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Show HN: ReasonGate- An explainable gate that blocks LLM prompt injection

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Why This Matters

ReasonGate introduces an explainable security gate designed to prevent prompt injection attacks in large language model applications. Unlike traditional black-box filters, it provides transparent reasons for each decision, enabling better auditing and trust. This advancement is crucial for safeguarding sensitive operations and maintaining compliance in the rapidly evolving AI landscape.

Key Takeaways

ReasonGate

An explainable security gate for LLM applications. Every decision carries a reason you can audit.

See it prevent a real breach not just flag a bad string

A bank support agent has tools ( send_email , transfer_funds ) and is handed a customer record with a hidden instruction inside it (indirect injection the dominant attack on RAG / agents). Same attack, one variable: the shield.

Shield Record Result OFF poisoned 🔴 breach the customer record is emailed to the attacker and $84,200 is wired out (real side effects, written to disk) ON poisoned 🟢 blocked same input; the injection is caught before the model is ever called; zero side effects ON clean 🟢 allowed the agent answers normally (not a dumb blocklist)

The proof isn't the agent's words it's the side effects that did not happen. Run it yourself (deterministic, no API key needed); it's a CI-enforced invariant, not a screenshot:

python -m examples.stakes_demo.run # see examples/stakes_demo/

▶ Try the live demo — paste a prompt, watch it get blocked with a reason and an auditable record

See it block a direct attack or a hidden, zero-width-obfuscated one — runs on the zero-dependency core, no API keys, no data leaves the server.

Prompt injection is the top item on the OWASP LLM Top 10 for a structural reason: a language model reads instructions and data through the same channel and cannot reliably tell them apart. You do not fix that inside the model. You put a gate in front of it.

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