders and receivers are present in the system [Millen89a].
In general, the attainable maximum bandwidth (i.e., capacity) depends on the choice of symbol encoding scheme agreed upon by a sender and a receiver. Coding schemes exist that allow the exploitation of the maximum attainable bandwidth of a channel on the distribution of symbols in the space of transmitted messages [Millen89a]. However, informal covert channel analysis usually assumes a 0 or a 1 represents each symbol transmitted. Thus, the distribution of 0s and 1s becomes an important factor of bandwidth computation whenever using informal methods. Where the time required to transmit a 0 is close (on the average) to the time required to transmit a 1, one can assume that 0s and 1s are used with approximately equal frequency. This assumption is based on the fact that the bandwidth (i.e., capacity) of discrete memoryless channels is maximized under such distributions. (Section 4.2 below illustrates both an informal bandwidth-computation method, where such distributions are assumed, and an information-theory-based method, where such distributions are not assumed.)
Informal bandwidth computation methods do not achieve, in general, the maximum bandwidth of a channel because they do not use appropriate coding techniques. Formal bandwidth- computation methods not only allow the precise determination of attainable maximum bandwidth but also help define coding schemes that can be used to attain those bandwidths [Millen89a].
In most systems, covert channel identification associates multiple TCB primitives with a covert channel variable. For example, most UNIX covert channel variables can be altered or viewed by a number of primitives that varies between about ten and forty. Among the primitives of each variable, one must select those having the highest speed for the bandwidth computation. Although one should measure each primitive's speed with only senders and receivers using the system, one should not conduct these measurements independently of the covert channel scenario of use (i.e., without using parameters and TCB state conditions that would be present when a channel is in use). Otherwise, the bandwidth computation could lead to unrealistically high or low values. Low values may cause security exposures whereas high values may cause performance degradation whenever delays are used based on bandwidth values. We can illustrate the latter case by the "chsize primitive of UNIX. The speed of this primitive depends on whether a file is shrunk (low speed) or expanded (higher speed). However, the use of "chsize" with the expand option cannot be made in covert channels requiring disk free block alteration because this primitive does not alter the disk free block variable. We discuss this in more detail in the next section.
The performance measurements of the TCB primitives of covert channels require one to include not only the altering and viewing primitives but also the performance of the primitives that initialize the environment for the altering and viewing of a variable. The environment initialization primitives may differ for the altering and viewing primitives. For example, the environment initialization primitive for altering a variable to transmit a 1 may differ from that necessary to transmit a 0. Similarly, the environment initialization primitives for viewing a 1 may differ from those necessary for viewing a 0. Furthermore, the same primitive may use different amounts of time depending upon whether it is used to set (read) a zero or a one (e.g., whether it returns an error). Scenarios of covert channel use are needed to determine which environment initialization primitives must be taken into account. Section 4.2 provides examples of different environment initialization primitives and their use for two real covert channels of UNIX.
Also included in the measurements is the process- or context-switching time. The measurement of this time is needed because, during the transmission of every bit of information through a covert channel, control is transferred between the sender and receiver at least twice. In most operating systems, the measurement of the minimum process switching time is a fairly complex task. The reason for this complexity is that with every process switch the measurement environment changes and, therefore, the measurement of each switch may yield different values. Sometimes it is also difficult to measure individual process-switching times because process switching may be possible only as a side-effect of some primitives. Other processes may be scheduled to run during a switch from one process to another, thereby adding unwarranted delay to switching time. To eliminate the difference between measured process-switching times within the same system, one must ensure that only a few processes are present in the system when taking measurements and repeat the measurements a large number of times (e.g., a hundred thousand times) to ensure choosing the minimum value.
Real scenarios of covert channel use include sender-receiver synchronization. This synchronization delays the covert channel and, therefore, decreases the channel's bandwidth. However, since one cannot predict the synchronization scenario (because it is privately agreed upon by the sender and receiver), we generally assume the bandwidth decrease caused by synchronization is negligible. This assumption helps ensure computing the maximum bandwidth.
All primitive measurements and process-switching time measurements must be repeatable. Otherwise, independent evaluators cannot verify the bandwidth computations.
TCB primitive measurements and process switching times depend very heavily on a number of system architecture parameters. These parameters include:
In general, both serial and parallel aggregation of distinct covert channels can increase the effective bandwidth available to senders and receivers for covert transmission of information. The easiest way to approximate the effect of aggregation on the maximum channel bandwidths is to (1) set the context-switching time to zero for both serial and parallel aggregation, and (2) to sum the bandwidths of the individual channels for parallel aggregation. However, the TCSEC requirements and guidelines neither require nor recommend that one consider aggregation in covert channel analysis. However, one needs to consider the notion of channel aggregation in the area of threat analysis, whenever such analysis is performed in the environment of system use (see Section 5.4 below).
Transient covert channels are those which transfer a fixed amount of data and then cease to exist. Normally, bandwidth and capacity calculations apply only to channels that are sustainable indefinitely. Thus, it would seem transient channels are an irrelevant threat. However, if a large volume of data can be leaked through a transient channel, one must consider channel bandwidth analysis and handling, for the threat of channel use becomes real.
Millen presents in [1989a] a method based on Shannon's information theory [Shannon and Weaver64]. In this method, one assumes the covert channels are noiseless, no processes other than the sender and receiver are present in the system during channel operation, and the sender-receiver synchronization takes a negligible amount of time. These assumptions are justified if the goal is the computation of the maximum attainable bandwidth. With these assumptions, one can model most covert channels that arise in practice as finite-state machines (graphs). Furthermore, these graphs are deterministic in that for any state transition corresponding to a given channel symbol (e.g., 0 or 1), only one next state appears in the graph. Figure 4-1 illustrates a state graph for a two- state channel. Most covert channels of interest in practice can be represented with two-state graphs. This is because, for most channels, the current state of the channel depends on the last signal sent and, thus, only two states are necessary to capture the scenario of information transfer.
Figure Missing
Figure 4-1. Two-State Graph for a Covert Channel
A scenario for the transfer of 0s and 1s using a two-state graph can be defined by associating each transition of the graph with the transfer of a 0 or a 1. Each transition covers a sender's action followed by a receiver's action.
For example, to send 0 in state 0:
To determine the bandwidth of a channel represented with a two-state graph, N(t), one must find the number of possible transmissions of duration t. The bandwidth (i.e., capacity) of a channel can be expressed in terms of Nh(t) as follows:
C = lim(log2Nh(t))/t.
To find Nh(t), let N0(t) be the total possible number of transmissions of duration exactly t beginning in one of the two states, and let N1(t) be the total possible number of transmissions of duration exactly t beginning in the other state. (In general, there will be an Nh(t) for the h-th state where h ranges over the state set.) The number of transmissions satisfies a system of difference equations that can be read off the two-state graph. Each equation is based on the fact that the set of transmissions beginning in a given state consists of a union of several disjoint sets, discriminated by the initial symbol of the transmissions. The number of transmissions with a given initial symbol is equal to the total number of (shorter) transmissions beginning in the next state after the transition for that symbol.
The following system of equations can be used for the file-lock channel:
N0(t)=N0(t - a)+N1(t - c)
N1(t)=N0(t - b)+N1(t - d)
In general, the hth equation has the form:
Nh(t' = &Sigma i(Ni(t - Thi),
where Thi is the time taken by a transition from state h to state i.
Note that N0(t) is nonzero only for those values of t that are expressible as a sum of multiples of a, b, c, and d. To determine the bandwidth of the channel, it is only necessary to find the asymptotic upper limit of N0(t) as t approaches infinity [Shannon and Weaver64]. This may be found in the form:
Nh(t)=Ah*xt
Substituting this solution, we obtain the system of equations:
Ah*xt = &Sigma (Ai*xt-Thi)
and C = lim(log2(Ah(xt))/t = log2x, when t -> infinity.
Note that there may be multiple solutions for x in the above equations. The largest solution provides the bandwidth (capacity).
We can express this system of equations in matrix form as (P-I)A = 0, where P is a matrix of negative powers of x. Since (P-I) is singular, its determinant Det(P-I) = 0. Figure 4-2 shows the system of equations, their determinant, and the solution.
Two of the Secure Xenix channels whose bandwidths were computed in reference [Tsai and Gligor88] for a PC/AT configuration are the inode table channel and the upgraded directory channel. In this example we illustrate Millen's method described above using measurements of Secure Xenix TCB primitives on an IBM PS/2 model 80 configuration. Tcs represents the context switch time, which is 3 milliseconds. The values of Tr (Ts) represent the duration of reading (setting) the covert channel variable, and the value of Tenv represents the duration of setting up the transfer environment (e.g., a state transition).
Figure Missing
Figure 4-2. Simultaneous Equations, Determinant, Capacity (Bandwidth)
In this example the state 0 of the inode table channel is represented by the inode table full state, and the state 1 by the node table nonfull state. Figure 4-3 shows the state transitions defined
Figure Missing
Figure 4-3. State Graphs for the lnode Table Channel
State 0:
When the inode table is full, two Tcs and one viewing primitive "open(f)" with a failure return are needed to transfer a 1 from a sending process to a receiving process. Thus, the following times are needed to transfer a 1 from state 0:
Tr(full->full) = open(f), Ts(full->full) = 0, Tenv(full->full) = 0.
When switching from the full state to the nonfull state, an alteration primitive "close(s)," a viewing primitive "open(s)," an environment set-up primitive "close(s)," and two Tcs are needed to send a 0. Thus, the following times are needed to transfer a 0 from state 0:
Tr(full->nonfull) = open(s), Ts(full->nonfull) = close(s), Tenv(full->nonfull) = close(s).
State 1:
When the transition is from the nonfull state to the nonfull state, a viewing primitive "open(s)," an environment set-up primitive "close(s)," and two Tcs are needed to transfer a 0. Thus, the following times are needed to transfer a 0 from state 1:
Tr(nonfull->nonfull) = open(s), Ts(nonfull->nonfull) = 0, Tenv(nonfull->nonfull) = close(s).
When switching from the nonfull state to the full state, an alteration primitive "open(s)," a viewing primitive "open(f)," and two Tcs are needed to transfer a 1. Thus, the following times are needed to transfer a 0 from state 1:
Tr(nonfull->full) = open(f), Ts(nonfull->full) = open(s), Tenv(nonfull->full) = 0.
The bandwidth (i.e., capacity) of this channel, denoted by C in Figure 4-3, is 47.63 bits/second.
In this example the state 0 of the upgraded directory channel is represented by the directory-full state, and the state 1 by the directory-nonfull state. The state transitions defined below and their durations are shown in Figure 4-4.
Figure Missing
Figure 4-4. State Graphs for the Upgraded Directory Channel
State 0:
When an upgraded directory is nonempty, two Tcs and one viewing primitive "rmdir(f)" with a failure return are needed to transfer a 1 from a sending process to a receiving process.
Tr(nonempty->nonempty) = rmdir(f), Ts(nonempty->nonempty) = 0, Tenv(nonempty->nonempty) = 0.
When switching from the nonempty state to the empty state, an alteration primitive "unlink(s)," a viewing primitive "rmdir(s)," an environment set-up primitive "mkdir(s)," and two Tcs are needed to send a 0. Thus, the following times are needed to transfer a 0 from state 0:
Tr(nonempty->empty) = rmdir(s), Ts(nonempty->empty) = unlink(s), Tenv(nonempty->empty) = mkdir(s).
State 1:
When the transition is from the empty state to the empty state, a viewing primitive "rmdir(s)," an environment set-up primitive "mkdir(s)," and two Tcs are needed to transfer a 0. Thus, the following times are needed to transfer a 0 from state 1:
Tr(empty->empty) = rmdir(s), Ts(empty->empty) = 0, Tenv(empty->empty) = mkdir(s).
When switching from the empty state to the nonempty state, an alteration primitive "creat(s)", a viewing primitive "rmdir(f)", and two Tcs are needed to transfer a 1. Thus, the following times are needed to transfer a 1 from state 1:
Tr(empty->nonempty) = open(f), Ts(empty->nonempty) = open(s), Tenv(empty->nonempty) = 0.
The bandwidth of this channel is denoted by C in Figure 4-4 and is 0.512 bits/second.
A simple formula for computing the maximum attainable bandwidth of a noise-less covert channel in absence of any spurious processes that would delay senders and receivers was presented in [Tsai and Gligor88]. The formula is:
B(0) = b*(Tr + Ts + 2Tcs)**(-1),
In this formula, b represents the encoding factor (which we assume to be 1 in most practical cases), and
Formula Missing
where n is the number of total possible transitions. Ts(i) and Tr(i) are the times necessary to set and read a 0 or a 1 after having transmitted a 0 or a 1. Thus, n = 4. Tenv(i) is the time to set up the environment to read a 0 or a 1. Note that in these formulas it is assumed that all environment setup for both variable reading and setting is done by the receiving processes.
In deriving this formula it is assumed that the setting of 0's and 1's take the same amount of time, and that all transmissions contain an equal distribution of 0's and 1's.
The maximum bandwidths of the two channels of Example 11 can be recalculated by using the above formula, as follows:
The Inode Table Channel
Ts = [Ts(full->full) + Ts(full->nonfull) + Ts(nonfull->nonfull) + Ts(nonfull->full)]/4
= [0 + close(s) + 0 + open(s)]/4
=(open+close)/4 = (12 + .2)/4 = 3.05 (ms)
Tr = [T,(full->full)+ Tenv(full->full) + Tr(full->nonfull) + Tenv(full->nonfull) + Tr(nonfull->nonfull) + Tenv(nonfull->nonfull) + Tr(nonfull->full) + Tenv(nonfull->full)]/4
= [open(f) + 0 + open(s) + close(s) + open(s) + close(s) + open(f) + 0]/4
=open + close/2 = 12.1 (ms)
Therefore,
B(0) = 1000/(l2.1 + 3.05 + 6) 47.28 bits/sec
Ts = [Ts(nonempty->nonempty) + Ts(nonempty->empty) + Ts(empty->empty) + Ts(emptyÆnonempty)]/4
= [0 + unlink(s) + 0 + creat(s)]/4
=(creat + unlink)/4 = (30 + 22)/4 = 13(ms)
Tr = [Tr(nonempty->nonempty) + Tenv(nonempty->nonempty) + Tr(nonempty->empty) + Tenv(nonempty->empty) + Tr(empty->empty) + Tenv(empty->empty) + Tr(empty->non-empty) + Tenv(empty->nonempty)]/4
= [rmdir(f) + 0 + rmdir(s) + mkdir(s) + rmdir(s) + mkdir(s) + rmdir(f) + 0]/4
= [rmdir(s) + rmdir(f)l/2 + mkdir/2
=(180+3020)/2+260/2=1730 (ms)
Therefore,
B(0) = 1000/(1730 + 13 +6)=0.572bits/sec
Comparing the results of Examples 11 and 12 one might be tempted to conclude that the two bandwidth computation methods yield similar results for all covert channels. This conclusion, however, is not always the case. Millen's method yields higher bandwidths whenever the times to set up transmission environments and/or those to transmit 0s differ significantly from those to transmit 1s. This may be the case after delays are placed in some but not all TCB primitives of a channel (e.g., in the error return path of a primitive needed to use the channel; this ensures that undue performance penalty is not incurred.). Subsequent recomputation of the (delayed) channel bandwidth by the two methods would yield significantly different results. Experience with using the two methods for Secure Xenix shows that in cases where the times to transmit a 0 and a 1 are close, the two methods yield results that differ by at most 20%.
Millen's method is superior to that presented in [Tsai and Gligor88] not only because it always helps compute the maximum attainable bandwidth but also because during its use one is required to define a realistic scenario of covert channel use. This process helps remove any misunderstandings that might arise when different parties use different assumptions to define the environment set-up times for a channel.
The TCSEC requirements for bandwidth determination of covert channels state, "The system developer ... shall make a determination (either by actual measurements or by engineering estimation) of the maximum bandwidths of each identified channel."
As explained in Section 4.1, the measurements or estimation of the maximum bandwidth must assume that the covert channels are noiseless, that no processes-other than the sender and receiver-are present in the system when measurements are performed, and that the synchronization time between senders and receivers is negligible. If the channel's bandwidth is estimated using informal methods, measurements of the channel's fastest primitives must be done to determine the values of T5(i), Tr(i), Tenv(j) as defined in Section 4.2.2, and the smallest measured value of Tcs must be chosen. For both formal and informal bandwidth determination methods, the selection of the TCB primitives measured should be based on realistic scenarios of channel use and should take into account any parameter of TCB state dependency that is relevant for a channel. The system configuration and architecture parameters should be specified for each set of measurements. All measurements necessary for bandwidth determination should be repeatable. Channel aggregation should be considered even though it is not supported by any TCSEC requirements or recommendations.
The TCSEC requirements for level A1 state, "Formal methods shall be used in the [covert channel] analysis."
In the context of bandwidth measurement or estimation, this requirement suggests that Millen's method (1989a)-defined and illustrated in Section 4.2.1 -should be used. Any other relevant information-theory-based method for covert channel bandwidth estimation could be acceptable on a case-by-case basis.
In this chapter we present three general methods for the handling of known covert channels that have been proposed and used to date. We also present a set of handling policies based on the analysis of the covert channel threats and risks that is consistent with the objective of the handling guideline of [NCSC TCSEC].
The first method is the elimination of covert channels. Elimination requires changing the design and/or implementation of a system to remove covert channels from the system. These changes include:
To illustrate elimination of covert channels by the elimination of resource sharing, let us reconsider Example 1. The dynamic allocation/deallocation of objects triggers dynamic allocation of memory segments, which provides a resource-exhaustion channel. If the memory is statically partitioned on a per-process or per-security-level basis, the resource-exhaustion channel is eliminated. However, as pointed out in Example 1, this partitioning is not always practical. For example, if the memory (or any other TCB resource, such as internal tables) is partitioned, memory utilization may decrease because some partitions may not be as frequently used as others. This infrequent use may cause a significant degradation in performance. We can find examples of resource partitioning that do not impose undue performance degradation. For instance, the name space of the UNIX, System V interprocess communication objects can be partitioned on a per- security-level basis without significant performance degradation.
Resource partitioning on a per-user, or a per-process, basis is not always possible (e.g., shared hardware resources, such as busses, cannot be partitioned on a per-user or per-process basis). However, the use of these resources can, in principle, be partitioned in time on a per-security-level basis. That is, processes running at the same time can share hardware resources only if the processes run at the same level. For example, in the case of the multiprocessor configurations presented in Example 4, and illustrated in Figure 2-7, a dual-mode process dispatcher can be implemented. In normal mode, the use of the CPUs is not partitioned. However, to eliminate the timing channels discussed in Example 4, the processes waiting for service in the "ready" queue(s) can be loaded in available CPUs during the same quantum only if they have the same security level. In this mode, called the time-partitioned mode, the timing channels caused by bus or memory locking by each memory reference become harmless. Trusted processes should be exempt from time-partitioned dispatching whenever it can be shown they do not exploit Covert channels. (Furthermore, threat analysis performed in the environment of system use may exempt other non- TCB applications from the time-partitioned mode of operation. This exemption is an accreditation- policy matter and, thus, beyond the scope of this guide.)
The performance degradation that may be caused from the time-partitioned dispatching depends on the mix of processes ready to run at any instance. In some environments, where families of processes run concurrently (i.e., are coscheduled, we discuss in Section 2.2.3), the performance degradation will be minimized since all processes of a family run at the same security level. Performance degradation will be significant whenever all processes of the "ready" queue(s) run at different security levels because partitioned-mode dispatching will idle all but one CPU. The overall performance degradation can be mitigated whenever partitioned mode dispatching can be turned on/off selectively by security administrators. In Section Lampson73] Alternatively, this channel can be eliminated by producing accounting information on a per-level basis. Neither alternative seems particularly troublesome, in practice.
The second method of handling known covert channels is based on bandwidth-limitation policies. Such policies require the reduction of the maximum, or alternatively the average, bandwidth of any channel to a predefined acceptable limit. One can limit bandwidths by:
The process identifier channel is an event-count channel that in most systems can have a bandwidth of 10 to 500 bits per second. This channel appears because most TCBs create a new process identifier by incrementing a process-identifier variable whenever a new process is created. Thus, a receiver process could detect whether the sender process transmitted a 0 or a 1 bit by determining whether the identifiers of two processes it creates are consecutive numbers. One can reduce the bandwidth of this channel by changing the process-identifier allocation algorithm of the TCB. That is, the TCB could allocate unused identifiers in the identifier space (pseudo) randomly in a nonmonotonic sequence. Depending upon the randomization characteristics of the allocation algorithm, the bandwidth of the process-identifier channel can be reduced to negligible values. Similar considerations apply to the other allocation algorithms of object identifiers. Note that using random allocation of identifiers introduces negligible overhead and performance degradation in a TCB.
An additional example of noise introduction in covert channels is the notion of "fuzzy time" introduced in [Hu91]. Security kernels can constrain user processes to use only virtual time (i.e., time related only to a user's process activity but not to real time). [Lipner75] To ensure little correlation between real and virtual time by a user process (i.e., a receiver), the relationship between real and virtual time is randomized. This is the underlying principle of the notion of "fuzzy time." The randomization appears to degrade system performance very little (i.e., 5-6% on a VAX system [Hu91]). Thus, "fuzzy time" seems practical even in systems where performance degradation is a significant concern.
An alternative method of reducing channel bandwidths includes the deliberate introduction of spurious processes. That is, user-level processes are introduced in the system to perform random alteration of channel variables. As illustrated in Figure 2-5, processes Up, . . . ,Uq can introduce noise by altering a channel variable. Furthermore, these processes can introduce delays in channels by interposing themselves between the senders and receivers. Analysis presented in [Tsai and Gligor88] shows that the introduction of spurious processes can reduce up to about 75% of the bandwidth of typical channels. However, the introduction of spurious processes for bandwidth- degradation purposes may not be cost-free. Spurious processes tend to degrade system performance-not only channel bandwidth.
The deliberate introduction of delays in TCB primitives of real channels is typically used only for limiting the bandwidth of resource-exhaustion channels. The reason is that one can place delays in these channels in a way that does not degrade system performance until these channels are used. Resource-exhaustion channels make use of resource-exhaustion exception (error) returns to transmit zeros or ones. By placing delays within the return path of an exception, the channel bandwidth is reduced proportionally with the frequency of either the zeros or the ones in the code used by the channel users. In normal mode of TCB operation, however, performance is not degraded because resource-exhaustion exceptions are generally rare (unless channels are used).
It is generally advisable to introduce settable delays within TCB primitives, for two reasons. First, settable delays give system management the opportunity to determine the extent of performance degradation incurred by setting delays selectively on a per-channel basis. Second, whenever the same operating system is used on different hardware platforms, the delay values need to be changed to account for increased or decreased bandwidth for the same channel.
The placement of delays in TCB primitives can be a more complex task than it may first appear. Tradeoffs appear in the placement of delays in the TCB. On one hand, the placement of a delay in functions closer to the TCB interface (i.e., in high-level functions) offers the potential of minimizing the impact of the delay on the entire TCB. For each covert channel, each TCB primitive can be dealt with separately. Thus, one can choose a minimum delay value for each particular TCB primitive and covert channel variable. On the other hand, disadvantages of this delay placement strategy are:
For most covert channels, one must place delays in more than one location of the TCB code. The control-flow paths presented in this example refer to the resource-exhaustion channel provided by the variable "inode->i_flag" of UNIX. This example shows that multiple control paths, both through different TCB primitives of a channel and through the same TCB primitive, must be covered by delays.
Some Control-Flow Paths for the inode->i_flag Variable
creat:
(1) creat->copen->namei->access
(2) creat->copen->access
open:
(1) open->copen->namei->access
(2) open->copen->access
unlink:
(1) unlink
(2) unlink->namei->access
utime:
(1) utime->namei->access
(2) utime->access
chsize:
(1) chsize
This example shows that delay addition to a channel should be placed in low-level TCB functions shared by multiple control paths for the same channel. The low-level TCB functions that are common to all control paths of the inode->i_flag channel include those of "access," "unlink," and "chsize."
The setting of a specific error message within a TCB primitive may correspond to the viewing of multiple covert channels. Thus, the highest-level functions of a TCB primitive cannot determine which channel is being used. Therefore, achieving minimum delay in high-level TCB functions is not always possible. The highest-level functions of TCB primitives where different channels can be distinguished should be found and used for placement of minimum delays. The primitive "creat" of UNIX, in which the ENFILE error is set for both the inode_space and file_table channels, illustrates this case.
File Table Channel
fork
The third method of handling known covert channels is that of deterrence of Co- vert channel use. This method allows all users to exploit known channels but provides a mechanism discouraging channel use. The main deterrence method is channel auditing. This method assumes audit mechanisms can unambiguously detect the use of a channel. Thus, users can be assured of detection of any unauthorized use of covert channels. Note, however, that the TCSEC requires only the ability to audit covert channels be provided-not that covert channels be actually audited. This detail limits somewhat the effectiveness of audit as a real deterrent.
Covert channel auditing requires that sufficient data be recorded in audit trails to enable the identification of (1) individual covert channel use, or use of certain channel types; and (2) identification of the senders and receivers of individual channels or of channel types (i.e., the identification of the covert channel users). Furthermore, discovery of covert channel use must be certain (i.e., covert channel auditing must not be circumventable), and false detection of covert channel use must be avoided. Circumvention of covert channel auditing is undesirable because it allows leakage of information to remain undetected. False detection of covert channel use is also undesirable because it may make it impossible to distinguish between innocuous user activity and covert channel use.
Estimation of actual covert channel bandwidth is possible and desirable once covert channel use has been determined by audit-trail analysis. Note that, in genera, it is impossible to discover the actual information being leaked through covert channels from audit trails because a user can encrypt it before leakage. Also, one cannot distinguish between real information and noise leakage merely by inspecting audit trails. Constant streams of either zeros or ones are the only recorded patterns one can unambiguously classify as noise.
Most of the problems identified in covert channel auditing are fundamental and are shared by most operating systems; these problems include (1) inability of distinguishing use of covert channels from innocuous use of TCB primitives, and (2) ambiguity in distinguishing senders from receivers among covert channel users. These problems appear because single TCB primitives may both alter and view a variable or attribute, depending on the argument values of that primitive and on the system state, and because different TCB primitives may be shared by different covert channels. Such primitives allow users to disguise covert channel use, thereby circumventing audit, and cause false detection of covert channels [Shieh and Gligor9]. Figures 3-2 and 3-4 show examples of such primitives.
Key design concerns of covert channel auditing are those of determining what events should be recorded by auditing mechanisms and what data should be maintained by auditing tools to ensure that all covert channel use can be discovered. The identification of covert channels can be summarized as sets of < variable, PAh,PVi > triples (where PAh/PVi represents a TCB primitive altering/viewing the variable, as shown in Figures 3-2 and 3-4), suggesting that recording all events including pairs of < PAh, variable > and < PVi, variable > is necessary and sufficient for covert channel auditing. However, recording such events is fraught with both practical and fundamental difficulties because audit-record formats and mechanisms currently used in practice include only process identifiers, object identifiers, process and object security levels, type of event (e.g., primitive identifier), and event outcome (i.e., success or error value); viz., Refs. [NCSC TCSEC, NCSC Audit]. Fields for recording covert channel variables are not included in existent audit- record formats. [Shieh and Gligor9o] provide examples of such fields and their setting.
In resource-exhaustion channels one can sometimes identify
Fundamental difficulties with recording channel variables appear because many TCB
primitives are shared by several covert channels. Thus, a PAh- or a PVi-type primitive may refer
to variables of multiple channels. The actual use of a single variable cannot be discerned even when
all potential variables are known and even when the error outcomes of a PV; primitive can be
unambiguously associated with single channel variables. For example, a user can infer a no-error
outcome of a shared PVi primitive on a given variable from an error outcome of the same PVi
primitive on another variable. This process enables users to disguise the use of a channel as
transmission of noise (e.g., constant strings of 0s or 1s) on multiple channels (an example of
reference [Shieh and Gligor90]). In such cases, auditors have to maintain additional information to
enable the detection of all potential use of covert channels.
Examples of the storage channel auditing problems mentioned above have been illustrated in
the context of the Secure Xenix system in reference [Shieh and Gligor90]. Solutions to these
problems are also presented in that reference. We must note, however, that not all use of covert
channels can be audited. Example 4 of section 2.2 illustrates a few instances of covert timing
channels usage where auditing is impractical.
TCSEC requirements for covert channel handling are included in the audit and documentation
requirements. Section 8 of the TCSEC, "A Guideline on Covert Channels," makes additional
recommendations.
The audit requirements of the TCSEC state, "The TCB shall be able to audit the identified
events that may be used in the exploitation of covert storage channels."
[Documentation] shall also present the results of the covert channel analysis and the
trade-offs involved in restricting the channels. All auditable events that may be used
in the exploitation of known covert storage channels shall be identified. The
bandwidths of known covert channels, the use of which is not detectable by the
auditing mechanisms, shall be provided.
The TCSEC requirements for handling covert channels and the covert channel guidelines
presented in Section 8 of the TCSEC suggest the following handling policy:
Although the intent of the TCSEC handling requirements and guideline is sound, the
justification of the particular values of bandwidth limits b (0.1 bits/second) and B (1 bit/second)
may be less than satisfactory for the following reasons:
Consider an application environment in which classified satellite images are processed (e.g.,
satellite images of various agricultural crops in certain countries). Each image frame consists of
512x512 picture elements (pixels), each pixel having 8 bits, and each application includes up to
10,000 frames. A multilevel secure system is used which includes a covert channel of 10,000 bits/
second. This means an image frame can be declassified by using this covert channel in
approximatively 200 seconds. Thus, up to 18 frames can be declassified in an unauthorized manner
per hour. The need to operate this channel for more than one hour to declassify less than 0.2% of
the data makes this threat negligible. The likelihood of detecting the use of this channel by (off-
line) audit is very high due to its long period of operation. Thus, in this environment b can be set
to 10,000 bits/second or even higher. Of course, information concerning the source of the satellite
images may have a higher classification. The vulnerability of this information to covert channels
may require its separate processing by trusted software rather than by untrusted application code.
In contrast, consider an application environment where 64-bit encryption keys are generated
whose lifetimes are comparable with that of a login session (i.e., 8 hours). Even if these keys are
encrypted when stored on nonvolatile storage, their actual use by application software would be in
cleartext form. If the secure system used in this application contains a 0.1 bit/second channel, each
session key can be declassified in less than 11 minutes, rendering the key vulnerable for most of
its lifetime. The likelihood of being able to detect the use of this channel through off-line audit may
not be very high because of the relatively short period of channel use. On-line audit of this channel
may be even less likely. Thus, in this application environment B could not be set to 0.1 bit/second.
Instead, a B of 0.002 bit/second would seem more appropriate because, at that rate, it would take
at least 8 hours to declassify a key.
The classification range of the information processed in a trusted system and, therefore, the
trusted system class (i.e., B2-A1) must also be considered in threat analysis. Covert channels of
high bandwidths (e.g., 1,000-10,000 bits per second) may be acceptable in a B2 system in which
only Top Secret and Secret information is processed, and leakage below the Secret level is
impossible. In contrast, the same leakage rate may be unacceptable in A1 systems that process
multilevel information, since the possibility of unauthorized declassification of Top Secret
information might be a real threat.
In threat analyses, one must also consider the characteristics of each covert channel. For
example, the CPU scheduling channels of Example 3 may have a maximum bandwidth of 5-300
bits/second on systems comparable to today's fast workstations (depending on the operating
system and scheduling parameters [Huskamp78]). However, compared with the upgraded
directory channels, the CPU scheduling channels are much more difficult to use in any real system
due to lack of control over scheduling parameters and due to noise introduced by background
processes. Thus, these channels (and also those illustrated in Example 4 which use shared hardware
resources) are significantly less likely to be used in practice than the noiseless upgraded-directory
channels of Example 2. On the other hand, other noisy channels such as the various identifier
channels may be more likely to be used than the upgraded directory channels because the
likelihood of auditing correctly a noiseless channel is higher than that of auditing correctly a noisy
channel. Thus, the high likelihood of detecting the use of the upgraded directory channel may deter
its use.
This example indicates the need for establishing a threat-analysis policy on a per environment
and system basis. It also suggests this analysis cannot be carried out at system evaluation time
without postulating the characteristics of the application environment. Finally, this example
suggests few of the important parameters that should be considered for such an analysis.
The TCSEC requirements of test documentation at class B2 state, ". . . [Test documentation]
shall include results of testing the effectiveness of the methods used to reduce covert channel
bandwidths."
Covert channel testing demonstrates that covert channel handling methods chosen by system
designers work as intended. These methods include covert channel elimination, bandwidth
limitation, and (ability to) audit. Testing is also useful to confirm that potential covert channels
discovered in the system are in fact real channels. Furthermore, testing is useful when the handling
method for covert channels uses variable bandwidth-reduction parameters (e.g., delays) that are
settable by system administrators (e.g., by auditors).
Bandwidth estimation methods necessary for the handling of covert channels may be based on
engineering estimation rather than on actual measurements. Bandwidth estimations provide upper
bounds for covert channels before employing any handling methods. In contrast, covert channel
testing always requires doing actual measurements to determine the covert channel bandwidths
after implementing the chosen handling method in a system.
Test plan documentation, including test conditions, test environment set-up, test data,
expected test outcome, and actual test result documentation are discussed in the security testing
guideline [NCSC Testing] in detail. Therefore, we do not repeat the discussion here. The security
testing guideline also gives an example of the test plans for a real channel (i.e., for the upgraded-
directory channel of Example 2).
We present in this chapter the TCSEC requirements relevant to covert channel analysis and
suggest ways to satisfy them. For each class containing them, we show the requirements of CCA
(which include channel identification, bandwidth measurement or estimation, audit, and design
documentation). We also summarize the recommendations made in the TCSEC guidelines on
covert channels. Our recommendations, though derived from TCSEC objectives, are not
requirements.
Channel Identification
The TCSEC requirement for CCA states, "The system developer shall conduct a thorough
search for covert storage channels . . ."
Developers shall identify the sources of information used to satisfy this requirement. These
sources shall include system reference manuals and the DTLS. They should include source code
and processor specifications whenever the identification method includes source code and
hardware analysis. Developers should show the identification method they use to be sound and
reliable (e.g., repeatable). This implies, among other things, that independent evaluators can use
the method on the same sources of covert channel information and get the same results. Otherwise,
the identification evidence will lack credibility.
Bandwidth Measurement or Engineering Estimation
The TCSEC requirement for this area states, "The system developer shall . . . make a
determination (either by actual measurement or by engineering estimation) of the maximum
bandwidth of each identified channel."
In measuring or estimating covert channel bandwidth, developers should consider the
following factors (as discussed in Section 4.1):
The TCSEC Audit requirements state, ". . . The TCB shall be able to audit the identified events
that may be used in the exploitation of covert storage channels."
To satisfy this requirement, audit mechanisms should include the following features whenever
possible (viz., discussion of Section 5.3):
. . . This documentation shall also present the results of the covert channel analysis
and the tradeoffs involved in restricting the channels. All auditable events that may
be used in the exploitation of known covert storage channels shall be identified. The
bandwidths of known covert storage channels, the use of which is not detectable by
the auditing mechanism, shall be provided. . . .
The documentation of each identified storage channel should consist of the variable the
channel views/alters and the TCB primitives that alter or view the variable. Developers should
distinguish potential covert channels from real ones.
Documentation of Bandwidth Estimation
Developers must document measurements of each covert channel primitive and should
include the bandwidth computation for each channel. They should document the measurement
environment as specified in Section 7.1.1.
Documentation of Covert Channel Auditing
Documentation shall include a definition of each event used in the exploitation of a covert
channel. This documentation should cite the definition of the TCB primitives and TCB paths
leading to a covert channel variable. Developers should also identify and justify the covert storage
channels that cannot be audited.
Channel Restriction and Handling Policies
The documentation shall include a description of (1) how covert channels are eliminated, and
(2) how covert channel bandwidth is limited to a value deemed acceptable. Sections 5.1 and 5.2
provide a discussion of channel restriction methods.
Covert channel-handling policies should be consistent with the intent of the TCSEC
guidelines. Covert channel bandwidth limits (b, B)-as defined in Sections 5.4 and 5.5-are
considered outside the purview of the TCSEC. System accreditors should specify these limits for
the specific threat environment the system will be used in.
Part of the TCSEC requirements for test documentation states, ". . . [Test documentation]
shall include results of testing the effectiveness of the methods used to reduce covert channel
bandwidths."
See the security testing guideline [NCSC Testing], which discusses these requirements.
Class B3 incorporates all requirements of class B2. In addition, the following requirements
apply.
Channel Identification
The only additional B3-class requirement is the identification of timing channels. Developers
must define timing channel scenarios and identify all system components providing independent
sources of timing (e.g., CPUs and I/O processors). Developers may use the same sources of
information and methods for identifying timing channels as those used for identifying storage
channels.
Bandwidth Measurement or Engineering Estimation
There are no additional requirements.
There are no additional requirements.
Documentation of Identified Channels
The only additional requirement for this class is the documentation of all timing channels.
Developers should document these channels by specifying the variable of the TCB state that may
be changed by direct or indirect actions of user processes. These channels include CPU-scheduling
channels, I/O-processor-scheduling channels, and page-replacement channels.
There are no additional requirements.
Class A1 contains all the class B3 requirements. The only additional requirements of class A1
appear in CCA.
Covert Channel Analysis
Part of the TCSEC requirement for this area states, ". . . Formal methods shall be used in
analysis."
Channel Identification
Developers can apply formal methods on both formal specifications and source code of the
TCB. These methods include syntactic information-flow analysis (with or without the use of
semantic analysis) and noninterference analysis. Developers shall apply the chosen identification
method to the FTLS. Unless the identification of covert channels is made a part of the
specification-to-code correspondence (in which case source-code analysis is included), developers
should complement the FTLS analysis with formal or informal source-code analysis. Otherwise,
covert channels may remain undetected.
Bandwidth Measurement or Engineering Estimation
The requirement to use formal methods suggests that developers should use Millen's method
(1989a)-defined and illustrated in Section 4.2.1. Any other information-theory-based method for
covert channel bandwidth estimation may be acceptable on a case-by-case basis.
ACCESS
Ability and means to communicate with (i.e., input to or receive output from) or
otherwise make use of any information, resource, or component in an AIS.
NOTE: An individual does not have "access" if the proper authority or a physical,
technical, or procedural measure prevents them from obtaining knowledge or having
an opportunity to alter information, material, resources, or components.
ACCESS TYPE
Privilege to perform an action on a program or file. NOTE: Read, write, execute,
append, modify, delete, and create are examples of access types.
ACCREDITATION
Formal declaration by a designated approving authority that an AIS is approved to
operate in a particular security mode using a prescribed set of safeguards.
ADMINISTRATIVE USER
A user assigned to supervise all or a portion of an AIS.
AUDIT
Independent review and examination of records and activities to assess the adequacy
of system controls, to ensure compliance with established policies and operational
procedures, and to recommend necessary changes in controls, policies, or
procedures.
AUDIT MECHANISM
The processes used to collect, review, and/or examine system activities.
AUDITOR
An authorized individual, or role, with administrative duties, which include selecting
the events to be audited on the system, setting up the audit parameters which enable
the recording of those events, and analyzing the trail of audit events.
AUDIT TRAIL
Chronological record of system activities to enable the reconstruction and
examination of the sequence of events and/or changes in an event.
BANDWlDTH
A characteristic of a communication channel that is the amount of information that
can be passed through it in a given amount of time, usually expressed in bits per
second.
BELL-LA PADULA SECURITY MODEL
Formal-state transition model of a computer security policy that describes a formal
set of access controls based on information sensitivity and subject authorizations.
CATEGORY
Restrictive label that has been applied to both classified and unclassified data,
thereby increasing the requirement for protection of, and restricting the access to, the
data. NOTE: Examples include sensitive compartmented information, proprietary
information, and North Atlantic Treaty Organization information. Individuals are
granted access to special category information only after being granted formal access
authorization.
CERTIFICATION
Comprehensive evaluation of the technical and nontechnical security features of an
AlS and other safeguards, made in support of the accreditation process, to establish
the extent to which a particular design and implementation meets a set of specified
security requirements.
CHANNEL
An information transfer path within a system. May also refer to the mechanism by
which the path is effected.
COVERT CHANNEL
Unintended and/or unauthorized communications path that can be used to transfer
information in a manner that violates an AIS security policy. See also: Covert Storage
Channel, Covert Timing Channel.
COVERT STORAGE CHANNEL
Covert channel that involves the direct or indirect writing to a storage location by one
process and the direct or indirect reading of the storage location by another process.
NOTE: Covert storage channels typically involve a finite resource (e.g., sectors on a
disk) that is shared by two subjects at different security levels.
COVERT TIMING CHANNEL
Covert channel in which one process signals information to another process by
modulating its own use of system resources (e.g., central processing unit time) in
such a way that this manipulation affects the real response time observed by the
second process.
DATA
Information with a specific physical representation.
DATA INTEGRITY
Condition that exists when data is unchanged from its source and has not been
accidentally or maliciously modified, altered, or destroyed.
DESCRIPTIVE TOP-LEVEL SPECIFICATION (DTLS)
Top-level specification that is written in a natural language (e.g., English), an
informal program design notation, or a combination of the two. NOTE: Descriptive
top-level specification, required for a class B2 and B3 AIS, completely and
accurately describes a trusted computing base. See formal top-level specification.
DISCRETIONARY ACCESS CONTROL
Means of restricting access to objects based on the identity and need-to-know of users
and/or groups to which the object belongs. NOTE: Controls are discretionary in the
sense that a subject with a certain access permission is capable of passing that
permission (directly or indirectly) to any other subject. See mandatory access control.
DOMAIN
Unique context (e.g., access control parameters) in which a program is operating; in
effect, the set of objects that a subject has the ability to access.
EXPLOITABLE CHANNEL
Covert channel that is intended to violate the security policy governing an AIS and is
usable or detectable by subjects external to the trusted computing base. See covert
channel.
FORMAL SECURITY POLICY MODEL
Mathematically precise statement of a security policy. NOTE: Such a model must
define a secure state, an initial state, and how the model represents changes in state.
The model must be shown to be secure by proving that the initial state is secure and
that all possible subsequent states remain secure.
FORMAL TOP-LEVEL SPECIFICATION (FTLS)
Top-level specification that is written in a formal mathematical language to allow
theorems, showing the correspondence of the system specification to its formal
requirements, to be hypothesized and formally proven. NOTE: Formal top-level
specification, required for a class A1 AIS, completely and accurately describes the
trusted computing base. See descriptive top-level specification.
FUNCTIONAL TESTING
Segment of security testing in which advertised security mechanisms of an AIS are
tested under operational conditions.
MANDATORY ACCESS CONTROL
Means of restricting access to objects based on the sensitivity (as represented by a
label) of the information contained in the objects and the formal authorization (i.e.,
clearance) of subjects to access information of such sensitivity. See discretionary
access control.
MULTILEVEL DEVICE
Device that is trusted to properly maintain and separate data of different security
levels.
OBJECT
Passive entity that contains or receives information. NOTE: Access to an object
implies access to the information it contains. Examples of objects are: records,
blocks, pages, segments, files, directories, directory trees and programs, as well as
bits, bytes, words, fields, processors, video displays, keyboards, clocks, printers, and
network nodes.
OVERT CHANNEL
Communications path within a computer system or network that is designed for the
authorized transfer of data. See covert channel.
PROCESS
A program in execution. See domain and subject.
READ
Fundamental operation in an AIS that results only in the flow of information from an
object to a subject. See access type.
READ ACCESS
Permission to read information in an AIS.
SECURITY ADMINISTRATOR
An administrative role (or user) responsible for the security of an AIS and having the
authority to enforce the security safeguards on all others who have access to the AIS
(with the possible exception of the auditor.) Also called system administrator.
SECURITY LEVEL
The combination of a hierarchical classification and a set of nonhierarchical
categories that represents the sensitivity of information.
SECURITY POLICY
The set of laws, rules, and practices that regulate how an organization manages,
protects, and distributes sensitive information.
SECURITY POLICY MODEL
An informal or formal presentation of a security policy enforced by the AIS. It must
identify the set of rules and practices that regulate how an AIS manages, protects, and
distributes sensitive information. See Bell-La Padula security model and formal
security policy model.
SECURITY TESTING
Process to determine that an AIS protects data and maintains functionality as
intended. NOTE: Security testing may reveal vulnerabilities beyond the scope of the
AS design.
SUBJECT
Active entity in an AIS, generally in the form of a person, process, or device that
causes information to flow among objects or changes the system state. NOTE:
Technically, a process/domain pair.
SUBJECT SECURITY LEVEL
Sensitivity label(s) of the objects to which the subject has both read and write access.
NOTE: Security level of a subject must always be dominated by the clearance level
of the user with which the subject is associated.
TCB PRIMITIVE
An operation implemented by the TCB whose interface specifications (e.g., names,
parameters, effects, exceptions, access control checks, errors, and calling
conventions) are provided by system reference manuals or DTLS/FTLS as required.
TOP-LEVEL SPECIFICATION (TLS)
A nonprocedural description of system behavior at the most abstract level; typically,
a functional specification that omits all implementation details.
TROJAN HORSE
Computer program containing an apparent or actual useful function that contains
additional (hidden) functions that allows unauthorized collection, falsification or
destruction of data.
TRUSTED COMPUTING BASE (TCB)
Totality of protection mechanisms within a computer system, including hardware,
firmer, and software, the combination of which is responsible for enforcing a security
policy. NOTE: The ability of a trusted computing base to enforce correctly a unified
security policy depends on the correctness of the mechanisms within the trusted
computing base, the protection of those mechanisms to ensure their correctness, and
the correct input of parameters related to the security policy.
USER
Person or process accessing an AIS by direct connections (e.g., via terminals) or
indirect connections. NOTE: "Indirect connection" relates to persons who prepare
input data or receive output that is not reviewed for content or classification by a
responsible individual.
VERIFICATION
The process of comparing two levels of an AIS specification for proper
correspondence (e.g., security policy model with top-level specification, top-level
specification with source code, or source code with object code). NOTE: This
process may or may not be automated.
WRITE
Fundamental operation in an AIS that results only in the flow of information from a
subject to an object. See access type.
WRITE ACCESS
Permission to write to an object in an AIS.
This appendix provides additional examples of storage and timing channels. For simplicity, in
all covert channel examples below we assume the security level of the sending process S dominates
that of the receiving process R. However, one can find similar examples where the security levels
of S and R are incomparable using the dominance relation defined in the system.
The following examples of covert storage channels are identified in the literature; for example,
see [Lopere85] or [Tsai and Gligor88]. These examples are necessarily genric in nature and are
meant to be a starting point for identification of covert storage channels in specific systems.
The table-space exhaustion channel is similar to the memory-resource exhaustion channel. The
channel is present on systems in which the TCB allocates a fixed amount of space for its table
rather than employing some type of dynamic allocation scheme. For the purpose of creating an
example here, suppose that a TCB has allocated a fixed table to keep track of processes created in
the system. A sending process S whose security level dominates that of a receiving process R
would transmit information in the following manner:
This covert storage channel is exploitable in a segmented memory architecture system in which
the file system cannot be unmounted if some segments are still in the address space of a process.
If a process attempts to unmount a file system and is given an answer busy or not busy, a higher
security level process owning segments contained in the file system can transfer information to a
lower security level process attempting the unmount. The scenario is as follows:
When physical printers or other I/O devices are shared resources in a system, a sending process
S at a high security level could potentially transfer information to a receiving process R at a lower
security level by creating contention for the device(s). As always, the sender and receiver must
have some way to synchronize. To send a 1, the sender process S simply checks to see if the printer
is attached, and attaches it if it is not. To send a 0, the sender process S checks to see if the printer
is attached, and detaches it if it is. The receiver process R attempts to attach the printer, receiving
a 0 if successful, and a 1 otherwise. The receiver process R then detaches the printer if the attach
call was successful.
One way to think of the difference between covert timing channels and covert storage channels
is that covert timing channels are essentially memoryless, whereas covert storage channels are not.
With a timing channel, the information transmitted from the sender must be sensed by the receiver
immediately, or it will be lost. However, an error code indicating a full disk which is exploited to
create a storage channel may stay constant for an indefinite amount of time, so a receiving process
is not as constrained by time.
As is the case with covert storage channels, covert timing channels will inevitably be present on
any system in which sharing of system resources takes place. We present several examples of
covert timing channels in the following sections.
The tasks of identification and handling covert timing channels (i.e., bandwidth reduction,
elimination, or audit) in a secure system are more difficult than for covert storage channels for the
following reasons:
The following sections enumerate some of the covert timing channels that are identified in the
literature (for example, see [Schaefer77, Huskamp78, Karger and Wray91]). These examples are
necessarily generic in nature and are meant to be a starting point for identification of covert timing
channels in specific systems. We make two basic assumptions for all the examples detailed in the
following sections. First, in each scenario we assume the communicating processes either have a
continuous clock available that has reasonable resolution, or the processes create a time reference
by using simple counters in memory segments or files. Second, we assume the communicating
processes are running alone the system (i.e., little or no noise is present). This second assumption
ensures calculating the maximum channels bandwidths.
These two assumptions help identify some of the countermeasures that can be used against some
covert timing channels ina secure system. The first is to virtualize the clock in the system by
resetting the clock at every context switch [Lipner75]. However, this action could render the
system useless, since many system functions depend on a real, continuous time source. Also, this
countermeasure is ineffective when the communicating processes have constructed their own time
references. The other countermeasure that applies to most covert timing channels is the addition of
noise to the system in the form of added processes. While the countermeasure can effectively
reduce the bandwidth of the channel, it adds unwanted overhead to the system.
Consider a movable head I/O device that uses a scheduling algorithm called the "elevator
algorithm." The algorithm works as follows: requests are enqueued by ascending cylinder
number. Requests are then dequeued in order of ascending cylinder number until no greater
cylinder number remains (i.e., the upper end of the cylinder is reached) and then are dequeued in
descending order until no lower numbered cylinders remain (i.e., the lower end of the cylinder is
reached). This process is continuously repeated.
Again, let process R be a receiver at a low security level and process S be the sender at a higher
security level. Process R is the owner of cylinders 51 through 59 of a disk, to which S has read
access. Process R issues a request for cylinder 55, waits until notified of its completion, and then
relinquishes the CPU. Process S then issues a request for either cylinder 53 (to send a 0) or 57 (to
send a 1), and then relinquishes the CPU. Process R then issues requests for cylinders 58 and 52,
recording a 1 or 0 depending on which request completes first.
Note that similar timing channels can be found for other I/O scheduling algorithms. One way to
eliminate these channels is to keep a process from viewing its requests until the entire queue of
requests has been completed. This action also leads to underutilization of the i/O processing power.
Assume process S and process R own separate portions of the same movable-head I/O device.
Process S and process R synchronize themselves to run alternately by using the system's
synchronization facilities. For an example of the synchronization primitives that could be used, see
[Reed and Kanodia78]. T send a 1, process S requests a read on a part of the disk that is farthest
from process R's portion of the disk. To send a 0, process S does nothing. Process R issues a read
to its portion of the disk and determines the bit of information received depending on the time that
it takes for the request to complete.
Note that both the I/O scheduling and the I/O completion channels are similar to the CPU
quantum and CPU interquantum channels of Example3, Section 2.2.1.
Below we describe two possible covert timing channels associated with the activity of
memory resource management. Both involve a sending process conveying information by
modulating the frequency with which a receiver process obtains a resource. The first channel
involves the ability of the sender to modulate the data paging rate; the second involves the sender
modulating the time the receiver takes to obtain addressability to a segment via an active segment
table.
Suppose a sender process S whose security level dominates that of a receiver process R can
request the same page of data in a demand-paging environment. In this scenario, the receiver
process R's security level must dominate the security level of the page, and the processes S and R
must possess "read" access to the page. The sender process S may not possess "write" access to the
page. Imagine also that the page has not been referenced, and so is not resident in main memory.
Additionally, the processes S and R must agree on a set of pages to be used to exploit this covert
channel. Process S can now modulate process R's response time (and thus send a bit of information
to R) when reading the page by either referencing the page or not (bringing the page into memory
or not). If process S is reading (or not reading) from a new page each time, it can continually send
information to R. Since memory is not infinite, a new page cannot be referenced each time. A
potentially continuous channel still exists, though, as long as process S has more pages available
to it than the memory management working set size, the pages are referenced ina circular fashion,
and the memory manager is using a Least Recently Used (LRU) page-replacement algorithm.
The active segment table channel is very similar to the data page pool channel, and is only a
threat in a segmented architecture. The sending process S either introduces a new segment into its
address space (resulting in the segment being entered into the active segment table) or doesn't,
depending on the desired value to be transmitted. The receiving process R introduces the same
segment into its address space, and perceives the difference in response time, which varies
depending upon whether or not the entry is already in the active segment table. Similar to the data
page pool case, this channel can be made continuous as long as process S and process R share more
segments than there are slots in the active segment table and process S releases the previous
iteration's segment (removing it from the table) before proceeding to the next interation.
Consider a system in which multiple single-level devices, of perhaps different levels, are
handled by the same controller, and I/O to each device is scheduled serially. Process S, which is
writing to device A, can send information to process R (R is dominated by S), which is writing to
device B, by varying the time that it spends doming I/O. Note that this channels's bandwidth can
potentially be raised by transmitting more elaborate bit patterns than just 0 or 1 with the use of
encoding techniques (by associating higher radix digits with different time intervals perceived by
the receiver). For example, a perceived interval of 0 to x would indicate a value of 0, interval x to
y would be a 1, and interval y to z would be a 2. Note, however, that more elaborate schemes for
encoding of data can be more susceptible to the effects of noise.
In come systems, a user is allowed to obtain exclusive use of a segment. If a process currently
has exclusive access to a segment, other requests for access to the segment are blocked until the
segment becomes available. Therefore, a sending process S at a high security level could
potentially gain exclusive access to a segment, and modulate the time it takes for a receiving
process R at a lower security level to gain access to the segment. Note that, as in the previous
section, the bandwidth of the channel could potentially be raised by the transmission of more
elaborate bit patterns.
Consider a system where a central lock provides and controls process synchronization
primitives. Contention for this central coordination can then be exploited to create a timing
channel. The required configuration is similar to that of Example 4 of Section 2.2.1: three
processors in system, one process per processor, with a clock process incrementing a counter ina
shared segment. The receiver process R continuously reads the shared counter, attempts two
synchronization primitive calls, and reads the counter again. The sender process S (whose security
level dominates that of the receiver process R) transmits a bit of data by either making a
synchronization call (thereby causing contention) or waiting for the amount of time it would take
to make two synchronization call (thereby causing contention) or waiting for the amount of time it
would take to make two synchronization calls (one with contention), in order to stay synchronized.
The receiver process R discriminates binary data by comparing the two reads of the counter in the
shared segment. The delay will be longer if the sender process S has created contention.
The TCSEC requires one use formal methods in the covert channel analysis of a system targeted
for the A1 class. A number of tools exist, and are generally associated with a particular suite of
tools such as the Formal Development Methodology (FDM), the Enhanced Hierarchical
Development Methodology (EHDM), and the Gypsy Verification Environment (GVE). Although
the emphasis has been on examining specifications written in a language such as Ina Jo (FDM),
Revised Special (EHDM), or Gypsy (GVE), some work has been done on analysis of source code
for covert channels using tools (see Section 3.2).
The examination for covert channels involves
looking at each variable referenced in the specification, and deciding where information flow is
possible.
The goal of using these tools is to identify (with respect to a given policy) insecure flows, so that
all such flows in a system can be reduced or eliminated. However, as discussed in Section 3.1, use
of a flow tool on a specification does not guarantee that insecure flows do not exist in an
implementation; rather, it guarantees that insecure flows do not exist in, and are not required by,
the specification. For this reason, one must be careful concerning assertions made about the
application of a given tool to a design. Also, since the tools developed to date are not designed to
find timing channel scenarios, they are useful primarily in the identification of covert storage
channels.
The information-flow tools described below are the FDM Multilevel Secure (MLS) and SRM
tools, the Gypsy Flow Analyzer, and the EHDM MLS tool. Chapter 3 describes the use of formal
methods in the identification of covert channels in source code.
The MLS tool of Ina Flo identifies flows in an Ina Jo specification by examining dependencies
between variables and formal parameters of transforms from one state to the next. If x and y are
variables or formal parameters of a transforms from one state to the next. If x and y are variables
or formal parameters of a transform, and the new value of y depends on the old value of x, then
information flows from x to y. MLS also includes the following rule for determining security: A
flow is secure if and only if the label (security level) of variable y dominates the label of variable
x (i.e., the *-property [Bell and La Padula76] is preserved). The user assigns labels to variables and
defines a partial ordering on those labels (defines the dominates relation). MLS then generates a
list of conjectures (one list per transform) which, when proven, guarantee there are no storage
channels in the specification. Conjectures that cannot be proven represent potential covert channels
which must be handled with manual analysis.
Because Ina Jo specifications can be written ina nondeterministic manner, the dependencies
between old and new values of variables can be difficult to determine. For this reason, the
generation of information regarding nondeterministic flows is optional. A preprocessor called
"PREMLS" is available that accepts an Ina for specification and produces a more deterministic
version of the same specification.
The SRM tool of Ina Flo is an implementation of the SRM Method, and is intended to be used
on specifications in which the MLS tool cannot be used. This would be the case when the
specification does not contain complete security policy information. The SRM tool does not
provide as much automated capability as the MLS tool. It simply accepts the Ina Jo specification
and generates the corresponding shared resource matrix. Analysis of this matrix is then a manual
procedure.
The EHDM MLS Tool [Rushby84] is an information flow tool that is part of the Enhanced
Hierarchical Development Methodology. It accepts as input a specification written in Revised
Special and produces a set of theorems to be verified. The successful verification of these theorems
asserts that the specification is multilevel secure as defined by the SRI model in [Rushby84].
A conceptually simple statement of the SRI model is that the information users can obtain from
a system cannot be influenced by users whose security level is greater than theirs. The model
assumes a lattice of security levels and a collection of users assigned a security level. If operations
in the system possess an invocation level SL1 then the operation is multilevel secure if:
Two concerns about the MLS tool are raised in [Kemmerer86]. One is that the volume of
generated theorems will be very high. The other is that all of the theorems may not be provable in
an automated way using the EHDM theorem prover, so the user may have to edit the PROOF
module, adding lemmas that make the verification conditions provable.
An earlier version of the MLS flow tool (old HDM) was used in the SCOMP verification effort
[Benzel84] to identify a number of covert channels. Isolation of the potential channels consisted of
tracing unprovable verification conditions back to the system specification, and then tracing the
lines of the specification back to the lines of code, using the results of the specification-to-code
correspondence effort before undertaking the task of applying the MLS flow tool to the
specification.
The previous three sections discuss various formal tools that can be used for the identification
of covert storage channels by examining the specification of a system. This section outlines the
steps of a formal method that has been developed for the identification of covert storage channels
by examination of the source code of a system. [Tsai90, He and Gligor90] The advantages of a
formal source-code approach to the identification of covert channels are:
5.4 TCSEC REQUIREMENTS AND RECOMMENDATIONS
The design documentation requirements state:
The [NCSC TCSEC] guidelines on covert channels suggest the following combination of the
above methods: (1) use elimination methods wherever possible to eliminate channels with
bandwidths over 0.1 bits/second; (2) use bandwidth-limitation methods to reduce, whenever
possible, the maximum bandwidth of every channel that cannot be eliminated to 1 bit/second or
less; (3) use deterrence methods, namely audit, for channels with bandwidths over 0.1 bit/second;
and (4) use a "don't care" policy for covert channels with bandwidths less than 0.1 bit/second.
This policy allows for the existence of storage channels that are not auditable. Also, it allows
for the possibility that covert storage and timing channels with bandwidths over B = 1 bit/second
will exist in secure systems. However, the suggested values of b = 0.1 bits/second and B = 1 bit/
second are not justified based on any specific policy. The only basis for deriving these values is the
determination that:
(Note: This guide may not contain the current covert channel bandwidth policy, which is
subject to change. Please contact the NCSC for information about the current policy.)
5.5 HANDLING POLICIES BASED ON THREAT ANALYSIS
These considerations indicate that the values of the bandwidth limits b and B can only be
determined after a threat analysis which includes the above factors. Let us consider an example
illustrating the necessity of threat analysis in the environment of secure system use.
Example 19 - Application Dependency of Bandwidth Limits
6.0 COVERT CHANNEL TESTING
6.1 TESTING REQUIREMENTS AND RECOMMENDATIONS
6.2 TEST DOCUMENTATION
7.0 SATISFYING THE TCSEC REQUIREMENTS FOR COVERT
CHANNEL ANALYSIS
7.1 REQUIREMENTS FOR CLASS B2
7.1.1 Covert Channel Analysis
7.1.2 Audit
7.1.3 Design Documentation
Part of the TCSEC requirements for this area states the following:
Documentation of Identified Channels
7.1.4 Test Documentation
7.2 ADDITIONAL REQUIREMENTS FOR CLASS B3
7.2.1 Covert Channel Analysis
7.2.2 Audit
7.2.3 Design Documentation
7.2.4 Test Documentation
7.3 ADDITIONAL REQUIREMENTS FOR CLASS A1
ACRONYMS AND ABBREVIATIONS
AIS Automated Information System
CCA Covert Channel Analysis
CPU Central Processing Unit
DAC Discretionary Access Control
DoD Department of Defense
DTLS Descriptive Top-level Specification
EHDM Enhance Hierarchical Development Methodology
FDM Formal Development Methodology
FTLS Formal Top-level Specification
GVE Gypsy Verification Environment
HDM Hierarchical Development Methodology
I/O Input/Output
IPC InterProcess Communication
LOCK Logical Co-processing Kernel
LRU Least Recently Used
MAC Mandatory Access Control
MLS Multilevel Secure
NCSC National Computer Security Center
SAT Secure Ada Target
SRM Shared Resource Matrix
TCB Trusted Computing Base
TCSEC Trusted Computer System Evaluation Criteria
TLS Top-level Specification
GLOSSARY
REFERENCES
[Andrews and Reitman80]
G. R. Andrews and R. P. Reitman, "An Axiomatic Approach to Information Flow in
Programs," ACM Transactions on Programming Languages and Systems, 2:1, pp. 56-76, January
1980.
[Bach86]
M. J. Bach, The Design of the UNIX Operating System, Prentice-Hall Inc., Englewood
Cliffs, New Jersey, 1986.
[Bell and La Padula76]
D. E. Bell and L. J. La Padula, Secure Computer System: Unified Exposition and Multics
Interpretation, The MITRE Corp., Report No. MTR-2997 Revision 1, Electronic Systems
Division, U. S. Air Force Systems Command, Technical Report ESD-TR-75-306, Bedford,
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APPENDIX A - ADDITIONAL EXAMPLES OF COVERT CHANNELS
A.1 STORAGE CHANNELS
A.1.1 Table-Space Exhaustion Channels
A.1.2 Unmount of Busy File System Channels
A.1.3 Printer Attachment Channel
A.2 TIMING CHANNELS
Despite the problems listed above, to a certain extent one can design a secure system that limits
or eliminates some types of covert timing channels. For example, one can eliminate a potential
covert timing channel by time-partitioning a shared resource on a security-level basis (see Section
5.1).
The addition of noise (for example, in the form of added processes) of added process) can also
reduce the bandwidth of most covert timing channels.
A.2.1. I/O Scheduling Channels
A.2.2 I/O Operation Completion Channels
A.2.3 Memory Resource Management Channels
A.2.3.1 Data Page Pool Channels
A.2.3.2 Active Segment Table Channels
A.2.4 Device Controller Contention Channels
A.2.5 Exclusive Use of Segments Channels
A.2.6 Synchronization Primitive Contention Channels
APPENDIX B - TOOLS FOR COVERT CHANNEL IDENTIFICATION
B.1.1 MLS
B.1.2 SRM
The application of a flow tool such as this to the problem of identification of convert channels
in secure systems involves the assignment of labels to variables, the definition of a flow policy, and
the definition of a partial ordering among different label values, much like is done with the MLS
tool of the FDM. Note that the choice of the flow policy is at the discretion of the user of the flow
tool. The entire process of using the Gypsy Flow Tool is summarized in [McHugh and Good85] as
follows:
Difficulty in proof of the verification conditions indicates existence of flows that violate the
stated flow policy. The source of these illegal flows must be pinpointed exactly and treated so that
the proof step can be completed. Unfortunately, in a large program, locating illegal flows can be
very difficult, and the Gypsy Flow Tool does not provide much help in this area.
B.3 EHDM MLS TOOL
The SRI model is conceptually similar to the Bell and La Padula model [Bell and La Padula76].
The MLS tool produces a set of theorems for each operation that correspond to the three conditions
stated above. Violations of the model may appear in the generated output, and may indicate design
flaws or covert channels.
B.4 SOURCE-CODE ANALYSIS TOOL
In addition to the advantages stated above, a code level examination for covert storage channels
seems to be stronger than the specification level searches provided by FDM. GVE, and HDM, since
a formal method has not been developed for showing the correspondence of the specification to the
code. The code-level search for covert storage channels is theoretically similar to specification-
level approaches and is conducted as follows:
For more details on this method of channel identification, we refer the reader to [Tsai90, He and
Gligor90].