AI agent security, explained.
Plain-language answers to the questions teams ask when they ship agents with tools, RAG, memory, and MCP — and how a context firewall addresses each one.
The runtime boundary that controls which context can influence which action.
Map sources and sinks, then enforce controls across the whole workflow.
Why detection isn't enough, and what source-to-sink controls add.
Schema pinning, drift, shadowing, and tool-call inspection for MCP agents.
Gate memory writes so stored context can't become future instruction.
Keep retrieved context as evidence, not instruction.
Inspect every tool call before it executes.
Test the whole agent loop, then turn findings into enforced policy.
Treat the DOM, OCR, and QR content as untrusted observation.
Permission to influence an action, not just to be in the prompt.
Context firewall vs the alternatives.
Detection vs authority, side by side.
Model I/O screening vs whole-workflow authority.
Why agents need runtime enforcement, not just guardrails.
Shaping behaviour vs enforcing authority.
Traffic management vs source-to-sink control.
Detecting the leak vs preventing the cause.
Web perimeter vs agent workflow.
Find the path, close it, prove it stays closed.
Turn the theory into proof for your workflow.
Give us one agent workflow. We’ll map the context boundary, replay the abuse paths, and show where the firewall stops them.