Large-scale attacks, such as those launched by worms and zombie farms, pose a serious threat to our network-centric society. Existing approaches such as software patches are simply unable to cope with the volume and speed with which new vulnerabilities are being discovered. In this paper, we develop a new approach that can provide effective protection against a vast majority of these attacks that exploit memory errors in C/C++ programs. Our approach, called COVERS, uses a forensic analysis of a victim server's memory to correlate attacks to inputs received over the network, and automatically develop a signature that characterizes inputs that carry attacks. The signatures tend to capture characteristics of the underlying vulnerability (e.g., a message field being too long) rather than the characteristics of an attack, which makes them effective against variants of attacks. Our approach introduces low overheads (under 10%), does not require access to source code of the protected server, and has successfully generated signatures for the attacks studied in our experiments, without producing false positives. Since the signatures are generated in tens of milliseconds, they can potentially be distributed quickly over the Internet to filter out (and thus stop) fastspreading worms. Another interesting aspect of our approach is that it can defeat guessing attacks reported against address-space randomization and instruction set randomization techniques. Finally, it increases the capacity of servers to withstand repeated attacks by a factor of 10 or more.

Buffer overflows have become the most common target for network-based attacks. They are also the primary mechanism used by worms and other forms of automated attacks. Although many techniques have been developed to prevent server compromises due to buffer overflows, these defenses still lead to server crashes. When attacks occur repeatedly, as is common with automated attacks, these protection mechanisms lead to repeated restarts of the victim application, rendering its service unavailable. To overcome this problem, we develop a new approach that can learn the characteristics of a particular attack, and filter out future instances of the same attack or its variants. By doing so, our approach significantly increases the availability of servers subjected to repeated attacks. The approach is fully automatic, does not require source code, and has low runtime overheads. In our experiments, it was effective against most attacks, and did not produce any false positives.

It is crucial to detect zero-day polymorphic worms and to generate signatures at the edge network gateways or honeynets so that we can prevent the worms from propagating at their early phase. However, most existing network-based signatures generated are not vulnerability based and can be easily evaded under attacks. In this paper, we propose to design vulnerability based signatures without any host-level analysis of worm execution or vulnerable programs. As the first step, we design a network-based Length-based Signature Generator (LESG) for worms based on buffer overflow vulnerabilities. The signatures generated are intrinsic to buffer overflows, and are very hard for attackers to evade. We further prove the attack resilience bounds even under worst case attacks with deliberate noise injection. Moreover, LESG is fast, noise-tolerant, and has efficient signature matching. Evaluation based on real-world vulnerabilities of various protocols and real network traffic demonstrates that LESG is promising in achieving these goals.

Abstract—It is crucial to detect zero-day polymorphic worms and to generate signatures at network gateways or honeynets so that we can prevent worms from propagating at their early phase. However, most existing network-based signatures are specific to exploit and can be easily evaded. In this paper, we propose generating vulnerability-driven signatures at network level without any host-level analysis of worm execution or vulnerable programs. As the first step, we design a network-based length-based signature generator (LESG) for the worms exploiting buffer overflow vulnerabilities1. The signatures generated are intrinsic to buffer overflows, and are very difficult for attackers to evade. We further prove the attack resilience bounds even under worst-case attacks with deliberate noise injection. Moreover, LESG is fast and noisetolerant and has efficient signature matching. Evaluation based on real-world vulnerabilities of various protocols and real network traffic demonstrates that LESG is promising in achieving these goals. Index Terms—length-based signature, polymorphic worm, worm signature generation, zero-day vulnerability. I.