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 OAuth authentication has been rewritten three times since March 2025. Here's how the spec, its token security model, and real CVEs like CVE-2025-49596 shape safe MCP deployments.
An MCP rug pull attack swaps a trusted server's tool definitions after approval. Here's how tool definition drift happens, and how Safeguard catches it early.
A practical buyer's guide to MCP security gateways and scanners — evaluation criteria, honest strengths and gaps for real vendors, and where Safeguard fits.
A precise MCP security glossary covering clients, servers, resources vs. tools, tool poisoning, rug pulls, and the confused deputy problem — with real-world examples.
A concrete, incident-driven walkthrough of AI supply chain security — from poisoned datasets and backdoored Hugging Face models to CI pipeline hijacks — and how to reduce the risk end to end.
Poisoned datasets and untraceable training data are already causing lawsuits and breaches. Here's why training data provenance is now a security requirement.
A practical guide to model weight integrity: baseline checksums, sign weights, verify in CI/CD, and detect tampering before it reaches production.
Fine-tuning pipeline security is now an AI supply chain priority: as few as 250 poisoned documents can backdoor a model, and LoRA adapters make it easy to hide.
A single expired domain and $60 can poison a training set. Here's how data poisoning attacks corrupt LLM behavior — and how Safeguard verifies training data before it ships.
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