All Deep Dives For Infosec Conference Talks Covering Threat Modeling. Talks analyzed in full.
![Kinetic Risk: Securing and Governing Physical AI in the Wild | [un]prompted 2026](https://thecyberarchive.com/assets/teasers/kinetic-risk-securing-governing-physical-ai-padma-apparao.webp)
Learn how physical AI security differs from digital AI risk and why latency is a safety parameter, not a performance metric, in autonomous systems.
![Securing Workspace GenAI at Google Speed | [un]prompted 2026](https://thecyberarchive.com/assets/teasers/genai-agent-security-google-defense-in-depth-blueprint-nicolas-lidzborski.webp)
Learn how Google's Workspace security team built a defense-in-depth architecture against indirect prompt injection and rogue agent actions in production GenAI systems.
![The AI Security Larsen Effect - How to Stop the Feedback Loop | [un]prompted 2026](https://thecyberarchive.com/assets/teasers/ai-security-vendor-evaluation-feedback-loop-maxim-kovalsky.webp)
Learn to break the AI security procurement loop using a risk taxonomy from OWASP, NIST, and MITRE — and a 5-minute vendor evaluation wizard.
Learn how Fly.io secured shared GPU infrastructure using VFIO, IOMMU isolation, and firmware auditing — a practical guide to multi-tenant GPU security.
![Code Is Free: Securing Software | [un]prompted 2026](https://thecyberarchive.com/assets/teasers/ai-security-guardrails-cicd-the-free-approach-paul-mcmillan-ryan-lopopolo.webp)
Learn how OpenAI engineers built LLM-powered security reviewers, living threat models, and a daily dependency scanner using ~40 lines of GitHub Actions YAML and checked-in Markdown files.
![Guardrails beyond Vibes | [un]prompted 2026](https://thecyberarchive.com/assets/teasers/ai-security-agents-production-stripe-guardrails-playbook-jeffrey-zhang-siddh-shah.webp)
Learn how Stripe built and deployed two production AI security agents with multi-agent architecture, LLM-as-judge eval pipelines, and phased rollout.
Learn to threat-model AI agents for indirect prompt injection: enumerate tools, map AI-specific attack vectors, and automate dynamic testing with TamperMonkey.
Learn how to build specialized AI security bots and apply generative AI across red team, blue team, and purple team workflows using a proven prompt engineering methodology.
Learn how to apply structured threat modeling to AI/ML systems using the ML SecOps framework, three diagnostic questions, and OWASP AI Exchange controls.
Learn how adversarial ML attacks silently bypass AI security controls and how to apply AI security threat modeling using Project Guardrail's tiered questionnaire framework.
