EFF: AI Makes Vulnerability Discovery Cheap, But Open-Source Infrastructure Maintainers Can't Keep Up With the Pace
Using the October 2026 PHP vulnerability incident as an example, the US Electronic Frontier Foundation (EFF) argues that frontier AI models have driven the cost of software vulnerability discovery to extremely low levels, while critical open-source projects remain maintained by a small number of unpaid volunteers. This asymmetry is placing internet infrastructure at systemic risk.
The US Electronic Frontier Foundation (EFF) has put forward a structural assessment: frontier AI models are fundamentally altering the cost balance between offense and defense in software security. In the past, discovering zero-day vulnerabilities in specific projects and developing exploits was considered expensive and scarce work requiring specialized knowledge; Google even dedicated an entire team to it. The EFF argues that the situation has now reversed—anyone with moderate technical skills and a few dollars to spend on accessing a frontier AI model can find vulnerabilities within minutes. The article cites a concrete example: recent vulnerabilities in PHP were discovered using a prompt to an AI model that literally said "find bad vulnerabilities in PHP."
The PHP incident itself is a typical case of this asymmetry. The EFF narrates the complete timeline: in 2024, an external security audit identified a potentially severe vulnerability in PHP, but maintainers could not agree on a fix, and more importantly, could not find a way to exploit it. Consequently, they deprioritized the fix to address more urgent security issues. In August 2026, security researchers using the latest models from OpenAI and Anthropic independently rediscovered this vulnerability and another one, and this time found ways to exploit them. The EFF points out that these vulnerabilities were severe enough to allow any creative hacker to take over any website running PHP, steal user data, deploy malware, monitor users, or launch denial-of-service attacks.