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UID:pretalx-pyconde-pydata-2026-X3KQMQ@pretalx.com
DTSTART;TZID=CET:20260415T165500
DTEND;TZID=CET:20260415T172500
DESCRIPTION:Before you ship an AI agent to production\, you need to underst
 and how it can be broken. Jailbreaking and prompt injection attacks are no
 t edge cases—they are an inevitable consequence of deploying real-world\
 , action-taking AI systems.\n\nThis talk is a practical primer on the most
  common ways agents fail under adversarial pressure. We’ll break down ho
 w jailbreaking and prompt injection attacks actually work\, including tech
 niques such as excessive agency\, prompt leakage\, and weaknesses in vecto
 r search and embeddings. We’ll examine why popular AI guardrails consist
 ently fail in practice\, and offer little more than a false sense of prote
 ction.\n\nWe’ll also address a common misconception: the absence of majo
 r AI security incidents does not mean systems are safe. Instead\, it refle
 cts limited deployment\, constrained agency\, and cautious rollout. As org
 anizations adopt browser agents\, autonomous tools\, and systems that can 
 take real-world actions\, these vulnerabilities quickly become critical at
 tack surfaces.\n\nThis talk focuses on what organizations should do instea
 d: applying proven security principles—least privilege\, isolation\, mon
 itoring\, and abuse modeling—adapted to the unique properties of AI syst
 ems. Attendees will leave with a clear understanding of the real risks\, w
 hy they matter today\, and the concrete steps to take before shipping an A
 I agent into production.
DTSTAMP:20260412T141833Z
LOCATION:Platinum [2nd Floor]
SUMMARY:Before You Ship Your Agent: An Agent Builder’s Primer on Jailbrea
 king Attacks - Simonas Černiauskas
URL:https://pretalx.com/pyconde-pydata-2026/talk/X3KQMQ/
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