Prompt injection

Who’s afraid of an open-weight model? GLM, context bombing and post-Black Hat attacks

Who’s afraid of an open-weight model? GLM, context bombing and post-Black Hat attacks

This episode dives into GLM-5.3's advanced vulnerability discovery, debating its potential for good or harm. It then explores "context bombing," an innovative defensive use of prompt injections, and analyzes recent social engineering attacks targeting cybersecurity pros after the Black Hat conference, emphasizing human vulnerability and the need for robust AI defenses.

Why Your Enterprise Tech Stack Isn’t Ready for AI Agents — Christopher Lovejoy & Saul Howard

Why Your Enterprise Tech Stack Isn’t Ready for AI Agents — Christopher Lovejoy & Saul Howard

Chris Lovejoy and Saul Howard discuss the critical challenges of deploying AI agents in highly regulated enterprise environments, particularly healthcare. They advocate for a "constraints-first" architectural approach, proposing three core primitives – an immutable event log for auditability, schema-driven object storage for sensitive data, and human-agent equivalency for seamless escalation – which collectively enable privacy-preserving evaluations as a fundamental byproduct of the system design, rather than being an afterthought.

What should security leaders do with AI? They don’t know.

What should security leaders do with AI? They don’t know.

This podcast explores the challenges cybersecurity leaders face in adopting AI, the emergence of new threats like ghostjacking, and AI's current capabilities in patching vulnerabilities. It highlights the prevalent "AI decision paralysis" and offers strategic advice for integrating AI into security operations, advocating for a human-in-the-loop approach and a realistic assessment of AI's current

Security Firewall for Agents — Ryan Dahl, Deno

Security Firewall for Agents — Ryan Dahl, Deno

Deno addresses the critical security challenge of AI agents with production write access by introducing Claw Patrol. This MIT-licensed proxy operates below the HTTP layer, deep inspecting all agent communications (including non-HTTP protocols), enforcing granular HCL-based rules, and handling credential injection. It allows for human or LLM approval workflows, ensuring robust, external security against prompt injection and malicious actions, as agents are fundamentally considered untrusted software.

The OWASP LLM Top 10 has a few surprises for you

The OWASP LLM Top 10 has a few surprises for you

This podcast episode breaks down the 2026 OWASP LLM Top 10, highlighting a significant rise in concern for 'Excessive Agency' over traditional prompt injection. It explores the discrepancies between practitioner fears and incident data, particularly regarding misinformation, and advocates for viewing security frameworks as tools for operationalization and cyber resilience, not just compliance. The discussion also covers CISA's new SBOM guidance, emphasizing the need to operationalize supply chain data for effective risk reduction, and shares Black Hat 2026 insights on AI agents as a new attack surface, introducing the concept of 'intent collusion' and underscoring the critical need for foundational security principles like least privilege.

5 Best Practices for Building AI Agent Skills

5 Best Practices for Building AI Agent Skills

This video outlines five essential best practices for developing reliable, secure, and effective AI agent skills. It covers optimizing skill triggering through descriptive metadata, leveraging real-world domain expertise over generic LLM output, managing context windows efficiently by writing lean skills and using progressive disclosure, implementing deterministic logic with scripts for fragile operations, and critically vetting all skills for security vulnerabilities before deployment. These practices are crucial for professionals building robust agentic systems.