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Fast and Black-box Exploit Detection and Signature Generation for Commodity Software
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ACM Transactions on Information and System Security (TISSEC) archive
Volume 12 ,  Issue 2  (December 2008) table of contents
Article No. 11  
Year of Publication: 2008
ISSN:1094-9224
Authors
Xiaofeng Wang  Indiana University
Zhuowei Li  Indiana University
Jong Youl Choi  Indiana University
Jun Xu  Google Inc. and North Carolina State University
Michael K. Reiter  University of North Carolina at Chapel Hill
Chongkyung Kil  North Carolina0 State University
Publisher
ACM  New York, NY, USA
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ABSTRACT

In biology, a vaccine is a weakened strain of a virus or bacterium that is intentionally injected into the body for the purpose of stimulating antibody production. Inspired by this idea, we propose a packet vaccine mechanism that randomizes address-like strings in packet payloads to carry out fast exploit detection and signature generation. An exploit with a randomized jump address behaves like a vaccine: it will likely cause an exception in a vulnerable program’s process when attempting to hijack the control flow, and thereby expose itself. Taking that exploit as a template, our signature generator creates a set of new vaccines to probe the program in an attempt to uncover the necessary conditions for the exploit to happen. A signature is built upon these conditions to shield the underlying vulnerability from further attacks. In this way, packet vaccine detects exploits and generates signatures in a black-box fashion, that is, not relying on the knowledge of a vulnerable program’s source and binary code. Therefore, it even works on the commodity software obfuscated for the purpose of copyright protection. In addition, since our approach avoids the expense of tracking the program’s execution flow, it performs almost as fast as a normal run of the program and is capable of generating a signature of high quality within seconds or even subseconds. We present the design of the packet vaccine mechanism and an example of its application. We also describe our proof-of-concept implementation and the evaluation of our technique using real exploits.


REFERENCES

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Collaborative Colleagues:
Xiaofeng Wang: colleagues
Zhuowei Li: colleagues
Jong Youl Choi: colleagues
Jun Xu: colleagues
Michael K. Reiter: colleagues
Chongkyung Kil: colleagues