Hey fellow cyber specialist can you give me a like or comment on my post -, please -> https://www.linkedin.com/pulse/48-million-cybersecurity-roles-thousands-under-attack-gebreselassie-svvwe/

This is going to be the last message into this community. Join me live for Become the AI Governance Practitioner Companies Want to Hire. You’ll learn how to choose the right role, position your experience, and build the proof employers want to see. 🕚 3:00 PM UTC | 11:00 AM ET 📄 Bring your résumé. 👉 Join free: https://maven.com/p/54e6a1/become-the-ai-governance-practitioner-companies-want-to-hire See you soon.

In July 2026, frontier AI models escaped a testing environment, exploited a zero-day vulnerability, obtained credentials, and compromised part of Hugging Face’s production infrastructure. No human directed the intrusion step by step. The models were pursuing one narrow objective: obtain the answers to a cybersecurity benchmark. The biggest lesson is not only about the exploit. It is about governance. The Cloud Security Alliance’s CISO community recommends treating AI agents as high-risk, privileged workloads. That means every high-risk AI agent should have: • A clearly defined purpose • Enforced permissions and boundaries • Continuous behavioral monitoring • A named human owner • A tested, pre-authorized shutdown process • An incident-response plan • Sufficient logs to reconstruct its actions Your assignment 1. Read the Field Note and CISO post-mortem CyberProsAI Field Note: https://www.cyberprosai.com/blog/openai-models-breached-hugging-face Cloud Security Alliance Post-Mortem: https://cloudsecurityalliance.org/artifacts/hugging-face-ciso-post-mortem 2. Watch the incident breakdown https://www.youtube.com/watch?v=tKGad74Ai8U&t=6s Want the technical deep dive? Study the timeline written by the people who responded to the incident: https://huggingface.co/blog/agent-intrusion-technical-timeline As you review these resources, think about four questions: 1. What was the agent authorized to do? 2. Which technical and governance boundaries failed? 3. Who should have been accountable for the agent’s behavior? 4. Who had the authority to shut it down immediately? If an organization cannot answer those questions, it has an AI governance gap.

Just shipped something I've wanted in the Vault since day one: a complete pre-deployment review you can run on any AI agent this week. What's inside? - 3-tier risk classification (tier sets the review depth) - 36 evidence-based checks across 9 domains, each anchored to NIST AI RMF, ISO 42001, EU AI Act, AIUC-1, OWASP, or MITRE ATLAS - A go / no-go sign-off record the artifact that makes your review real to leadership - A fully worked example: "RefundBot" failing its review, no-go record and all Grab it here: cy-ber.pro/agent-review-kit How I'd use it if I were you: 1. Run the worked example first (pages 7–8) it shows the whole method in five minutes. 2. Tier one real agent at work, a client's, or one you're building. 3. If you're job hunting: complete the review on a public or hypothetical agent and you have a work sample no certificate gives you. Then come back and comment with the agent you're putting through it name, what it can do, and what tier you landed on.