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AI Security

ML supply chain glossary: checkpoint, adapter, merge, quantized and more

Plain definitions of architecture, checkpoint, adapter, merge, quantized model, model card and ML BOM, and why each matters for supply chain records.

Oct 18, 20264 min read
AI Security

ML data lineage: what to record so you can answer where it came from

A minimum useful lineage record for ML: datasets, jobs, runs, versions and owners. What to capture so deletion and incident questions have answers.

Oct 18, 20263 min read
AI Security

What should you ask an MCP server vendor about tokens and scopes?

Questions to put to a vendor offering an MCP server: token audience checks, minimal scopes, consent screens, session handling and logs you can read.

Oct 18, 20263 min read
AI Security

MCP tool security: what the spec requires versus suggests

Which MCP tool controls are mandatory and which are only advice? A MUST versus SHOULD table for servers and clients, plus gaps you must cover yourself.

Oct 18, 20264 min read
AI Security

What should an MCP security evaluation test? Ten trial test cases

An MCP security evaluation should test token handling, tool changes, consent, SSRF and logging. Here are ten test cases drawn from the MCP specification.

Oct 18, 20264 min read
AI Security

MCP guardrail buyer questions: what to ask a vendor before you buy

Twelve questions to ask any vendor selling MCP guardrails: scope, enforcement point, logging, failure mode, identity and what happens on outage.

Oct 18, 20264 min read
AI Security

MCP security controls compared: allowlist, proxy or client prompts

Three ways to control MCP use in a team: a static allowlist, a central proxy, or client approval prompts. What each catches, misses and costs in effort.

Oct 18, 20263 min read
AI Security

LiteLLM PyPI compromise of March 2026: what the advisory says

Two litellm releases on PyPI carried credential-harvesting code in March 2026. The affected versions, what it collected and what the advisory says to do.

Oct 18, 20263 min read
AI Security

Keep human approvals of agent actions meaningful, not rubber stamps

Approval prompts only protect you if people read them. How to design agent approvals, limit their number and measure whether they still work over time.

Oct 18, 20263 min read

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