Securing MCP Servers: A Practical Checklist
MCP servers are runtime dependencies your agent trusts implicitly. Here is a concrete checklist for auth, tool pinning, sandboxing, and monitoring before you ship one.
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 are runtime dependencies your agent trusts implicitly. Here is a concrete checklist for auth, tool pinning, sandboxing, and monitoring before you ship one.
A zero-day discovery pipeline is only as useful as the triage process around it. Here is what triage looks like when the pipeline gives engineers something they can defend.
Small language models aren't a worse version of large ones. For specific security workflows, they're the right tool — if you know which workflows.
Per-token pricing on the OpenAI API looks cheap on a single call and expensive on a year-long security workload. Griffin AI's pricing reflects the architecture.
A senior engineer's threat model for Claude MCP tool poisoning in 2026, covering malicious servers, description hijacking, and the authorization patterns that actually help.
Prompt injection started as a research curiosity. In 2026 it is a regular line item on bug bounty leaderboards, with payout norms, scope definitions, and a maturing triage culture.
MCP servers do not stay still. Tool surfaces drift, scopes expand, and the server you approved is not the server in production. Here is how to catch that.
The difference between grounded reasoning and hallucinated reasoning is not eloquence — it's citation. A look at how Griffin AI anchors every claim.
Gemini on-device models are fast and cheap. For the developer-tool layer, they're useful. For the engine-plus-LLM layer, on-device is not the right fit.
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