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UID:pretalx-pts2026-MPAYUX@cfp.pass-the-salt.org
DTSTART;TZID=CET:20260701T145000
DTEND;TZID=CET:20260701T152500
DESCRIPTION:As organizations rapidly adopt AI frameworks and third-party co
 mponents\, traditional software\nvulnerabilities are increasingly being in
 troduced into AI infrastructure. While AI security discussions often\nfocu
 s on model level issues such as prompt injections\, the most dangerous ris
 ks frequently arise from\ntraditional software vulnerabilities within the 
 frameworks that power AI systems.\n\nIn this talk\, we will present two vu
 lnerabilities we discovered in Chainlit\, a widely used open-source\nframe
 work that helps building conversational AI apps (CVE-2026-22218 and CVE-20
 26-22219). The issues\naffect internet-facing AI systems and can be trigge
 red remotely\, enabling attackers to steal sensitive files\,\nleak cloud A
 PI keys and secrets\, and perform server-side request forgery (SSRF) on th
 e AI framework\nserver. We confirmed the vulnerabilities in real world\, i
 nternet facing applications used by major\nenterprises\, demonstrating how
  a framework layer vulnerabilities can escalate to cloud level impact.\n\n
 We will walk through the technical details of the vulnerabilities and the 
 exploitation chain that leads to\nserver compromise and credential exposur
 e. We’ll also show how leaking artifacts such as cached\nconversation hi
 story\, configuration files\, or environment variables can reveal highly s
 ensitive enterprise\ndata.
DTSTAMP:20260514T113557Z
LOCATION:Amphitheater 122
SUMMARY:ChainLeak: From AI Framework to Cloud Secrets - Gal Zaban\, Ido Sha
 ni
URL:https://cfp.pass-the-salt.org/pts2026/talk/MPAYUX/
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