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AI Security: Vulnerability Detection and Hidden Model File Risks
Manage episode 454669245 series 3461851
In this episode of the MLSecOps Podcast, the team dives into the transformative potential of Vulnhuntr: zero shot vulnerability discovery using LLMs. Madison Vorbrich hosts Dan McInerney and Marcello Salvati to discuss Vulnhuntr’s ability to autonomously identify vulnerabilities, including zero-days, using large language models (LLMs) like Claude. They explore the evolution of AI tools for security, the gap between traditional and AI-based static code analysis, and how Vulnhuntr enables both developers and security teams to proactively safeguard their projects. The conversation also highlights Protect AI’s bug bounty platform, huntr.com, and its expansion into model file vulnerabilities (MFVs), emphasizing the critical need to secure AI supply chains and systems.
Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models
Recon: Automated Red Teaming for GenAI
Protect AI’s ML Security-Focused Open Source Tools
LLM Guard Open Source Security Toolkit for LLM Interactions
Huntr - The World's First AI/Machine Learning Bug Bounty Platform
50 episodios
Manage episode 454669245 series 3461851
In this episode of the MLSecOps Podcast, the team dives into the transformative potential of Vulnhuntr: zero shot vulnerability discovery using LLMs. Madison Vorbrich hosts Dan McInerney and Marcello Salvati to discuss Vulnhuntr’s ability to autonomously identify vulnerabilities, including zero-days, using large language models (LLMs) like Claude. They explore the evolution of AI tools for security, the gap between traditional and AI-based static code analysis, and how Vulnhuntr enables both developers and security teams to proactively safeguard their projects. The conversation also highlights Protect AI’s bug bounty platform, huntr.com, and its expansion into model file vulnerabilities (MFVs), emphasizing the critical need to secure AI supply chains and systems.
Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models
Recon: Automated Red Teaming for GenAI
Protect AI’s ML Security-Focused Open Source Tools
LLM Guard Open Source Security Toolkit for LLM Interactions
Huntr - The World's First AI/Machine Learning Bug Bounty Platform
50 episodios
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1 Implementing Enterprise AI Governance: Balancing Ethics, Innovation & Risk for Business Success 38:39

1 Evaluating Real-World Adversarial ML Attack Risks and Effective Management: Robustness vs Non-ML Mitigations 41:19

1 Cybersecurity of Tomorrow: Exploring the Future of Security and Governance for AI Systems; With Guest: Martin Stanley, CISSP 39:45

1 A Holistic Approach to Understanding the AI Lifecycle and Securing ML Systems: Protecting AI Through People, Processes & Technology; With Guest: Rob van der Veer 29:25

1 ML Model Fairness: Measuring and Mitigating Algorithmic Disparities; With Guest: Nick Schmidt 35:33

1 Privacy Engineering: Safeguarding AI & ML Systems in a Data-Driven Era; With Guest Katharine Jarmul 46:44

1 Indirect Prompt Injections and Threat Modeling of LLM Applications; With Guest: Kai Greshake 36:14

1 ML Security: AI Incident Response Plans and Enterprise Risk Culture; With Guest: Patrick Hall 38:49

1 MLSecOps: Red Teaming, Threat Modeling, and Attack Methods of AI Apps; With Guest: Johann Rehberger 40:29
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