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New Interlock Gateway Secures AI Agents Accessing Real-World Systems

A new runtime security gateway called Interlock has been developed to address the risks associated with AI agents accessing real-world systems. The gateway acts as an intermediary, scrutinizing every tool call made by an AI agent before it reaches the target system. Interlock enforces policies, validates schemas against baselines to detect drift, scans for prompt injection and PII, and logs all actions, ensuring that security decisions are made proactively before execution. AI

IMPACT Enhances the security posture for AI agents interacting with external systems, mitigating risks like prompt injection and schema drift.

RANK_REASON This is a technical deep-dive into a newly developed security tool for AI agents, not a release from a frontier model lab or a major industry event.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Interlock Gateway Secures AI Agents Accessing Real-World Systems

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0 / 100
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Tool
This is a technical deep-dive into a newly developed security tool for AI agents, not a release from a frontier model lab or a major industry event.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra, safety
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High
Clearly on-topic for AI-industry coverage.
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120 days old
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COVERAGE [1]

  1. dev.to — MCP tag TIER_1 English(EN) · Maaz Ahmed ·

    We Built a Runtime Security Gateway for MCP Agents in 30 Days — Here's What We Learned

    <p>TL;DR: AI agents are getting tool access to real systems. Nobody is enforcing what they can actually do at runtime. We built Interlock to fix that. Here's the honest technical story.</p> <p>The Problem Nobody Was Talking About<br /> When I started giving AI agents access to MC…