“The issue is in the age of LLMs, these reports appear at first-glance to be potentially legitimate and thus require time to refute,” Larson explained, highlighting how this phenomenon strains already limited resources in the open source security ecosystem. Seth Larson, the Python Software Foundation’s Security Developer-in-Residence, confirmed that open source maintainers’ time is increasingly being consumed by reviewing such AI-generated vulnerability reports. Socket.dev researchers have identified this trend as particularly problematic for open-source projects and under-resourced organizations that lack the internal expertise to properly evaluate technical security reports. These AI-generated reports pose a particular threat because they often appear legitimate at first glance, especially to organizations without dedicated security experts. Bug bounty programs, once celebrated for incentivizing independent researchers to report real-world vulnerabilities, are now facing a significant challenge from AI-generated fake vulnerability reports. The reports typically include technical jargon, references to security concepts, and even suggested patches-all designed to pass initial triage processes. Many organizations find themselves in a difficult position: investing time and resources to thoroughly investigate each report or simply paying bounties to avoid potential security risks and negative publicity. The phenomenon represents a growing trend where malicious actors leverage large language models (LLMs) to generate technical-sounding but entirely fictitious security reports. Security researcher Harry Sintonen noted that curl, being a highly technical open source project with deep expertise, immediately recognized the deception. Cyber Security News is a Dedicated News Platform For Cyber News, Cyber Attack News, Hacking News & Vulnerability Analysis. With years of experience under his belt in Cyber Security, he is covering Cyber Security News, technology and other news.
This Cyber News was published on cybersecuritynews.com. Publication date: Thu, 08 May 2025 05:49:59 +0000