How should a disclosure policy handle AI-written bug reports?
Ask for reproduction, plain words and proof, not a ban on tools. What one major open source project asks of reporters and what your policy can borrow.
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.
Ask for reproduction, plain words and proof, not a ban on tools. What one major open source project asks of reporters and what your policy can borrow.
Twelve AI security terms in plain words, from agent and MCP to guardrail, gate, excessive agency and tool poisoning, so you can read a vendor page.
At 90 days, track coverage, owner assignment, scope reduction, approval quality, exceptions and time to stop. Six measures that show governance is real.
Buyers ask whether AI writes your code. Cover usage scope, review rules, dependency checks, data handling and logging without overclaiming control.
AI triage and fix suggestions change your data flow. Contract and review questions on model providers, retention, training, opt out and human approval.
What to ask an AI coding assistant vendor before rollout: data handling, retention, training use, admin controls, agent mode and incident response.
Seven common beliefs about AI chat privacy, checked against Anthropic and Google documentation: delete, incognito, links, voice, location and human review.
AI agent security tools fall into a few categories: discovery, identity, guardrails, testing and observability. How to tell which problem you have first.
An AI agent kill switch should stop actions, revoke credentials, halt queued work and keep a record. Use this checklist to test whether yours really works.
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