Binary-level Function Profiling for Intrusion Detection and Smart Error Virtualization

Most current approaches to self-healing software (SHS) suffer from semantic incorrectness of the response mechanism. To support SHS, we propose Smart Error Virtualization (SEV), which treats functions as transactions but provides a way to guide the program state and remediation to be a more correct value than previous work. We perform runtime binary-level profiling on unmodified applications to learn both good return values and error return values (produced when the program encounters ``bad'' input). The goal is to ``learn from mistakes'' by converting malicious input to the program's notion of ``bad'' input. We introduce two implementations of this system that support three major uses: function profiling for regression testing, function profiling for host-based anomaly detection (environment-specialized fault detection), and function profiling for automatic attack remediation via SEV. Our systems do not require access to the source code of the application to enact a fix. Finally, this paper is, in part, a critical examination of error virtualization in order to shed light on how to approach semantic correctness

Dark Application Communities

In considering new security paradigms, it is often worthwhile to anticipate the direction and nature of future attack paradigms. We identify a class of attacks based on the idea of a "Dark" Application Community (DAC) - a collection of bots and zombie machines that actively performs binary-level supervision of applications to help an attacker automate the process of finding vulnerabilities. A collection of such hosts can observe and attempt to influence the behavior of automatic defense systems. An attacker can use the DAC as both a test platform for subverting security applications and as a reconnaissance network for exploiting commonly deployed automatic update and early warning systems. An instance of this type of Application Community can host what we call an automorphic worm. An automorphic worm is application-agnostic and vulnerability-generic. Such a worm attempts to remain stealthy by cycling through the portfolio of vulnerabilities that the DAC has identified. We examine the underlying principles of a DAC, which are based on the existing paradigm of using security tools to help violate security

Polygraph: Automatically generating signatures for polymorphic worms

It is widely believed that content-signature-based intrusion detection systems (IDSes) are easily evaded by polymorphic worms, which vary their payload on every infection attempt. In this paper, we present Polygraph, a signature generation system that successfully produces signatures that match polymorphic worms. Polygraph generates signatures that consist of multiple disjoint content sub-strings. In doing so, Polygraph leverages our insight that for a real-world exploit to function properly, multiple invariant substrings must often be present in all variants of a payload; these substrings typically correspond to protocol framing, return addresses, and in some cases, poorly obfuscated code. We contribute a definition of the polymorphic signature generation problem; propose classes of signature suited for matching polymorphic worm payloads; and present algorithms for automatic generation of signatures in these classes. Our evaluation of these algorithms on a range of polymorphic worms demonstrates that Polygraph produces signatures for polymorphic worms that exhibit low false negatives and false positives. © 2005 IEEE

CONFLLVM: A Compiler for Enforcing Data Confidentiality in Low-Level Code

We present an instrumenting compiler for enforcing data confidentiality in low-level applications (e.g. those written in C) in the presence of an active adversary. In our approach, the programmer marks secret data by writing lightweight annotations on top-level definitions in the source code. The compiler then uses a static flow analysis coupled with efficient runtime instrumentation, a custom memory layout, and custom control-flow integrity checks to prevent data leaks even in the presence of low-level attacks. We have implemented our scheme as part of the LLVM compiler. We evaluate it on the SPEC micro-benchmarks for performance, and on larger, real-world applications (including OpenLDAP, which is around 300KLoC) for programmer overhead required to restructure the application when protecting the sensitive data such as passwords. We find that performance overheads introduced by our instrumentation are moderate (average 12% on SPEC), and the programmer effort to port OpenLDAP is only about 160 LoC.Comment: Technical report for CONFLLVM: A Compiler for Enforcing Data Confidentiality in Low-Level Code, appearing at EuroSys 201

Smashing the Stack with Hydra: The Many Heads of Advanced Polymorphic Shellcode

Recent work on the analysis of polymorphic shellcode engines suggests that modern obfuscation methods would soon eliminate the usefulness of signature-based network intrusion detection methods and supports growing views that the new generation of shellcode cannot be accurately and efficiently represented by the string signatures which current IDS and AV scanners rely upon. In this paper, we expand on this area of study by demonstrating never before seen concepts in advanced shellcode polymorphism with a proof-of-concept engine which we call Hydra. Hydra distinguishes itself by integrating an array of obfuscation techniques, such as recursive NOP sleds and multi-layer ciphering into one system while offering multiple improvements upon existing strategies. We also introduce never before seen attack methods such as byte-splicing statistical mimicry, safe-returns with forking shellcode and syscall-time-locking. In total, Hydra simultaneously attacks signature, statistical, disassembly, behavioral and emulation-based sensors, as well as frustrates offline forensics. This engine was developed to present an updated view of the frontier of modern polymorphic shellcode and provide an effective tool for evaluation of IDS systems, Cyber test ranges and other related security technologies