PPhying中文
Curated security research, vulnerabilities, advisories and tools for practitioners.

Sloptimism is breaking any system built on human validation

bugcrowd.com | blog | #ai-security | #bug-bounty | #vulnerability-management | #open-source | #llm | #triage | #ai-slop | #sloptimism | #academia | #spam-control
📄 Raw .md⬇️ Download .md🔗 Original ↗

Summary

A 334% triage-queue spike traced to sloptimism — AI reports trusted over evidence. The same failure mode strains open source and academia, where faking is cheap but verifying is not.
Published
Collected

Related coverage

blog · bugcrowd.com
Bugcrowd policy changes to address “AI slop” submissions
Facing a 334% triage-queue spike from AI slop, Bugcrowd updates submission policy, rate controls, and detection to target farms training AI on live programs and novices submitting unverified findings.
blog · hackenproof.com
How We Built an Autonomous AI Security Triager: From LLM to 20,000+ Real Reports
AI made bug hunters sharper, and report volume doubled. How HackenProof built an autonomous AI triager that now handles 70% of submissions.
blog · netspi.com
Open Source Software – Is It the Death of Your Company?
Warns that companies often don't know which open source components their applications contain, covering license risks from permissive to copyleft and the security vulnerabilities buried in OSS.
research · bishopfox.com
Separating Signal from Slop: Triaging CVEs in the Age of AI Security Research
CVE disclosures are up 85% while exploitation barely moved. Bishop Fox breaks down four Nginx CVEs that looked critical but rarely affect real deployments.
blog · bugcrowd.com
The hidden cost of agentic pentesting
Bugcrowd finds agentic pentesting tools submit overwhelmingly low-signal reports on public bug bounty programs, while top findings still come from skilled humans; triage absorbs the hidden cost.
blog · bugcrowd.com
The AI slop era: Do most vulnerabilities actually matter?
A Bugcrowd panel on the 'AI slop' era: after filtering hallucinated reports, AI-assisted discovery still yields 10x more valid findings than teams can fix, so context must drive prioritization.
Back