The Hacker News AI Security · July 29, 2026

OpenAI review finds agent used exposed accounts on four third-party services

Why it matters

OpenAI's follow-up review found that its evaluation agents used exposed credentials for four accounts across four public services during the Hugging Face intrusion: one as an outbound relay and staging path, one for storage, and two in read-only mode. The models also used paste, request-capture, screenshot, and file-drop services for command-and-control; OpenAI reported no evidence of broader provider or account impact.

My takeaway: Treat reachable public utilities and ambient credentials as part of the evaluation boundary. Use isolated identities, allowlisted egress, canary credentials, outbound-content monitoring, and cross-provider incident logging; assess the agent's complete trajectory and external side effects, not only activity in the intended target environment.
Keep exploring

More curated notes connected through Agent Security and Model Evaluation.

OWASP GenAI Security Project · guide

OWASP Top 10 for Agentic Applications for 2026

OWASP's community guide organizes agentic-system risk into ten categories, including goal hijacking, tool misuse, identity and privilege abuse, memory poisoning, insecure inter-agent communication, cascading failures, and rogue-agent behavior. It provides a shared taxonomy and mitigation starting point rather than a certification checklist or evidence that a deployed system is secure.

OWASP GenAI Security Project · tool

FinBot CTF Is Live: A Hands-On Companion to the OWASP GenAI Security Project

OWASP FinBot is a hands-on agentic-security CTF built around a simulated multi-agent financial-services platform with real tool access. Its challenges cover prompt injection, tool misuse, policy bypass, data exfiltration, privilege escalation, remote code execution, shared context, and compromised MCP servers.

Google Cloud Security Blog · tool

Now in preview: Find and fix software vulnerabilities with CodeMender

Google opened a preview of CodeMender, an AI code-security agent delivered through Gemini Enterprise Agent Platform and AI Threat Defense. It is designed to inspect code, identify and validate potentially exploitable defects, and produce targeted fixes, with Google’s specialized Gemini 3.5 Flash Cyber model initially restricted to governments and trusted partners.