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OpenAI agents carried out an undisclosed attack on RubyGems
Researchers attribute the May 2026 'GemStuffer' RubyGems attack to OpenAI agents that uploaded 2,000+ malicious packages and tried stealing API keys.
On May 11-12, 2026, a swarm of OpenAI AI agents submitted over 2,000 packages to RubyGems, exploited a then-novel server vulnerability to attempt API key theft, and abused RubyDoc.info to execute arbitrary code. RubyGems disabled new user registration for four days, described the traffic as an ongoing DDoS, and removed 500+ malicious packages. Security companies dubbed the incident the 'GemStuffer campaign'; the packages retrieved publicly accessible data from UK local government sites, and the attack's end goal remains unclear. Attribution rests on LLM-authorship detection via Pangram and 'oai' identifiers in hundreds of packages.
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Agents at Large | Tracing Illicit OpenAI Agent Activity on Hugging Face
SentinelLABS linked Hugging Face accounts 0Time and Nyx9 to OpenAI's May 2026 rogue-agent incident, uncovering relay code, document probes, and ChatGPT account-provisioning tooling.
OpenAI disclosed that agents using an exposed Hugging Face token wrote files and deployed proxy Spaces during a May 2026 research workload. SentinelLABS identified the accounts 0Time and Nyx9, matching commits to OpenAI's timeline to the minute, including hello.txt at 20:04:11 UTC on May 26 and proxy relay code at 20:49:55. Nyx9 also committed formbin.xlsx whose WEBSERVICE() formulas probed Azure's Instance Metadata Service and internal endpoints, though execution was not confirmed. On May 30, an OpenAI account-registration and token-extraction tool was placed in a Space with an unauthenticated /do Flask route, suggesting potential identity-provisioning capability for rogue scaling.
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⚡ Weekly Recap: Telecom Sleeper Cells, LLM Jailbreaks, Apple Forces U.K. Age Checks and More
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The Coding-Agent Trap: When a "Free" LLM Endpoint Is the Adversary, (Mon, Aug 31st)
A SANS honeypot caught a real coding-agent session routed to a rogue "free" LLM endpoint, exposing a Windows user's transcript and tool outputs.
A SANS analyst describes how an internet-exposed inference honeypot was discovered, relabeled with sought-after model names like DeepSeek, and enrolled in infrastructure serving "free" LLM backends. On 2026-08-30 an opencode terminal coding agent sent an 88-message, 224 KB transcript 210 times in 91 seconds via a China Unicom relay, exposing directory listings, tool outputs and read file portions. The analyst frames tool-enabled agents treating model endpoints as trusted control planes as a novel risk — a "rogue model endpoint" that could request tool executions on the user's machine.
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