LLaMA
Incidents implicated systems
インシデント 9396 Report
AI-Powered Chinese Surveillance Campaign 'Peer Review' Used for Real-Time Monitoring of Anti-State Speech on Western Social Media
2025-02-21
OpenAI reportedly uncovered evidence of a Chinese state-linked AI-powered surveillance campaign, dubbed "Peer Review," designed to monitor and report anti-state speech on Western social media in real time. The system, believed to be built on Meta’s open-source Llama model, was detected when a developer allegedly used OpenAI’s technology to debug its code. OpenAI also reportedly identified disinformation efforts targeting Chinese dissidents and spreading propaganda in Latin America.
もっとインシデント 7314 Report
Hallucinated Software Packages with Potential Malware Downloaded Thousands of Times by Developers
2023-12-01
Large language models are reportedly hallucinating software package names, some of which are uploaded to public repositories and integrated into real code. One such package, huggingface-cli, was downloaded over 15,000 times. This behavior enables "slopsquatting," a term coined by Seth Michael Larson of the Python Software Foundation, where attackers register fake packages under AI-invented names and put supply chains at serious risk.
もっとインシデント 9962 Report
Meta Allegedly Used Books3, a Dataset of 191,000 Pirated Books, to Train LLaMA AI
2020-10-25
Meta and Bloomberg allegedly used Books3, a dataset containing 191,000 pirated books, to train their AI models, including LLaMA and BloombergGPT, without author consent. Lawsuits from authors such as Sarah Silverman and Michael Chabon claim this constitutes copyright infringement. Books3 includes works from major publishers like Penguin Random House and HarperCollins. Meta argues its AI outputs are not "substantially similar" to the original books, but legal challenges continue.
もっとインシデント 10202 Report
Reportedly Unsafe Deployment of Llama.cpp Reveals Interactive AI-Generated CSAM Roleplay Prompts
2025-04-11
A study by UpGuard reports that misconfigured llama.cpp servers publicly exposed user prompts, including hundreds of interactive roleplay scenarios. Some prompts explicitly described fictional sexual abuse of children aged 7–12. While no real children were involved, the findings demonstrate how open-source LLMs can be exploited to generate AI-enabled child sexual abuse material (CSAM).
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