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Introduction

In this paper we address the problem of how an operating-system kernel or a server can determine with absolute certainty that it is safe to execute code supplied by an application or other untrusted source. We propose a mechanism that allows a kernel or server--from now on referred to as the code consumer--to define a safety policy and then verify that the policy is respected by native-code binaries supplied to it by an untrusted code producer.

In contrast to some previous approaches, we do not rely on the usual authentication or code-editing mechanisms. Instead, we require that the code producer creates its binaries in a special form, which we call proof-carrying code, or simply . A binary contains an encoding of a formal proof that the enclosed native code respects the safety policy. The proof is structured in such a way that makes it easy and foolproof for any agent (and in particular, the code consumer) to verify its validity without using cryptographic techniques or consulting with external trusted entities; there is also no need for any program analysis, code editing, compilation, or interpretation. Besides being safe, binaries are also extremely fast because the safety check needs to be conducted only once, after which the consumer knows it can safely execute the binary without any further run-time checking.

In a binary, the proof is linked with the native code so that its validity guarantees the code's safety. Furthermore, proof-carrying code is tamper-proof; the consumer can easily detect most attempts by any malicious agent to forge a proof or modify the code. Tampering can go undetected only if the adulterated code is still guaranteed to respect the consumer-defined safety policy. Another feature of the method is that the proof checking algorithm is very simple, allowing fast and easy-to-trust implementations.

The safety policy is defined and published by the code consumer and comprises a set of proof-formation rules, along with a set of preconditions. Safety policies can be defined to stipulate standard requirements such as memory safety, as well as more abstract and fine-grained guarantees about the integrity of data-abstraction boundaries. To take a simple example, consider the abstract type of file descriptors. In this case, a client is said to preserve the abstraction boundaries if it does not exploit the fact that file descriptors are represented as integers (by incrementing a file descriptor, for example).

Although we have worked out many of the theoretical underpinnings for (and indeed, most of the theory is based on old and well-known principles from logic, type theory [4, 11], and formal verification [5, 6, 8]), there are many difficult problems that remain to be solved. In particular we do not know at this point the most practical way to generate the proofs. We have thus set out to gain some preliminary experience, both to measure the benefits and to identify the practical problems.

In the experiments reported in this paper, we have in fact achieved fully automatic proof generation. In general, however, this problem is similar to program verification and is not completely automatable. Actually, the problem is somewhat easier than verification because we have the option of inserting extra run-time checks (as is done in Software Fault Isolation), which would have the effect of simplifying the proving process at the cost of reducing performance. By ``extra'', we mean run-time checks that are not intrinsically a part of the algorithm of the extension code. (For example, SFI will actually edit the code and insert ``extra'' checks; does not normally do this.) Fortunately, we have not yet had any need or desire to insert extra run-time checks in any of our examples. Still, automation of proof generation remains as one of the most serious obstacles to widespread practical application of PCC.

In our main experiment, we implemented several network packet filters [12, 15] in DEC Alpha assembly language [19] and then used a special prototype assembler to create binaries for them. We were motivated to use an unsafe assembly language in order to place equal emphasis on both performance and safety, as well as to demonstrate the generality of the approach. In addition to the assembler, we implemented a proof validator that accepts a binary, checks its safety proof, and if it is found to be valid, loads the enclosed native code and sets it up for execution.

The results of this and other experiments are encouraging. For our collection of packet filters, we are able to automate completely the generation of the binaries. The one-time cost of loading and checking the validity of the safety proofs is between 1 and 3 milliseconds. Because a safety proof guarantees safety, our hand-tuned packet filters can be executed safely in the kernel address space without adding any run-time checks. Predictably, they are much faster than safe packet filters produced by any other means with which we are familiar.

We believe that our early results show that proof-carrying code is a new point in the design space that is worthy of further attention and study. This paper presents an overview of the approach. We begin with a brief overview of the process of generating and validating the safety proofs. Then, we make this more concrete by showing how a safety policy can be defined and proofs created for a generic assembly language. This is followed by a description of our main experiment involving safe network packet filters. The benchmark results provide some preliminary indication that the methodology has the potential to surpass traditional approaches from a safety point of view while maintaining or improving performance. In particular, we show that leads to faster and safer packet filters than previous approaches to code safety in systems software, including Berkeley Packet Filters [12], Software Fault Isolation [23], and programming in the safe subset of Modula-3 [1, 9, 17]. Finally, we conclude with a discussion of the remaining difficulties and speculate on what might be necessary to make the approach work on a practical scale.

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Figure 1: Overview of Proof-Carrying Code. 



next up previous
Next: Proof-Carrying Code Up: Safe Kernel Extensions Without Previous: Safe Kernel Extensions Without



Peter Lee
Tue Sep 17 15:37:44 EDT 1996