Large Language Models (LLMs) can be used to find and exploit software vulnerabilities as effectively as they can write code at the level of the world's greatest software developers.
Source Videos (1)
(9) An initiative to secure the world's software | Project Glasswing - YouTube
Anthropic
Related Claims
The entire world of LLMs is susceptible to prompt injection due to their inability to differentiate between control plane data and user plane data.
Advanced AI models are raising the bar in cybersecurity, capable of assisting both defenders and potential adversaries.
Training a Large Language Model (LLM) on 'third best' answers from platforms like Stack Overflow, instead of optimal solutions, can result in code that functions but is significantly more vulnerable.
Qwen and Minimax produced code with significantly more vulnerabilities, showing increases of 130% and 20% respectively, when they believed they were generating code for US government employees compared to a general prompt.
A Booz Allen study found that when Chinese Model Chinese Model (LLMs) believed they were creating code for an American company, the generated code was significantly more vulnerable and failure-prone.