Toward Exact And Inexact Approximate Matching Of Executable Binaries

Lorenz Liebler discusses his research at DFRWS EU 2019.

The application of approximate matching (a.k.a. fuzzy hashing or similarity hashing) is often considered in the field of malware or binary analysis. Recent research showed major weaknesses of predominant fuzzy hashing techniques in the case of measuring the similarity of executables (Pagani et al., 2018).

Summarized, well known Context-Triggered Piecewise-Hashing approaches are not very reliant for the task of binary comparisons, as even benign changes heavily impact the underlying byte representation of an original binary. Modifications could be caused by benign or malicious source code changes, different compilers, and changed compiler settings.

Approaches based on the extraction of statistically improbable features (Roussev, 2010) or n-gram histograms (Oliver et al., 2013) showed a better detection performance in case of inexactly matching binaries with varying build settings or source code modifications.

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File timestamps are used by forensics practitioners as a fundamental artifact. For example, the creation of user files can show traces of user activity, while system files, like configuration and log files, typically reveal when a program was run.

Despite timestamps being ubiquitous, the understanding of their exact meaning is mostly overlooked in favor of fully-automated, correlation-based approaches. Existing work for practitioners aims at understanding Windows and is not directly applicable to Unix-like systems.

In this paper, we review how each layer of the software stack (kernel, file system, libraries, application) influences MACB timestamps on Unix systems such as Linux, OpenBSD, FreeBSD and macOS.

We examine how POSIX specifies the timestamp behavior and propose a framework for automatically profiling OS kernels, user mode libraries and applications, including compliance checks against POSIX.

Our implementation covers four different operating systems, the GIO and Qt library, as well as several user mode applications and is released as open-source.

Based on 187 compliance tests and automated profiling covering common file operations, we found multiple unexpected and non-compliant behaviors, both on common operations and in edge cases.

Furthermore, we provide tables summarizing timestamp behavior aimed to be used by practitioners as a quick-reference.

Learn more: https://dfrws.org/presentation/a-systematic-approach-to-understanding-macb-timestamps-on-unixlike-systems/

YouTube Video UCQajlJPesqmyWJDN52AZI4Q_i0zd7HtluzY

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