Agent credentials: issue, scope, expire and revoke
A lifecycle for the credentials an AI agent holds: one identity per agent, narrow scopes, short lifetimes, monitored use and a revoke path you have tested.
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.
A lifecycle for the credentials an AI agent holds: one identity per agent, narrow scopes, short lifetimes, monitored use and a revoke path you have tested.
Does an AI feature inside a vendor app belong in your AI inventory? A decision guide for in-house models, APIs, embedded features and agents.
A decision guide for human-in-the-loop approval on agent tool calls, based on the MCP spec and OWASP guidance: irreversible, external and costly actions.
A simple way to sort agent tool calls into allow, ask and block, using impact, reversibility and reach, with OWASP and MCP guidance behind it.
Criteria for stopping an AI system: unacceptable risk, drift, vendor change or lost purpose. What the NIST AI RMF says about disengaging and retiring.
AI is a poor fit for some SOC tasks. Here are the cases to avoid or keep manual: irreversible actions, legal calls, unmeasured alerts and sensitive data.
An AI acceptable use policy should cover scope, approved tools, data rules, human review, incidents and exceptions. A section by section outline to adapt.
The fields a RAG system should log, from retrieved chunk IDs to tool calls and agent identity, so you can trace a bad answer back to its source.
Assume users can read your system prompt. A checklist of what to keep out, such as credentials, permission maps and business limits, and where to put it.
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