Theory and Techniques for Automatic Generation of Vulnerability-Based Signatures
Abstract
In this paper, we explore the problem of creating vulnerability signatures. A vulnerability signature matches all exploits of a given vulnerability, including polymorphic and metamorphic variants. Our work departs from previous approaches by focusing on the semantics of the program and vulnerability exercised by a sample exploit instead of the semantics or syntax of the exploit itself. We show the semantics of a vulnerability define a language which contains all and only those inputs that exploit the vulnerability. A vulnerability signature is a representation (e.g., a regular expression) of the vulnerability language. Unlike exploit-based signatures whose error rate can only be empirically measured for known test cases, the quality of a vulnerability signature can be formally quantified for all possible inputs. We provide a formal definition of a vulnerability signature and investigate the computational complexity of creating and matching vulnerability signatures. We also systematically explore the design space of vulnerability signatures. We identify three central issues in vulnerability-signature creation: how a vulnerability signature represents the set of inputs that may exercise a vulnerability, the vulnerability coverage (i.e., number of vulnerable program paths) that is subject to our analysis during signature creation, and how a vulnerability signature is created for a given representation and coverage. We propose new data-flow analysis and a novel adoption of existing techniques, such as constraint solving, for automatically generating vulnerability signatures. We have built a prototype system to test our techniques. Our experiments show that we can, using a single exploit, automatically generate a vulnerability signature which is of much higher quality than previous exploit-based signatures. In addition, our techniques have several other security applications, and thus may be of independent interest.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2006
- Accession Number
- ADA462599
Entities
People
- David Brumley
- Dawn Song
- Hao Wang
- James Newsome
- Somesh Jha
Organizations
- Carnegie Mellon University