AI models can acquire backdoors from surprisingly few malicious documents
Scraping the open web for AI training data can have its drawbacks. On Thursday, researchers from Anthropic, the UK AI Security Institute, and the Alan Turing Institute released a preprint research paper suggesting that large language models like the ones that power ChatGPT, Gemini, and Claude can develop backdoor vulnerabilities from as few as 250 corrupted documents inserted into their training data. That means someone tucking certain documents away inside…