JPCERT/CC Study on Reverse Engineering Rust Binaries

On March 15, 2026, JPCERT/CC published a study examining the challenges and techniques involved in reverse engineering binaries compiled from the Rust programming language. This research aims to aid security analysts and reverse engineers in understanding the structure and characteristics of Rust-based malware. Rust’s increasing popularity among malware authors necessitates specialized knowledge to effectively analyze and detect these threats. The study details specific features of Rust binaries that differ from those compiled from other languages like C or C++, focusing on aspects such as metadata handling, string encoding, and unique function calling conventions. The research provides practical guidance for overcoming common obstacles encountered during reverse engineering of Rust binaries.

Attack Chain

This threat brief focuses on the analysis of Rust binaries, not a specific attack chain. However, understanding the structure of these binaries is crucial for analyzing attacks leveraging them. The following steps outline a general reverse engineering process applicable to any binary, with considerations specific to Rust:

1. Initial Reconnaissance: Obtain the Rust binary and gather basic information such as file type, size, and compilation timestamp using tools like file and strings.
2. Metadata Analysis: Examine the binary’s metadata section to identify Rust version, crate dependencies, and potentially debug symbols. This can be done using tools like objdump or specialized Rust metadata parsers.
3. String Extraction: Extract embedded strings from the binary. Note that Rust often uses UTF-8 encoding for strings, so ensure your tools support this encoding.
4. Function Identification: Identify key functions such as main, and any other functions related to suspicious behavior. Tools like IDA Pro or Ghidra can be used for disassembly and function analysis.
5. Control Flow Analysis: Analyze the control flow of the program, paying attention to function calls and branching logic. Rust’s ownership and borrowing system can make control flow more complex than in C/C++.
6. Dependency Analysis: Identify and analyze any external crates (libraries) used by the binary. These crates may contain known vulnerabilities or malicious code.
7. Behavioral Analysis: Execute the binary in a controlled environment (sandbox) to observe its behavior, including file system access, network connections, and registry modifications.
8. Detection Rule Creation: Based on the reverse engineering and behavioral analysis, create detection rules for identifying similar malicious Rust binaries.

Impact

The increasing use of Rust in malware development poses a challenge for security analysts. Successful reverse engineering and understanding of Rust binaries are crucial for detecting and mitigating threats. Failure to adapt to this trend could lead to a decreased ability to identify and respond to novel malware strains.

Recommendation

• Familiarize detection engineers with the structure and characteristics of Rust binaries as described in the JPCERT/CC study to improve reverse engineering capabilities.
• Implement the Sigma rules provided below to detect suspicious behaviors commonly associated with potentially malicious binaries, adjusting thresholds and whitelists as needed for your environment.
• Utilize tools capable of parsing Rust metadata to extract crate dependencies and other useful information from Rust binaries during analysis, as described in the “Metadata Analysis” step above.