RevEng.AI
Uses AI to detect vulnerabilities and malicious code in software binaries, enhancing supply chain security.
| Date | Investors | Amount | Round |
|---|---|---|---|
* | $4.2m | Seed | |
| Total Funding | 000k | ||
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RevEng.AI is a London-based cybersecurity firm, founded in 2022 by Dr. James Patrick-Evans, that specializes in analyzing binary code to secure software supply chains. The company operates in the cybersecurity market, targeting security engineers and malware analysts. Its core business revolves around a proprietary AI model called BinNet™, described as the world's largest of its kind for understanding the semantics of binary machine code. Revenue is generated through its AI Binary Analysis Platform, which provides detailed software analysis without requiring access to the source code.
The founder and CEO, Dr. James Patrick-Evans, developed the foundational technology during his PhD at Royal Holloway in collaboration with Universität der Bundeswehr München. This academic background in binary analysis directly informs the company's core technology. The firm has successfully completed notable accelerator programs, including the UK National Cyber Security Centre's Startups program and the Intel Ignite 2024 cohort, which provided access to resources and commercial partners.
RevEng.AI's platform addresses the critical challenge of identifying vulnerabilities, malicious code, and backdoors in compiled software, a significant issue given that a large percentage of organizations are expected to face software supply chain attacks. The platform integrates with Linux, Windows, and Android environments and offers tools like a command-line interface and a Ghidra plugin to fit into existing developer workflows. Key features include in-depth analysis of a binary's capabilities, security assessments, and the automatic creation of YARA rules for threat hunting. In June 2025, the company secured $4.15 million in a seed funding round led by Sands Capital, with participation from In-Q-Tel Capital, IQ Capital, and Episode 1, to enhance its AI models and expand its presence in the U.S. market.
Keywords: binary analysis, software supply chain security, malware analysis, reverse engineering, cybersecurity AI, vulnerability detection, threat hunting, machine code analysis, BinNet, James Patrick-Evans, binary-level security, software integrity, malicious code detection, automated YARA rule generation, Ghidra plugin, software composition analysis, deep learning cybersecurity, closed-source analysis, threat intelligence, application security