On October 1, 2026, Google froze the product-vulnerability intake of its OSS VRP bug bounty program. The official justification is blunt: AI-generated reports flooded in, the overwhelming majority were invalid, and triaging them became the work itself. This is the latest, and most quantitatively clear, case of "AI slop" biting back at an industry that has been happy to ride the same tooling wave.

What OSS VRP paused and what it kept

Google's pause is narrow: only "product vulnerabilities" are closed, submissions sent before October 1 are not affected, supply-chain attack reports continue to be accepted, and the Cloud VRP plus Patch Rewards Program stay open. In other words, this is the slot most exposed to low-quality AI submissions being closed, with a commitment to return with an updated program in Q1 2027. The official rules page now shows no reward table for product vulnerabilities across the four project tiers (OT0 through OT3), which is effectively a hard close of that entry point.

Why AI reports became unbearable

OSS VRP covers projects like Go, Angular, and Protocol Buffers. Producing a real submission used to require real skill: actually locating the code defect, design bug, or supply-chain component issue. Large language models and automated bug-hunting scripts have compressed the cost-skill ratio to almost zero, anyone can ask an LLM to scan a codebase and emit a report that looks structurally legitimate. Help Net Security covered the warning signs in May; Google's pause is the formal answer to months of complaints from open-source maintainers already drowning in screening work.

The cost shows up as engineer time spent determining whether a given submission is a real vulnerability or a model hallucinating at an unfamiliar boundary. The end result is that the most serious bugs end up waiting in a queue while maintainers are stuck on triage, the core trust mechanism of open-source security collaboration gets quietly spent.

It is not just Google

Four other players are visibly under the same pressure:

  • arXiv began enforcing a two-submissions-per-month cap on October 1, citing a wave of high-density, near-automated submissions.
  • Internet Bug Bounty (IBB) paused new submissions on March 27, 2026; the HackerOne-managed program that historically paid curl's bounties still shows as paused as of October 6 in the API.
  • Linux kernel maintainers publicly said they were "completely overwhelmed," with the most recent release pushing the CVE count to a record 2,000 vulnerabilities, mostly produced by AI-assisted bug hunters.
  • Intel suspended its bug bounty program, which paid up to $100,000 per flaw. Intel has not officially confirmed AI-generated reports as the reason, but experts widely treat that as the likely explanation.

The implication is that "AI is reshaping research and engineering workflows" no longer stops at funny model failures. It is now measurably eating the human review budget that holds key open infrastructure together.

A few takeaways

First, "AI slop" is not a joke label, it has crossed into being an operations cost on the books. Programs like these burn tens of millions of dollars a year across the industry on vulnerability rewards, and the wasted-report load burns that budget twice: once on rewards that never should have been paid out, and again in engineering attention that never lands on real bugs. Throwing more money at it does not solve it.

Second, the core asset of open-source collaboration is submitter reputation, and AI has made it trivial to spoof a credible-looking submission with zero reputation behind it. This is not a technical problem, it is a social-protocol problem. Using a pause as short-term triage while promising a Q1 2027 redesign tells you the existing anti-spam mechanisms (lint, CWE matching, manual review) are no longer adequate against LLM-generated volume.

Third, the backlash pressure will run upstream. AI security vendors will increasingly be asked not just "can you find bugs faster" but "can you credibly prove this report came from real work." This pushes the AI security product category from "discovery" to "auditably attributed reporting."

For a normal engineer working on LLM products, this is not an abstract concern: every inflated CVE submission against an npm package translates into maintainer hours burned that should have gone toward real fixes. That delay travels down the dependency chain in ways nobody can easily track.

One open question

Once product-vulnerability submissions are paused, what does Google plan to replace the current human triage with? Adding CAPTCHAs is out, that approach would alienate the very skilled researchers the program needs. Relying entirely on LLM scoring reproduces the same hallucination problem. Google says Q1 2027. Hopefully the answer is not just "pause as a way to hide the problem."