AI Security
Securing MCP Servers in the Enterprise: A Practical Guide
MCP servers connect AI agents to your infrastructure. Here's how to secure them without killing the productivity gains.
Feb 15, 20267 min read
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.
MCP servers connect AI agents to your infrastructure. Here's how to secure them without killing the productivity gains.
AI/ML models are the new open source libraries. Here's why your supply chain security strategy needs to account for model provenance, poisoning, and compliance.
Every HTTP vulnerability begins at a route. Griffin AI models routing; Mythos-class tools guess it. That difference shapes every downstream finding.
PCI DSS 4.0 raised the evidence bar for software security, supplier management, and continuous assurance. Griffin AI meets the new requirements with persisted records. Mythos-class pure-LLM tools leave QSAs asking for artifacts.
Set up the Safeguard GitHub Action to block risky pull requests on dependency vulnerabilities, license violations, and policy breaches before merge.
GCP's Artifact Analysis API is the most direct way to get scan results into your triage tooling. Here is how to use it without drowning your team.
How Safeguard achieves hard multi-tenant isolation in a platform that meets FedRAMP HIGH — the boundaries, the proofs, and the trade-offs we accepted.
If you cannot measure your supply chain security posture, you cannot invest in it. Here are the KPIs that separate real programs from the theater.
SLSA provenance is the cryptographic receipt of a build. Griffin AI verifies it, parses it, and uses it as typed evidence. Mythos-class tools describe it and forget to check the signature.
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