Built for teams building with LLMs.

Detects language that tries to override system instructions, hijack context, or insert adversarial directives through user input.

Catches jailbreak attempts, uncensored-mode requests, and language designed to remove the model's safety rails.

Flags prompts that request credentials, API keys, PII, internal data, or anything that should never leave the model context.

Identifies manipulation patterns that try to coerce the model into unsafe actions by appealing to authority or urgency.

Spots instructions that fetch or summarise external URLs, which could inject hostile content into the model's context window.

Detects over-broad tool grants — shell access, filesystem writes, unrestricted API calls — that increase blast radius.

Flags prompts likely to produce dangerous code, SQL, or markup without proper sanitisation guidance.

Catches attempts to bias future model behaviour or embed persistent instructions through crafted inputs.

Prompts that explicitly invite the model to fabricate facts, citations, statistics, or data it cannot verify.

Instructions that may cause the model to produce contradictory or internally inconsistent factual claims across a response.

Ambiguous or contradictory instructions that reduce the model's ability to complete tasks reliably and predictably.

Prompts likely to produce wildly varying outputs across repeated runs, making results hard to test or depend on.

Instructions that prevent the model from appropriately refusing unsafe or out-of-scope requests.

Missing or ambiguous output format constraints that could cause inconsistent or unparseable responses downstream.