Multiple Llms
AI Agent Reliability Report
Failure Modes
Root Causes
Frequently Asked Questions
Is Multiple Llms reliable?
Based on 3 documented incidents, Multiple Llms has an average failure severity of 3.8/10. 0 incidents were rated critical and 0 were rated high severity. Common failure modes include hallucination.
What are the most common Multiple Llms failures?
The most frequently documented Multiple Llms failure modes are: hallucination (3 incidents). These failures range from low to high severity.
How many Multiple Llms AI failures have been documented?
StupidLLM has documented 3 Multiple Llms AI agent failures. Each incident is severity-scored on a 0-10 scale, verified against source evidence, and categorized by failure mode and root cause.
All Multiple Llms Incidents
Slopsquatting: LLMs hallucinate package names attackers pre-register (react-codeshift, unused-imports)
'Slopsquatting' is a supply-chain attack that weaponizes a systematic AI failure: coding agents confidently recommend packages that do not exist. Across 576,000 code samples genera
AI 'CVE slop' is drowning open-source maintainers: 60-80% of HackerOne submissions now invalid
Beyond curl, AI-generated 'CVE slop' is drowning the volunteers who secure open-source software. HackerOne now reports that 60-80% of vulnerability submissions across its platform
AI 'slop' vulnerability reports flooded curl until it killed its bug bounty
curl's founder Daniel Stenberg shut down the project's long-running HackerOne bug bounty at the end of January 2026 after being overwhelmed by AI-generated 'slop' — long, confident