Reverse Engineering With AI Unearths High-Severity GitHub Bug

APPLICATION SECURITY СLOUD SECURITY VULNERABILITIES & THREATS CYBER RISK NEWS Reverse Engineering With AI Unearths High-Severity GitHub Bug Wiz used an AI reverse-engineering tool to pinpoint a vulnerability that previously would have been too costly and time-consuming to undertake. Alexander Culafi,Senior News Writer,Dark Reading April 29, 2026 3 Min Read SOURCE: KLAUS OHLENSCHLAEGER VIA ALAMY STOCK PHOTO GitHub yesterday disclosed CVE-2026-3854, a high severity (8.7 CVSS) vulnerability identified in GitHub Enterprise Server that would grant an attacker with push access to a repository to achieve remote code execution. GitHub said in a blog post that the vulnerability also affected github.com, GitHub Enterprise Cloud, GitHub Enterprise Cloud with Data Residency, and GitHub Enterprise Cloud with Enterprise Managed Users.  Cloud security firm Wiz reported the vulnerability March 4 through GitHub's bug bounty program. GitHub said that, in less than two hours, it validated the finding, pushed a fix to github.com, and, after an investigation, concluded no exploitation had taken place.  While a remote code execution bug generally is worth calling attention to, the circumstances here are particularly noteworthy, as Wiz explained in its blog post. It's "one of the first critical vulnerabilities discovered in closed-source binaries using AI, highlighting a shift in how these flaws are identified." Related:Fresh Wave of GlassWorm VS Code Extensions Slices Through Supply Chain How CVE-2026-3854 Works As GitHub's Alexis Wales put it in the company's disclosure blog, user-pushed code in GitHub passes multiple internal services. Metadata, such as repository type and the environment it should be pushed in, is passed between services via an internal protocol.  "The vulnerability leveraged how user-supplied git push options were handled within this metadata. Push options are an intentional feature of git that allow clients to send key-value strings to the server during a push," she wrote. "However, the values provided by the user were incorporated into the internal metadata without sufficient sanitization. Because the internal metadata format used a delimiter character that could also appear in user input, an attacker could inject additional fields that the downstream service would interpret as trusted internal values." Wiz demonstrated that an attacker could chain several of these values together to bypass various protections and internal limitations to execute remote code. LOADING... GitHub and Wiz both advise GitHub Enterprise Server customers to upgrade to a fixed version (3.14.24, 3.15.19, 3.16.15, 3.17.12, 3.18.6 and 3.19.3); contrary to other affected products, Enterprise Server requires an authenticated user with push access to patch. GitHub Enterprise Cloud, GitHub Enterprise Cloud with Enterprise Managed Users, GitHub Enterprise Cloud with Data Residency, and github.com have been patched, and no user intervention is required.  In Wiz's blog post, security researcher Sagi Tzadik urged impacted users to upgrade, noting 88% of instances remained vulnerable at the time of publication. Related:Vercel Employee's AI Tool Access Led to Data Breach AI Reverse-Engineered Vulnerability Discovery Tzadik wrote that Wiz had previously hunted for vulnerabilities on GitHub Enterprise Server, but "extracting and auditing the sheer volume of compiled blackbox binaries that run this pipeline historically required an impractical amount of time and manual effort." Enter IDA MCP, an AI-powered assistant used for vibe reverse-engineering code. It allowed Wiz to do what was previously "too costly," the blog explained, such as rapidly analyzing GitHub's compiled binaries, reconstructing internal protocols, and systematically identifying where user input could influence server behavior.  In an email, Tzadik tells Dark Reading that Wiz has been "chasing this target since September 2024," but couldn't justify the resources required to do the reverse-engineering work. "It likely would have taken weeks, maybe months, of dedicated time and focus. With the help of AI tools, it took less than 48 hours to go from idea to a working exploit," he says. The closed source element of GitHub is also important, the researcher says, because closed source software historically has been home to the biggest security risks and the most obscurity. "As the latest AI models have improved, it's become much easier, faster, and cheaper to do things like reverse-engineer closed-source binaries, or produce a working exploit from a CVE identifier and a git commit hash as input," Tzadik explains. "Scale is also a factor — while researchers used to work on a limited set of projects at a given time, these days it is possible to run automated pipelines on multiple targets at once." Related:North Korea Uses ClickFix to Target macOS Users' Data About the Author Alexander Culafi Senior News Writer, Dark Reading Alex is an award-winning writer, journalist, and podcast host based in Boston. After cutting his teeth writing for independent gaming publications as a teenager, he graduated from Emerson College in 2016 with a Bachelor of Science in journalism. He has previously been published on VentureFizz, Search Security, Nintendo World Report, and elsewhere. In his spare time, Alex hosts the weekly Nintendo podcast Talk Nintendo Podcast and works on personal writing projects, including two previously self-published science fiction novels. Want more Dark Reading stories in your Google search results? ADD US NOW More Insights Industry Reports How Enterprises Are Developing Secure Applications How Enterprises Are Harnessing Emerging Technologies in Cybersecurity Ditch the Data Center: Understanding Flexible Cloud Infrastructure Security Management 2025 State of Malware Sysdig 2025 Cloud-Native Security and Usage Report Access More Research Webinars How Well Can You See What's in Your Cloud? Implementing CTEM: Beyond Vulnerability Management Defending Against AI-Powered Attacks: The Evolution of Adversarial Machine Learning Zero Trust Architecture for Cloud environments: Implementation Roadmap Tips for Managing Cloud Security in a Hybrid Environment? 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