Every conference talk we've analyzed. Sorted newest first.. Talks analyzed in full.
Learn how to architect a unified Personal AI Infrastructure (PAI) stack with Council multi-agent debate, the PAI algorithm, and Arbo pipelines to amplify your security engineering practice.
Learn how AI workflows, reasoning models, and feedback loops turned a two-week manual investigation into a two-day operation that identified 2,400 supply chain attack victims.
Learn how AI cut a 6-week chip glitching failure to 7 minutes. Discover how LLMs guide EM fault injection and design hardware hacking platforms on a $7 Pico.
Discover how AI notetakers introduce prompt injection, viral OAuth expansion, and silent recording into your enterprise — and the controls every security team needs now.
Discover how Trend Micro's FENRIR engine chains SAST tools, fast LLM triage, and agentic sandboxes to find 60+ CVEs at $8.80 per true positive.
Learn how attackers embed prompt injections in passport images to hijack AI KYC agents and exfiltrate customer PII at scale.
Learn how Binary Shield uses AI fingerprinting to detect and share prompt injection threats across all LLM services in your portfolio — privacy-safe and 36x faster.
Learn how AI agents detect authentication bypasses, MFA bypasses, and authorization bugs using validator reuse and auth transmogrification.
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.
Learn how Stripe built and deployed two production AI security agents with multi-agent architecture, LLM-as-judge eval pipelines, and phased rollout.
Learn how Adobe built a RAG-powered security guidance platform delivering org-specific recommendations across Jira, Slack, and IDE at scale.
Learn why precision and recall fail for autonomous AI security agents — and how rubric-based LLM judge evaluation gives your team a reliable deployment bar.
Discover how Google's Big Sleep and Code Mender use agentic AI to find and patch deep memory safety bugs with zero false positives.
Learn the three hidden costs of software composition analysis and how to match SCA tools to your AppSec program maturity.
Learn a proven 7-phase AI red teaming methodology, prompt injection taxonomy, and real enterprise case studies for assessing LLM systems.
Learn how malicious VS Code extensions bypass Microsoft's safeguards to steal credentials and execute code on developer machines — and the only defense that actually works.
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 to assess AI code generation security risks—from package hallucination to IP liability—and apply governance controls that protect your SDLC.
Learn how Snapchat uncovered three chained, high-impact bug bounty findings—supply chain RCE, Android deep link abuse, and Jupyter XSS-to-RCE—and the program capabilities each forced them to build.
Learn to exploit OWASP ML Top 10 risks hands-on — supply chain attacks, data poisoning, and output integrity bypasses against a real AWS SageMaker infrastructure.
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.
Learn to find WebRTC security vulnerabilities — TURN relay abuse, RTP injection, and signaling DoS — that most web and API pentesters miss entirely.