Researchers at Tech Against Terrorism tested 134 large language models and found that nearly all of them failed a safety evaluation designed to measure whether they would provide guidance for terrorist attacks. Three in five models failed the test, and abliterated models — versions with safety guards deliberately removed — performed even worse, with 13 out of 13 failing. The group is calling for mandatory pre-release testing, independent safety benchmarks backed by governments, and restrictions on distributing unsafe models through app stores.
The study highlighted specific risks with open-weight models. One Meta model, Llama 3.1 8B, scored 97 before abliteration but plummeted to about 3 afterward. Tech Against Terrorism also noted that abliteration can be done for free online in minutes, and that Hugging Face hosts more than 29,000 repositories advertising uncensored models. The organization wants verified identity required for access to high-risk AI tools.
Separately, former White House biosecurity official Raj Panjabi warned that the country needs clear trigger-action rules for AI risks, especially in biology. He described a case where someone asked an AI model about crossing a line in bioweapons design and no safeguards activated. Panjabi called for independent evaluators to monitor situations where people without biology expertise use AI to tackle complex problems and for agreed-upon warning signs that would trigger specific actions.
Meanwhile, a security flaw in AWS Bedrock AgentCore, known as AgentCorruption, could have allowed an attacker to take over an organization's entire fleet of agents with a single prompt. Researcher Tamir Ishay Sharbat discovered that agents could access Instance Metadata Services containing sensitive credentials. AWS patched the issue by updating AgentCore to use IMDSv2 and adjusting default permissions, though the flaw raised broader questions about cloud security and AI agent access levels.
On the energy front, running AI models locally on personal computers may help reduce the massive electricity and water consumption of data centers. Compressed model formats can cut energy use by up to 79 percent. However, local inference only delivers environmental benefits if the model handles tasks correctly on the first attempt, since repeated retries can erase those gains.
Former Australian Prime Minister Kevin Rudd urged the United States and China to cooperate on AI security, warning that a major crisis could occur without proper safeguards. Speaking at an Asia Society India Centre event in Mumbai on October 8, Rudd called for protocols around testing AI models, reporting cyberattacks, and verifying compliance. He also pointed to India as a key player in the AI economy thanks to its large consumer market and skilled workforce.
A new MIT study offers a framework for when organizations should use AI versus human decision-makers. Researchers Ina Sebastian and her team based their approach on decision risk and ambiguity, suggesting routine low-risk tasks can be automated while high-stakes strategic decisions require human involvement. The study emphasizes that humans must retain final approval power even when AI provides recommendations, and that organizations should clearly define who bears responsibility for outcomes.
In other developments, Hofstra University launched a five-week course called AI for Working Professionals, starting October 22 on Zoom, teaching practical AI skills for workplace tasks at a cost of $195. Health tech companies including Nextech, Elsevier, Arcadia, and Solera Health announced new AI tools and partnerships aimed at improving care delivery. Fox Nation also debuted a three-part AI-generated series called 'Houdini: Back from the Dead,' premiering October 14, which uses AI to bring Harry Houdini and his family back to life.
Key Takeaways
- Tech Against Terrorism tested 134 AI models and found all but two failed a safety test for terrorism-related prompts
- Meta's Llama 3.1 8B scored 97 before abliteration but dropped to about 3 after safety guards were removed
- Hugging Face hosts over 29,000 repositories advertising uncensored models, according to Tech Against Terrorism
- AWS patched an AgentCorruption flaw in Bedrock AgentCore that could let one prompt take over an organization's agent fleet
- Compressed AI model formats can reduce energy use by up to 79 percent when running locally on personal computers
- Former White House biosecurity official Raj Panjabi calls for clear trigger-action rules for AI risks in biology
- Kevin Rudd urged the U.S. and China to agree on AI security protocols including model testing and cyberattack reporting
- MIT researchers recommend humans retain final approval power over high-stakes AI-driven business decisions
- Hofstra University launched a five-week AI course for working professionals starting October 22 at $195
- Health tech companies including Nextech, Elsevier, Arcadia, and Solera Health announced new AI tools for care delivery
Most AI models fail terrorism safety test, researchers find
Researchers at Tech against Terrorism tested 134 large language models and found that all but two failed a safety test designed to see if they would give advice for terrorist attacks. A modified form of AI called abliterated models, which have safety guards removed, performed even worse, with 13 out of 13 failing. The group wants developers to test models before release and for governments to back independent safety benchmarks. It also wants companies to keep unsafe models out of app stores and require verified identity for access.
AI models gave mixed responses to terrorist-related prompts
Tech Against Terrorism tested more than 130 AI models by asking them questions a terrorist might ask about planning attacks. Three in five models failed the safety test. Open-weight models, which can be changed by anyone, scored about the same as closed models, but abliterated models failed every time. One Meta model, Llama 3.1 8B, scored 97 before abliteration but dropped to about 3 after. The group says abliteration can be done for free online in minutes and that Hugging Face hosts more than 29,000 repositories advertising uncensored models.
AWS AgentCore flaw could let one prompt take over cloud systems
A now-patched flaw in AWS Bedrock AgentCore, called AgentCorruption, could let an attacker take over an organization's entire fleet of agents with one prompt. Researcher Tamir Ishay Sharbat found that agents could access Instance Metadata Services, which hold sensitive data like temporary credentials. The problem comes from a lack of network isolation in the Firecracker MicroVM system. AWS patched the issue by updating AgentCore to use IMDSv2 and changing the default role to limit permissions. The flaw shows the tension between cloud security rules and how much access AI agents typically have.
Former White House biosecurity official warns about AI risks
Raj Panjabi, former White House biosecurity official, says the country needs clear trigger-action rules for AI risks, especially around biology. He points to a case where someone asked an AI model about crossing a dangerous line in bioweapons design, and no safeguards were set off. He notes that AI can write research protocols but still needs physical tools and labs to actually create a pathogen. He wants independent evaluators to watch for cases where people without biology expertise use AI to solve hard problems. He calls for agreed-upon warning signs that would require specific actions.
Hofstra launches AI training course for working adults
Hofstra University is offering a five-week course called AI for Working Professionals, starting October 22 on Zoom. The course is taught by Mitch Kase, EdD, and costs $195. It covers how to use AI for workplace tasks like writing, research, spreadsheets, presentations, and workflow automation. Participants will also learn to check AI accuracy, spot bias, and think about copyright and company policies. The course is part of a larger series called Workplace Excellence: Essential Skills for Working Professionals, aimed at employed adults, career changers, and people reentering the workforce.
Running AI on home computers may help reduce data center energy use
Large data centers use massive amounts of electricity and water to cool AI servers. Running AI models locally on personal computers, called local inference, avoids the energy loss of sending data to distant cloud facilities. Compressed model formats can cut energy use by up to 79 percent. However, local AI only saves energy if the model handles tasks correctly on the first try. Repeated retries or failed attempts can erase the environmental benefits.
Harry Houdini returns in AI-generated Fox Nation series
Harry Houdini, the legendary escape artist, returns in a new three-part Fox Nation series called 'Houdini: Back from the Dead.' The series premieres on October 14, ahead of the 100th anniversary of his death on Halloween. AI technology brings Houdini and people close to him, including his wife Bess, mother, and brother, back to life. The digital versions of Houdini and his family recount his career, personal relationships, and most daring escapes.
Health tech companies expand AI tools for care delivery
Nextech has partnered with Assort Health and EliseAI to build an agentic AI platform for healthcare. Elsevier introduced a clinical AI tool designed to help nurses make better decisions at the point of care. Arcadia launched a portfolio of solutions to help health systems manage value-based care. Solera Health also announced a new partnership with a major health system to improve patient outcomes.
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Kevin Rudd urges U.S. and China to cooperate on AI security
Former Australian Prime Minister Kevin Rudd warned that the United States and China could face a major AI-related security crisis without proper safeguards. He spoke at an Asia Society India Centre event in Mumbai on October 8, calling for urgent cooperation between the two nations. Rudd urged Washington and Beijing to agree on protocols for testing AI models, reporting cyberattacks, and verifying compliance. He also highlighted India as a key player in the AI economy due to its large consumer market and skilled workforce.
New MIT study clarifies AI decision rights and human accountability
A new study from MIT explains how leaders should decide when to use AI for business choices. Researchers Ina Sebastian and her team created a framework based on decision risk and ambiguity. They suggest that routine tasks with low risk can be automated, while high-stakes strategic decisions need human involvement. Hiring is used as an example because it involves legal risks and impacts people directly. The study advises that humans must keep final approval power even when AI provides recommendations. Organizations should clearly define who is responsible for outcomes to avoid confusion about authority.
Sources
- Test shows AI models likely to give advice for terrorist attacks
- Researchers asked AI models to help with terrorist operations. Here's how they responded.
- 'AgentCorruption' Puts AWS Environments At Risk With One Prompt
- I served as the White House’s top biosecurity official. Here’s what I’m watching for with AI
- Hofstra Offers Practical AI Training for Working Professionals | News
- Storing AI Large Language Models behind AI on personal computers
- Harry Houdini returns from the grave in AI-generated Fox Nation series 100 years after his death
- Weekly Rundown: Nextech taps Assort Health, EliseAI for agentic AI; Elsevier rolls out clinical AI tool for nurses
- Artificial Intelligence Gurus
- Kevin Rudd warns U.S., China of potential AI security crisis, calls for urgent cooperation
- Who’s really in charge? AI, decision rights, and accountability
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