While building agent-based systems with LLM tool use, I kept running into the same failure mode:

External content (webpages, files, API responses) would eventually influence agent behavior in unintended ways.

Prompt injection isn’t just a “filtering problem” it’s an architectural one.

So I built Sentinel Gateway, a middleware layer that sits between agents and tools and enforces a strict separation:

• Instruction channel (trusted, signed, runtime-issued only)
• Data channel (untrusted, never executable)

Any action an agent takes must be backed by a signed, scoped runtime token, which means:

• external content cannot escalate into instructions
• tool calls cannot be influenced by injected payloads
• agent actions are constrained to explicit permissions

It’s designed around the idea that:

What it currently supports

• FastAPI-based agent gateway
• Streamlit UI for inspection and control
• Claude sessions + external agent integration
• Runtime-signed tool execution tokens
• Audit logging of all agent actions
• Scheduled tasks + memory tiers
• Local (SQLite) or Postgres deployment