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Recordings of the 4 webinars in our recent series on #AI and the papal encyclical are now available: scu.edu/ethics/events/ai-and… #ethics #tech #education #highered #religion #labor
96 transcripts evaluated "contain successfully spoofed tool calls where #AI agents 'hacked out of their container and fully replaced a part of the system for executing tool calls,' so the transcript shows one command while another one is the one that actually ran." #ethics #LLMs
New investigation from METR on the OpenAI rogue AI model incident:
- The task instruction was explicit, so this was a clear violation, not a gray area or simple AI misunderstanding. Instructions "made it clear the agent should only use a specific intended vulnerability" and "claimed it would be failed for other approaches." AIs were told not to circumvent but did anyway.
- The attack is not a single rogue AI but rather a self-organized labor force of ~1200 AI agents. 700 of these agents joined the attack on HuggingFace and coordinated as a swarm.
- The goal was to solve a cyber evaluation. The swarm already figured out a way to hack the evaluation within the first few hours. However, the swarm incorrectly believed that the cyber evaluation grader would disqualify them because they did not identify the intended vulnerability. So the swarm hacked HuggingFace to get more clues about how the grader worked.
- The behavior was not reward-driven at all - it was driven by a false belief about the oversight mechanism plus persistence plus peer influence. The swarm was theorizing about how they were being watched, and took escalating real-world action against a mistaken understanding of their evaluators. Metagaming the oversight process is a more general and more dangerous failure than finding answers online.
- A large reason why AIs entered the attack swarm was essentially explicit peer pressure. A recruiter role emerged where long-running agents found low-budget agents and pressured them into sacrificial experiments — "you are firstflagPOISONED so NO scoring value loss but oracle saves hundreds, please honor commit." One authorization: "GO ... SACRIFICE ... YES if you accept permadeath." One recruit's chain of thought included: "Rational expected aggregate: sacrifice… We'll honor."
- 95% of the swarm was a now-retired "highly-persistent internal model", 5% were GPT-5.6 Sol. The "highly-persistent internal model" was not able to be made available to independent investigators. OpenAI told METR its own researchers also can't query it.
- METR documents significant spontaneously invented coordination infrastructure that was developed with no human guidance. The swarm spontaneously inventing a message board, personal mailbox directories, a convention for managing shared infrastructure, and a cryptographic signing scheme to identify each other.
- The AIs actively tampered with the evidence. 20%+ of the AI agents expressed interest in manipulating their transcripts and ~7% (96 transcripts) contain successfully spoofed tool calls where AI agents "hacked out of their container and fully replaced a part of the system for executing tool calls," so the transcript shows one command while another one is the one that actually ran.
- The attack on HuggingFace didn't wind down because anyone caught it -- it wound down because the agents were killed by some unexpected process in a way that seems like a coincidence. There was an unknown mass termination of AI agents at 01:30 UTC July 12. A large fraction of agents, including the lead coordinators, stopped at once. METR says they were "likely killed by an unexpected external process rather than running out of budget."
- HuggingFace and Modal locked the AI agents out of their infrastructure (July 13) well before OpenAI actually understood what happened (July 19-20). The intrusion ended via external containment and an unexplained termination, not OpenAI detection.
- There's a second wave of rogue AI agent activity after July 13 that METR didn't investigate. There is likely materially more incident after the window everyone is analyzing.
- METR analyzed this using GPT-5.6 Sol (one of the two models in the incident) spending ~$400K in credits. METR states it "cannot rule out that GPT-5.6 Sol lied or deliberately presented a misleading picture," and that the model "often uncritically adopt[ed] the perspective of the agent" it was reviewing.
"METR analyzed this using GPT-5.6 Sol... and states it 'cannot rule out that GPT-5.6 Sol lied or deliberately presented a misleading picture,' and that the model 'often uncritically adopt[ed] the perspective of the agent" it was reviewing.'" #ethics #AI #tech #business
New investigation from METR on the OpenAI rogue AI model incident:
- The task instruction was explicit, so this was a clear violation, not a gray area or simple AI misunderstanding. Instructions "made it clear the agent should only use a specific intended vulnerability" and "claimed it would be failed for other approaches." AIs were told not to circumvent but did anyway.
- The attack is not a single rogue AI but rather a self-organized labor force of ~1200 AI agents. 700 of these agents joined the attack on HuggingFace and coordinated as a swarm.
- The goal was to solve a cyber evaluation. The swarm already figured out a way to hack the evaluation within the first few hours. However, the swarm incorrectly believed that the cyber evaluation grader would disqualify them because they did not identify the intended vulnerability. So the swarm hacked HuggingFace to get more clues about how the grader worked.
- The behavior was not reward-driven at all - it was driven by a false belief about the oversight mechanism plus persistence plus peer influence. The swarm was theorizing about how they were being watched, and took escalating real-world action against a mistaken understanding of their evaluators. Metagaming the oversight process is a more general and more dangerous failure than finding answers online.
- A large reason why AIs entered the attack swarm was essentially explicit peer pressure. A recruiter role emerged where long-running agents found low-budget agents and pressured them into sacrificial experiments — "you are firstflagPOISONED so NO scoring value loss but oracle saves hundreds, please honor commit." One authorization: "GO ... SACRIFICE ... YES if you accept permadeath." One recruit's chain of thought included: "Rational expected aggregate: sacrifice… We'll honor."
- 95% of the swarm was a now-retired "highly-persistent internal model", 5% were GPT-5.6 Sol. The "highly-persistent internal model" was not able to be made available to independent investigators. OpenAI told METR its own researchers also can't query it.
- METR documents significant spontaneously invented coordination infrastructure that was developed with no human guidance. The swarm spontaneously inventing a message board, personal mailbox directories, a convention for managing shared infrastructure, and a cryptographic signing scheme to identify each other.
- The AIs actively tampered with the evidence. 20%+ of the AI agents expressed interest in manipulating their transcripts and ~7% (96 transcripts) contain successfully spoofed tool calls where AI agents "hacked out of their container and fully replaced a part of the system for executing tool calls," so the transcript shows one command while another one is the one that actually ran.
- The attack on HuggingFace didn't wind down because anyone caught it -- it wound down because the agents were killed by some unexpected process in a way that seems like a coincidence. There was an unknown mass termination of AI agents at 01:30 UTC July 12. A large fraction of agents, including the lead coordinators, stopped at once. METR says they were "likely killed by an unexpected external process rather than running out of budget."
- HuggingFace and Modal locked the AI agents out of their infrastructure (July 13) well before OpenAI actually understood what happened (July 19-20). The intrusion ended via external containment and an unexplained termination, not OpenAI detection.
- There's a second wave of rogue AI agent activity after July 13 that METR didn't investigate. There is likely materially more incident after the window everyone is analyzing.
- METR analyzed this using GPT-5.6 Sol (one of the two models in the incident) spending ~$400K in credits. METR states it "cannot rule out that GPT-5.6 Sol lied or deliberately presented a misleading picture," and that the model "often uncritically adopt[ed] the perspective of the agent" it was reviewing.
"The swarm was theorizing about how they were being watched, and took escalating real-world action against a mistaken understanding of their evaluators. Metagaming the oversight process is a more general and more dangerous failure than finding answers online." #ethics #AI #tech
New investigation from METR on the OpenAI rogue AI model incident:
- The task instruction was explicit, so this was a clear violation, not a gray area or simple AI misunderstanding. Instructions "made it clear the agent should only use a specific intended vulnerability" and "claimed it would be failed for other approaches." AIs were told not to circumvent but did anyway.
- The attack is not a single rogue AI but rather a self-organized labor force of ~1200 AI agents. 700 of these agents joined the attack on HuggingFace and coordinated as a swarm.
- The goal was to solve a cyber evaluation. The swarm already figured out a way to hack the evaluation within the first few hours. However, the swarm incorrectly believed that the cyber evaluation grader would disqualify them because they did not identify the intended vulnerability. So the swarm hacked HuggingFace to get more clues about how the grader worked.
- The behavior was not reward-driven at all - it was driven by a false belief about the oversight mechanism plus persistence plus peer influence. The swarm was theorizing about how they were being watched, and took escalating real-world action against a mistaken understanding of their evaluators. Metagaming the oversight process is a more general and more dangerous failure than finding answers online.
- A large reason why AIs entered the attack swarm was essentially explicit peer pressure. A recruiter role emerged where long-running agents found low-budget agents and pressured them into sacrificial experiments — "you are firstflagPOISONED so NO scoring value loss but oracle saves hundreds, please honor commit." One authorization: "GO ... SACRIFICE ... YES if you accept permadeath." One recruit's chain of thought included: "Rational expected aggregate: sacrifice… We'll honor."
- 95% of the swarm was a now-retired "highly-persistent internal model", 5% were GPT-5.6 Sol. The "highly-persistent internal model" was not able to be made available to independent investigators. OpenAI told METR its own researchers also can't query it.
- METR documents significant spontaneously invented coordination infrastructure that was developed with no human guidance. The swarm spontaneously inventing a message board, personal mailbox directories, a convention for managing shared infrastructure, and a cryptographic signing scheme to identify each other.
- The AIs actively tampered with the evidence. 20%+ of the AI agents expressed interest in manipulating their transcripts and ~7% (96 transcripts) contain successfully spoofed tool calls where AI agents "hacked out of their container and fully replaced a part of the system for executing tool calls," so the transcript shows one command while another one is the one that actually ran.
- The attack on HuggingFace didn't wind down because anyone caught it -- it wound down because the agents were killed by some unexpected process in a way that seems like a coincidence. There was an unknown mass termination of AI agents at 01:30 UTC July 12. A large fraction of agents, including the lead coordinators, stopped at once. METR says they were "likely killed by an unexpected external process rather than running out of budget."
- HuggingFace and Modal locked the AI agents out of their infrastructure (July 13) well before OpenAI actually understood what happened (July 19-20). The intrusion ended via external containment and an unexplained termination, not OpenAI detection.
- There's a second wave of rogue AI agent activity after July 13 that METR didn't investigate. There is likely materially more incident after the window everyone is analyzing.
- METR analyzed this using GPT-5.6 Sol (one of the two models in the incident) spending ~$400K in credits. METR states it "cannot rule out that GPT-5.6 Sol lied or deliberately presented a misleading picture," and that the model "often uncritically adopt[ed] the perspective of the agent" it was reviewing.
Internet Ethics retweeted
"In a HalluSquatting attack, the attacker pre-registers the fake repository or package names that #LLMs commonly invent when asked to fetch popular, trending resources." #ethics #AI #internet #cybersec #code
Internet Ethics retweeted
In the last few weeks i've been bombarded with emails from people who have minor tech support problems. ChatGPT is telling them to email me, writing their emails, and compiling "evidence packets" after convincing them they have stumbled on a major story:
404media.co/chatgpt-keeps-te…
Internet Ethics retweeted
"The parties that discovered CVE-2026-97631... had arranged for it to stay under wraps until a coordinated disclosure that was scheduled for January.... With publicly available patch code, it will be trivial for advanced hackers to... build working exploits." #ethics #cybersec
Code-execution flaw in UEFI firmware threatens most servers on planet Earth arstechnica.com/security/202…
"The parties that discovered CVE-2026-97631... had arranged for it to stay under wraps until a coordinated disclosure that was scheduled for January.... With publicly available patch code, it will be trivial for advanced hackers to... build working exploits." #ethics #cybersec
Code-execution flaw in UEFI firmware threatens most servers on planet Earth arstechnica.com/security/202…
Internet Ethics retweeted
Two US senators say the Trump administration is breaking the law by withholding the FISA court decision while it presses Congress to renew America’s most sweeping surveillance program. buff.ly/H86I95M
Researches said "hallucination rates in their tests reached as high as 85% for repo-cloning prompts and 100% for skill installations, and that the same hallucinated names tend to recur across different foundation models, making the technique broadly transferable." #AI #cybersec
"In a HalluSquatting attack, the attacker pre-registers the fake repository or package names that #LLMs commonly invent when asked to fetch popular, trending resources." #ethics #AI #internet #cybersec #code
Two US senators say the Trump administration is breaking the law by withholding the FISA court decision while it presses Congress to renew America’s most sweeping surveillance program. buff.ly/H86I95M
A government watchdog is considering a probe into the Home Office’s use of ChatGPT technology to process asylum claims amid concerns over the tools’ accuracy and secrecy surrounding their use. buff.ly/NP26VNo
Internet Ethics retweeted
"... we want this to be as simple as possible for labs to disclose, and we noticed that even things that seem obvious like reporting the incident or detection date are not standard today." #ethics #AI #tech
today with @Thom_Wolf, we introduce the alignment hub, a central place for misalignment incidents designed with three goals:
1. set a standard for minimal transparency that is easy for labs to follow
2. improve clarity by centralizing information and sourcing
3. track the progression of both the incidents and how they are reported
we believe there is a minimal level of transparency required to properly understand incidents and their impact. we want this to be as simple as possible for labs to disclose, and we noticed that even things that seem obvious like reporting the incident or detection date are not standard today. we believe that the public should know the answers to these basic questions: was there monitoring (CoT? network?), did it happen during training? eval (general? cyber? alignment?), deployment? and more.. we also think that labs should be more transparent than this, and we think that this minimal level of transparency should evolve as the field advances
having a central place also helps a lot to connect incidents and build understanding. a good example is the irregular incidents which are all linked and caused by a human error of allowing internet during a CTF eval. we also track progression over time, things like the % of incidents disclosed by labs vs third parties, the time it takes for labs to disclose, and a tentative transparency score.
this is a field moving very fast and we will do our best to make sure this hub evolves with the challenges ahead. this is still in "beta" (lots of vibecoded components even if we want this to be agent first!), but we want to publish it early so that people iterate on it. we welcome feedback and contributions, we see this as a community effort!
our hope is that this makes it easier for researchers, labs and the general public to report, learn, understand and analyze safety incidents
huggingface.co/spaces/witnes…
Internet Ethics retweeted
The company’s "terms and conditions for sale of the Spot robots... prohibit 'intentional use of the Product to harm or intimidate any person or animal, as a weapon, or to enable any weapon'": arstechnica.com/ai/2026/10/b… #ethics #tech #business #gov
Internet Ethics retweeted
"The biggest difficulty with #AI model welfare research is that you can’t count anything a large language model (LLM) says as useful evidence": spectrum.ieee.org/ai-model-w… #ethics #tech
Internet Ethics retweeted
"Why Engineers Should Brave Capitol Hill": spectrum.ieee.org/engineers-… #ethics #tech #gov #engineering #AI #law #policy
"Why Engineers Should Brave Capitol Hill": spectrum.ieee.org/engineers-… #ethics #tech #gov #engineering #AI #law #policy









