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HighFlame Launches MCP Security to Bring Defense in Depth to the Model Context Protocol Layer

Detect tool poisoning early, block unsafe tool calls in real time, and prove governance—so enterprises can deploy agentic AI safely at scale.

News on our announcement about RAMPARTS

In the rapidly evolving landscape of artificial intelligence, Model Context Protocol (MCP) has emerged as a pivotal open standard, enabling AI agents and Large Language Models (LLMs) to seamlessly interact with external data sources and tools.

HighFlame at BlackHat2025

Meet with our team to learn how we help enterprises stay ahead ofreal-world threats with a unified stack that not only protects AI systems inproduction, but continuously stress-tests them using automated red teaming.

HighFlame joins Coalition for Secure AI

At Highflame, we’re dedicated to enabling organizations to deliver AI outcomes safely, at scale, and without compromise.

Announcing the Ramparts MCP Toolkit on Docker Hub

Javelin is proud to announce that the Ramparts MCP Toolkit is officially available on the Docker Hub registry. We’ve made setup simple with a single docker pull command, enabling any developer to deploy enterprise-grade MCP security scanning in under two minutes.

Launching Palisade: Zero-Trust Security for the AI Model Supply Chain

The AI ecosystem has a security blind spot. We lock down software delivery with SAST, dependency scanning, signed artifacts, and hardened CI/CD. Then we download multi-GB model files from the internet, deploy them to production, and let them call internal tools—often with far less scrutiny than a container image.

Introducing Overwatch: Code Agent Security

When developers open their IDEs today, they’re not just writing code. They’re working alongside agents, tools, and servers that can generate, analyze, and even ship code on their behalf. The rise of the Model Context Protocol (MCP) has made it easier than ever for these agents to plug directly into local environments. But the line between helpful and harmful servers is far thinner than most people realize.

Introducing Overwatch: Code Agent Security

When developers open their IDEs today, they’re not just writing code. They’re working alongside agents, tools, and servers that can generate, analyze, and even ship code on their behalf. The rise of the Model Context Protocol (MCP) has made it easier than ever for these agents to plug directly into local environments. But the line between helpful and harmful servers is far thinner than most people realize.

Launching Palisade: Zero-Trust Security for the AI Model Supply Chain

The AI ecosystem has a security blind spot. We lock down software delivery with SAST, dependency scanning, signed artifacts, and hardened CI/CD. Then we download multi-GB model files from the internet, deploy them to production, and let them call internal tools—often with far less scrutiny than a container image.

Announcing the Ramparts MCP Toolkit on Docker Hub

Javelin is proud to announce that the Ramparts MCP Toolkit is officially available on the Docker Hub registry. We’ve made setup simple with a single docker pull command, enabling any developer to deploy enterprise-grade MCP security scanning in under two minutes.

HighFlame joins Coalition for Secure AI

At Highflame, we’re dedicated to enabling organizations to deliver AI outcomes safely, at scale, and without compromise.

HighFlame at BlackHat2025

Meet with our team to learn how we help enterprises stay ahead ofreal-world threats with a unified stack that not only protects AI systems inproduction, but continuously stress-tests them using automated red teaming.

News on our announcement about RAMPARTS

In the rapidly evolving landscape of artificial intelligence, Model Context Protocol (MCP) has emerged as a pivotal open standard, enabling AI agents and Large Language Models (LLMs) to seamlessly interact with external data sources and tools.

HighFlame Launches MCP Security to Bring Defense in Depth to the Model Context Protocol Layer

Detect tool poisoning early, block unsafe tool calls in real time, and prove governance—so enterprises can deploy agentic AI safely at scale.