Vulnerability Disclosure in the Age of AI
New article: “Responsible Disclosure in the Age of AI: A Call for Urgent Action,” by Melissa Hathaway.
Abstract: Artificial intelligence is fundamentally reshaping the balance between vulnerability discovery and remediation. Frontier AI models are now capable of autonomously identifying exploitable software vulnerabilities at unprecedented speed and scale. This development exposes decades of accumulated technical debt created by a software industry that prioritized rapid deployment over secure-by-design engineering practices. Drawing on the evolution of software assurance, vulnerability disclosure frameworks, and U.S. cyber policy, this perspective argues that the current moment represents a strategic inflection point for governments, industry, and critical infrastructure operators. The author examines the growing tension between offensive and defensive equities in cyberspace, the emergence of AI-enabled vulnerability discovery capabilities in both the U.S. and China, and the increasing risks posed by unsupported legacy systems and AI-assisted code generation practices. Responsible disclosure can no longer remain a reactive or fragmented process, but must become a coordinated national and international resilience effort involving governments, software vendors, infrastructure operators, and emergency response organizations. The article concludes with an urgent call for accelerated remediation, large-scale patch management coordination, and sustained investment in automated vulnerability repair capabilities before adversaries exploit this rapidly narrowing window of opportunity.
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Clive Robinson • June 1, 2026 1:54 PM
@ ALL,
The first point of note,
Is something I’ve previously warned about.
Not just because of the nasties it hides, but more importantly the fact it makes AI Vulnerability finding look way more impressive than it actually is.
In short the veritable tsunami of “technical debt” has not broken over us because nobody has really been interested in “chasing it down” because there was no financial incentive to do so.
Now AI can find much of this technical debt quickly and currently at low cost…
Yes “the equation has changed”, which means a lot of stuff that should have been dealt with a couple of decades ago no has to be fixed
The result will be a very large initial work load, that will fairly quickly get reduced down to a much much lower rate if not trickle.
To much is currently being made about the “quantity of technical debt” some types of LLM systems are finding.
The thing is the AI systems are not really finding anything particularly new.. In effect they are finding lots and lots of “Known Knowns” that have been “ignored”, some “unknown, knowns” that are basically a small variation on “known knowns”.
These things just require a “clean-up”
What we really need and it’s something Current AI LLM and ML systems are not of much use for is finding the “unknown unknowns” and the more serious “unknown knowns”.
We are currently quite a way from these automated systems finding new instances in a class of known vulnerability type and more than “moon shot” distances on new unknown instances in new unknown classes.
We will have to wait for the “initial smoke to clear” before we can asses what type of combustion is causing it, and if it’s actually a problem. This is something that Current AI systems can’t really replace “experienced humans” with and it’s going to take us quite a while –if ever– before we can.