[un]prompted
[un]prompted Security Practitioner Con 2026
Every session of [un]prompted 2026: Nicholas Carlini, Daniel Miessler, Heather Adkins + 50 more who brought what they've learned from the edge: agents, detection, forensics, governance, llm security, offensive, prompt injection, threat intel. "It feels like a warp point in time: the moment security has to decide whether to stay deterministic, or jump into this non‑deterministic, AI‑driven world. But if we can pull just 2% of the people around us up one level, from "I type into ChatGPT like Google" to "I use agents and tools," then I believe we can change companies and countries.” - Gadi Evron.
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[un]prompted
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Latest episode
May 28, 2026
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Episodes
Ep 51 | Srajan Gupta - Injecting Security Context During Vibe Coding | [un]prompted 2026 28.05.2026 23:07
Day 2 | Stage 2 Senior Security Engineer from Dave discusses vibe coding with AI tools like Cursor being fast but quietly bypassing traditional AppSec controls. Demos MCP server injecting security context directly into AI coding loop. Before code generation, pulls threat models, security requirements, OWASP guidance. After generation, verifies output for vulnerabilities and security standards comp...
Ep 52 | Scott Behrens & Justice Cassel - Source to Sink: Improving LLM Vuln Discovery | [un]prompted 2026 28.05.2026 25:58
Day 2 | Stage 2 Principal Security Engineer and Application & GenAI Security from Netflix discuss getting tired of LLMs crying wolf about every string concatenation. Built agentic pipeline that thinks before it screams. Explores improving accuracy and actionability of LLM-driven first-party vulnerability discovery in real-world codebases. Therapy session for anyone who mass-closed 200 AI-gener...
Ep 53 | Joey Melo - The Parseltongue Protocol: Textual Obfuscation Methods | [un]prompted 2026 28.05.2026 18:15
Day 2 | Stage 2 AI Red Teaming Specialist from CrowdStrike presents 100+ textual obfuscation methods against 9 leading AI models with 17,000+ malicious prompts. LLMs designed with robust multilingual support create new security vulnerability. Systematic empirical study reveals significant gaps in current AI safety systems. Gains insights into evolving prompt injection attack surface and which enco...
Ep 54 | Jenny Guanni Qu - Why Most ML Vulnerability Detection Fails | [un]prompted 2026 28.05.2026 12:59
Day 2 | Stage 2 AI Researcher from Pebblebed covers counterintuitive lessons from training on 125K Linux kernel commits. Most obvious ML-based vulnerability detection approaches failed. Why "hard negatives" hurt performance, why subsystem boundaries are where bugs hide, and why average kernel security bug survives 2.1 years undetected. Practical takeaways for building vuln discovery systems. Jenny...
Ep 55 | Matt Rittinghouse & Millie Huang - 1.8M Prompts, 30 Alerts | [un]prompted 2026 28.05.2026 21:56
Day 2 | Stage 2 Lead Security Data Scientist and Staff Security Data Scientist from Salesforce discuss securing 12,000 autonomous agents when anyone can build one. Static rules alone can't catch abuse without drowning SOC in noise. Process millions of daily prompts across thousands of organizations. Created behavioral baselines like Asset Rarity and Query Complexity, distilling unpredictable activ...
Ep 56 | Ilia Shumailov - AI Security with Guarantees | [un]prompted 2026 28.05.2026 25:35
Day 2 | Stage 2 CEO of AI Sequrity Company discusses running modern AI agents with security guarantees, even for complex setups such as computer use. Ilia Shumailov is CEO, AI Sequrity Company. Watch on YouTube: https://www.youtube.com/watch?v=NU6l0Qcf5rU
Ep 57 | Dongdong Sun - From OSINT Chaos to Knowledge Graph | [un]prompted 2026 28.05.2026 27:03
Day 2 | Stage 2 Senior Staff Machine Learning Engineer from Palo Alto Networks walks through production AI pipeline turning millions of unstructured threat reports into queryable knowledge graph. Extracts threats and relationships from raw OSINT data. Architectural decisions making it work at scale. Dongdong Sun is Senior Staff Machine Learning Engineer, Palo Alto Networks. Watch on YouTube: https...
Ep 58 | Xenia Mountrouidou - Traditional ML vs LLMs: who can classify better? | [un]prompted 2026 28.05.2026 7:40
Day 2 | Stage 2 Principal Cyber Data Scientist from Expel compares traditional ML and LLMs for classification tasks. Xenia Mountrouidou is Principal Cyber Data Scientist, Expel. Watch on YouTube: https://www.youtube.com/watch?v=fAmr0N2rHIU
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