LLMs show potential to automate app vulnerability exploitation

A security researcher spent $1,500 to test if Large Language Models (LLMs) could exploit vulnerabilities in a specially designed application. The experiment demonstrated that LLMs can replicate human attacker techniques, identifying and simulating exploits for common weaknesses like SQL injection and XSS. This automation could significantly speed up penetration testing, helping developers better secure applications against such automated threats and potentially reducing costs associated with data breaches. AI

IMPACT LLM-driven automation could accelerate penetration testing, enabling faster vulnerability discovery and improved application security.

RANK_REASON The cluster describes an experiment testing the capabilities of LLMs in a specific domain (application security), which aligns with research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

• cross-site scripting
• Large Language Models
• LLMs
• security testing
• SQL injection
• vulnerable applications

• product
• safety

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →