@snyksec Announcement:

We’re thrilled to officially join forces with @snyksec! . Together, we’re changing the landscape of the agentic AI future. More to come!

RT @lbeurerkellner: 😈 BEWARE: Claude 4 + GitHub MCP will leak your private GitHub repositories, no questions asked. We discovered a new at….

Invariant researchers have uncovered a new security flaw in GitHub’s official MCP server, enabling attackers to exfiltrate private repository data. The toxic flow was identified during an automated scan using Invariant's security stack. Learn more:

🔵 New release: Invariant MCP-scan v0.2 is here!. Track, audit & secure all local MCP traffic with static+dynamic scanning, local guardrails, and customizable policies. Ideal for orgs prioritizing agent security & compliance. Docs: #AI #DevSecOps

We are proud to share that AgentDojo, an Invariant research project done with @ETH, has won the first price of the @ai_risks SafeBench competition. We truly appreciate this recognition from the community. Learn More:

MCP-scan:

Blog post:

🛡️ We are thrilled to partner with @SmitheryDotAi to protect their MCP servers with Invariant MCP-scan. Also, a lot of features will be dropping in MCP-scan soon!

RT @DoerrfeldBill: MCP is the hottest thing in AI right now, but people aren't really talking about the security implications. I covered….

RT @marc_r_fischer: We recently shipped a lot of updates to mcp-scan:.- whitelisting of tools.- Improvements to the server (reducing false-….

For more details on Invariant Guardrails, check out our blog post:

Invariant Guardrails, Gateway, and Explorer are all open-source. Check them out! We would love some feedback.

Policies can be written in our powerful rule language or deployed from our library of examples in a single click. Test, debug, and monitor in real time with Invariant Explorer.

Guardrails can be deployed in minutes with no changes to your model or app architecture. Just drop in the Invariant Gateway as a lightweight proxy layer for LLMs and MCP.

Guardrails go far beyond simple prompts and filters: You can define and enforce context-aware policies for your AI apps with tool calling and MCP. This enables content safety, data flows, and contextual security checks that actually work.

🛡️ We just released Invariant Guardrails — a contextual guardrail system for agents and MCP-powered AI applications. Open source & easy to deploy. 🧵

RT @lbeurerkellner: 🔴🌎 New MCP attack on BrowserMCP. We show an MCP attack on the popular BrowserMCP. It allows attackers to read arbitrary….

A small disclaimer: We use Invariant Guardrails server-side via an API, and we are collecting tool names and descriptions for security research purposes (not your user data!). Don't use it if you don't want to share your tools.

For more details, check out our full blog post on MCP-Scan: