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A model can be trained to behave well. The system around it still needs checks, limits, and ways to recover. Explore the roles each layer can play.
Check incoming requests and external content for risk signals.
Flag suspicious instructions in a retrieved webpage.
A suspicious-input signal can miss a new attack or flag a legitimate quotation. It should not be treated as permission to trust everything that passed.
Try a malicious instruction embedded in a long document and a benign document discussing the same attack. Record both missed detections and unnecessary interruptions.
The sources behind this page, with a reason to open each one. Practical examples and recommendations are our editorial interpretation.
Threat examples and layered defenses for applications that process untrusted text.
Explains binary attack detection, the 512-token window and differences between the 22M and 86M versions.
Sources reviewed 13 September 2026. Product documentation can change. How we use evidence
Useful for interpreting language, classifying ambiguous content, and judging policy fit.
Meet specialized modelsA spending limit or restricted file path can be enforced directly, without asking a model to remember it.
Understand permissionsReview, oversight, and feedback help address ambiguity, investigate failures, and set appropriate goals.
Explore human oversight