Breaking AI: Adversarial Techniques in LLM Penetration Testing

Bishop Fox’s “Breaking AI” explores how traditional pentesting methods are insufficient for testing large language models and introduces techniques tailored to LLM-specific vulnerabilities. Instead of focusing on code exploits, attackers manipulate language through tactics like emotional preloading, narrative hijacking, and context reshaping. These linguistic attacks can bypass safety filters and trigger unintended behaviors. The talk emphasizes that secure LLM deployments require defense-in-depth strategies, including sandboxing, output monitoring, and human oversight for sensitive actions. Effective pentesting must reflect real-world abuse scenarios, using full conversational transcripts to assess risks and improve resilience. 

https://bishopfox.com/resources/breaking-ai-inside-the-art-of-llm-pen-testing

Comments

Popular posts from this blog

Secure Vibe Coding Guide: Best Practices for Writing Secure Code

KEVIntel: Real-Time Intelligence on Exploited Vulnerabilities

OWASP SAMM Skills Framework Enhances Software Security Roles