~/talk

When AI Gets Manipulated: Security Risks in LLM Applications

Talkat Commit Your Code 2026 · 2026-09-02..09-04· [security, large-language-models]
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Generative AI systems accept both system prompts and user input and remain vulnerable to prompt injection that overrides guardrails; the demo uses an attacker-controlled subdomain and the out‑of‑band tool interact.sh to trigger a DNS lookup, exfiltrate a hidden promo code and redeem it for a 100% discount. The talk names direct and indirect injection, maps how agent tool calls reach internal REST APIs, shows reconnaissance + exploitation steps, and says practical defense is tightening guardrails and limiting LLM access to sensitive tools.

AI-written summary · about

  1. 0:00LLM security risks
  2. 2:22What is prompt injection
  3. 5:55Why prompt injection is dangerous
  4. 8:07LLM attack architecture
  5. 10:40LLM vulnerabilities types
  6. 12:26Meme break and prompt tricks
  7. 13:08Demo setup and shopping assistant
  8. 16:01Live demo and attack
  9. 23:55Reconnaissance and ethical hacking
  10. 24:59Real-world impact and bug bounty
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