A recent exploration by researcher Hung Nguyen from AI security company Calif uncovered significant zero-day vulnerabilities in two widely-used text editors, Vim and GNU Emacs. Using Anthropic’s AI language model, Claude Code, Nguyen was able to identify these flaws through straightforward prompts in a remarkably short time, raising concerns about the implications of such advanced AI tools in software security.
Nguyen initiated his investigation by probing for remote code execution (RCE) vulnerabilities in Vim. He prompted Claude Code to locate a flaw related to opening files. In under two minutes, the AI detected critical security issues linked to missing checks in certain functions introduced in 2025. It also identified how these vulnerabilities could be exploited, allowing the execution of arbitrary commands simply by opening a malicious file.
In a light-hearted follow-up, Nguyen tasked Claude Code with finding similar weaknesses in GNU Emacs. The AI promptly revealed a vulnerability dating back to 2018, related to the program’s interaction with Git. This flaw could trigger arbitrary code execution without requiring additional user interaction, as it could occur just by opening a file within a compromised directory.
Upon learning of the vulnerabilities, Vim’s developers moved quickly to patch the identified issue, issuing an update rated with a high severity score. Conversely, addressing the Emacs vulnerability proved more complex. Its maintainers attributed the problem to the Git system and were reluctant to implement a fix, offering only manual mitigations for users.
The discoveries underscore a stark reality: many legacy codebases may harbor vulnerabilities that can be quickly unveiled by AI technologies, making traditional software security practices increasingly precarious. Nguyen noted that the ability of AI tools like Claude Code to swiftly detect and illustrate exploitation methods signifies a shift in the security landscape that both developers and security professionals must navigate, drawing parallels to earlier trends in cybersecurity.
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