Hosted on MSN
Size doesn't matter: Just a small number of malicious files can corrupt LLMs of any size
Large language models (LLMs), which power sophisticated AI chatbots, are more vulnerable than previously thought. According to research by Anthropic, the UK AI Security Institute and the Alan Turing ...
Hosted on MSN
How many malicious docs does it take to poison an LLM? Far fewer than you might think, Anthropic warns
Just 250 corrupted files can make advanced AI models collapse instantly, Anthropic warns Tiny amounts of poisoned data can destabilize even billion-parameter AI systems A simple trigger phrase can ...
Contrary to long-held beliefs that attacking or contaminating large language models (LLMs) requires enormous volumes of malicious data, new research from AI startup Anthropic, conducted in ...
Vulnerabilities include significant shortcomings in the scanning of email attachments for malicious documents, potentially putting millions of users worldwide at risk The study, conducted by SquareX's ...
The MacroPack framework, initially designed for Red Team exercises, is being abused by threat actors to deploy malicious payloads, including Havoc, Brute Ratel, and PhatomCore. Security researchers at ...
Perhaps even more than 'poisoning' this seems like it could be interesting for 'watermarking'. At least as best as I can tell as a legal layman, a number of the AI copyright cases seem to follow the ...
Earlier this year, Kaspersky’s Global Research and Analysis Team (GReAT) identified a campaign by the ‘Mysterious Elephant’ APT. The group mainly targets government entities as well as foreign affairs ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback