Key Takeaways from Red-Teaming 100 Generative AI Products
Dinesh Kumar
Swotting AI, Offensive Security, CISSP | Cyber Threat Researcher | Threat Hunting, Malware Analysis, Cybercrime Investigation, Former Product Manager at Yahoo! | Cyber Aware #WeDoHack #d9hunt #d09r
Generative AI is evolving, but with it comes significant risks. Microsoft’s AI Red Team has shared a comprehensive report on red-teaming over 100 AI systems, offering actionable lessons and case studies that highlight key vulnerabilities and solutions.
Key Lessons:
Case Studies:
1?? Jailbreaking a Vision Language Model: Exploiting vulnerabilities in image inputs to bypass safety.
2?? Automating Scams with LLMs: Weaponizing persuasion through text-to-speech integration.
3?? Chatbot Responses to Distressed Users: Assessing risks in mental health-related scenarios.
4?? Gender Bias in Text-to-Image Generators: Highlighting AI's potential to reinforce stereotypes.
5?? SSRF in Video Processing Applications: Exposing server-side request forgery risks in outdated components.
Read the full report: https://airedteamwhitepapers.blob.core.windows.net/lessonswhitepaper/MS_AIRT_Lessons_eBook.pdf
PyRIT (Python Risk Identification Toolkit for generative AI), to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.
#AI #Cybersecurity #GenerativeAI #GenAI #LLM #RiskManagement #AIethics #Automation #PyRIT #RedTeaming #d09r #wedohack #d9hunter