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Supply Chain Security, in plain English.

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.

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AI Security

Model Context Protocol Permissions Model Explained

MCP's permissions model is subtle. Here is a careful walkthrough of how tool scoping, sampling, and resource access actually work in production.

Apr 12, 20266 min read
AI Security

Securing MCP Servers Without Killing Developer Velocity

MCP servers are spreading inside engineering orgs faster than security teams can review them. Here is how to govern them without slowing teams down.

Apr 12, 20267 min read
AI Security

Why LLMs Are Structurally Insecure (and What That Means for Your Pipeline)

Language models are not insecure because of a bug you can patch. They are insecure by construction — non-deterministic, context-poisonable, and unreproducible. Here is how to reason about them without pretending otherwise.

Apr 12, 20267 min read
AI Security

Auto-PR Remediation Without Broken Builds

Automated fix pull requests sound great until half of them fail CI. Here is how to ship auto-PR remediation that keeps the green build, every time.

Apr 11, 20267 min read
AI Security

Supply Chain Risks of AI Coding Assistants

Copilot, Cursor, and Claude Code change what enters your codebase and how. A practitioner's map of the real supply chain risks — hallucinated packages, rules-file injection, and unreviewed transitive trust.

Apr 11, 20266 min read
AI Security

DSPM for AI: navigating data and AI compliance regulations

DSPM for AI closes the gap traditional tools miss: tracking sensitive data through embeddings, fine-tuning, and vector stores to meet EU AI Act and Colorado AI Act requirements.

Apr 11, 20268 min read
AI Security

Anthropic's Mythos Vulnerability Scanner: An Honest Assessment of Strengths, Weaknesses, and Reasons to Be Cautious

Anthropic's Mythos model is generating buzz for AI-powered vulnerability detection. We break down what it does well, where it struggles, and why security teams should approach the results with healthy skepticism.

Apr 10, 202613 min read
AI Security

Pervasive AI Security: Protecting AI That Is Everywhere in Your Stack

Pervasive AI means models embedded in nearly every application and workflow. That ubiquity creates a security surface most programs have not mapped. Here is how to think about it.

Apr 10, 20266 min read
AI Security

The Limits of Single-Model Vulnerability Scanning: A Technical Analysis of the Mythos Approach

Anthropic's Mythos model claims to find vulnerabilities in open-source code using a single LLM. We analyze where this approach falls short and why production-grade zero-day discovery requires Safeguard's Multi-Agent TAOR Deep Think AI Engine.

Apr 10, 202610 min read
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