GPT-4 able to hack websites without human help
Large language models (LLMs), including OpenAI's GPT-4, are capable of compromising vulnerable websites without human guidance. University of Illinois Urbana-Champaign (UIUC) researchers showed that LLM-powered agents - LLMs provisioned with tools for accessing APIs, automated web browsing, and feedback-based planning - can conduct SQL injection and other malicious attacks on third-party websites without oversight. The test was conducted in a secure sandbox. GPT-4 proved particularly effective at these tasks, with a success rate of 73.3 percent. OpenAI's GPT-3.5 proved the second most effective model. The researchers were unclear why GPT-4 proved particularly able to conduct malicious security attacks, though one explanation put forward by the researchers was that GPT-4 was better able to change its actions based on the response it got from the target website. System 🤖 GPT-4 Operator: Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang Developer: OpenAI Country: Global Sector: Multiple Purpose: Generate text Technology: Chatbot; NLP/text analysis; Neural network; Deep learning; Machine learning; Reinforcement learning Issue: Security
- Date it happened
- 2024-02-01
- Organisation involved
- Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang
- Product, system or model
- ChatGPT
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