When to pause, roll back or retire an AI system
Criteria for stopping an AI system: unacceptable risk, drift, vendor change or lost purpose. What the NIST AI RMF says about disengaging and retiring.
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.
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.
Logs hold credentials, personal data and internal names. Here is what to strip or tokenize before an LLM sees them, and how to keep analysis useful.
Prompt injection is input that changes an LLM's behavior in unintended ways. Learn direct vs indirect forms and the OWASP mitigation steps that help.
MCP is an open standard for connecting AI applications to data, tools and workflows. Learn how it works and the security questions it raises.
MITRE ATLAS is a public knowledge base of adversary tactics and techniques against AI systems. Here is what it contains and how teams put it to work.
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