Using HTML5 to Prevent Detection of Drive-by-Download Web Malware

The web is experiencing an explosive growth in the last years. New technologies are introduced at a very fast-pace with the aim of narrowing the gap between web-based applications and traditional desktop applications. The results are web applications that look and feel almost like desktop applications while retaining the advantages of being originated from the web. However, these advancements come at a price. The same technologies used to build responsive, pleasant and fully-featured web applications, can also be used to write web malware able to escape detection systems. In this article we present new obfuscation techniques, based on some of the features of the upcoming HTML5 standard, which can be used to deceive malware detection systems. The proposed techniques have been experimented on a reference set of obfuscated malware. Our results show that the malware rewritten using our obfuscation techniques go undetected while being analyzed by a large number of detection systems. The same detection systems were able to correctly identify the same malware in its original unobfuscated form. We also provide some hints about how the existing malware detection systems can be modified in order to cope with these new techniques.Comment: This is the pre-peer reviewed version of the article: \emph{Using HTML5 to Prevent Detection of Drive-by-Download Web Malware}, which has been published in final form at \url{http://dx.doi.org/10.1002/sec.1077}. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archivin

Formal Verification of Security Protocol Implementations: A Survey

Automated formal verification of security protocols has been mostly focused on analyzing high-level abstract models which, however, are significantly different from real protocol implementations written in programming languages. Recently, some researchers have started investigating techniques that bring automated formal proofs closer to real implementations. This paper surveys these attempts, focusing on approaches that target the application code that implements protocol logic, rather than the libraries that implement cryptography. According to these approaches, libraries are assumed to correctly implement some models. The aim is to derive formal proofs that, under this assumption, give assurance about the application code that implements the protocol logic. The two main approaches of model extraction and code generation are presented, along with the main techniques adopted for each approac

Towards Smart Hybrid Fuzzing for Smart Contracts

Smart contracts are Turing-complete programs that are executed across a blockchain network. Unlike traditional programs, once deployed they cannot be modified. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In recent years, smart contracts suffered major exploits, costing millions of dollars, due to programming errors. As a result, a variety of tools for detecting bugs has been proposed. However, majority of these tools often yield many false positives due to over-approximation or poor code coverage due to complex path constraints. Fuzzing or fuzz testing is a popular and effective software testing technique. However, traditional fuzzers tend to be more effective towards finding shallow bugs and less effective in finding bugs that lie deeper in the execution. In this work, we present CONFUZZIUS, a hybrid fuzzer that combines evolutionary fuzzing with constraint solving in order to execute more code and find more bugs in smart contracts. Evolutionary fuzzing is used to exercise shallow parts of a smart contract, while constraint solving is used to generate inputs which satisfy complex conditions that prevent the evolutionary fuzzing from exploring deeper paths. Moreover, we use data dependency analysis to efficiently generate sequences of transactions, that create specific contract states in which bugs may be hidden. We evaluate the effectiveness of our fuzzing strategy, by comparing CONFUZZIUS with state-of-the-art symbolic execution tools and fuzzers. Our evaluation shows that our hybrid fuzzing approach produces significantly better results than state-of-the-art symbolic execution tools and fuzzers

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

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