AI incident summaries: verify before you send them
LLMs write smooth incident summaries that can include wrong times, invented causes and missing steps. Use this checklist to verify one before it goes out.
Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
LLMs write smooth incident summaries that can include wrong times, invented causes and missing steps. Use this checklist to verify one before it goes out.
Your incident plan probably misses AI failures. What to add: definitions, intake fields, a kill switch, communication, third-party cases and review.
Who owns what in AI governance? A simple RACI for executive, system owner, security, legal, engineering and reviewers, based on NIST AI RMF accountability.
Seven common AI governance myths checked against the NIST AI RMF and federal guidance: certification, bans, checklists, one-time reviews and more.
A 30-day plan for a small company starting AI governance: inventory, policy, owners, tiers, vendor checks and a first review, without a big program.
Buyers increasingly ask how much code comes from AI assistants and how it is reviewed. Questions to expect and a policy that gives a straight answer.
Evals measure behaviour on fixed test sets and repeat cheaply. Red teaming hunts for new failures with an adversary mindset. Why you need both.
AI can speed up security questionnaires, but wrong answers become commitments. Rules for source material, human review and what never to auto send.
Persistent memory lets an injected instruction outlive one chat. What ATLAS says about memory and thread poisoning, and the four hardening controls.
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