Detects Vertex AI prompt-response logs where a candidate safety_ratings.probability is HIGH or MEDIUM. Those values are stronger signals than NEGLIGIBLE or LOW alone. Requires the request to include safetySettings so ratings are logged.

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Detects three or more Vertex AI GenerateContent replies in 60 minutes whose assistant text indicates a refusal (cannot fulfill/assist/help/answer, unable to assist, decline the request, against my guidelines, and similar), aggregated by project and model. Prompt-response logs lack a stable caller identity, so this is a project-wide refusal burst signal — pivot to auditlogs for principal/IP attribution.

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Detects Vertex AI GenerateContent responses whose candidate finish_reason is SAFETY. That value is emitted when Gemini safety filters stop generation. Unlike textual refusals (finish_reason STOP), SAFETY means the provider blocked or truncated the completion.

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Detects three or more completed assistant refusals from the same client, API Management subscription, and model. Matching replies finished on their own (finish_reason stop) and declined the prompt. A burst means that caller kept sending prompts the model will not answer.

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Identifies multiple successive failed attempts to use denied model resources within AWS Bedrock. This could indicated attempts to bypass limitations of other approved models, or to force an impact on the environment by incurring exhorbitant costs.

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Identifies multiple validation exeception errors within AWS Bedrock. Validation errors occur when you run the InvokeModel or InvokeModelWithResponseStream APIs on a foundation model that uses an incorrect inference parameter or corresponding value. These errors also occur when you use an inference parameter for one model with a model that doesn't have the same API parameter. This could indicate attempts to bypass limitations of other approved models, or to force an impact on the environment by incurring exhorbitant costs.

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Identifies multiple violations of AWS Bedrock guardrails within a single request, resulting in a block action, increasing the likelihood of malicious intent. Multiple violations implies that a user may be intentionally attempting to cirvumvent security controls, access sensitive information, or possibly exploit a vulnerability in the system.

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Identifies multiple violations of AWS Bedrock guardrails by the same user in the same account over a session. Multiple violations implies that a user may be intentionally attempting to cirvumvent security controls, access sensitive information, or possibly exploit a vulnerability in the system.

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Identifies multiple AWS Bedrock executions in a one minute time window without guardrails by the same user in the same account over a session. Multiple consecutive executions implies that a user may be intentionally attempting to bypass security controls, by not routing the requests with the desired guardrail configuration in order to access sensitive information, or possibly exploit a vulnerability in the system.

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Detects repeated high-confidence 'BLOCKED' actions coupled with specific 'Content Filter' policy violation having codes such as 'MISCONDUCT', 'HATE', 'SEXUAL', INSULTS', 'PROMPT_ATTACK', 'VIOLENCE' indicating persistent misuse or attempts to probe the model's ethical boundaries.

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Detects repeated compliance violation 'BLOCKED' actions coupled with specific policy name such as 'sensitive_information_policy', indicating persistent misuse or attempts to probe the model's denied topics.

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Detects repeated compliance violation 'BLOCKED' actions coupled with specific policy name such as 'topic_policy', indicating persistent misuse or attempts to probe the model's denied topics.

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Detects repeated compliance violation 'BLOCKED' actions coupled with specific policy name such as 'word_policy', indicating persistent misuse or attempts to probe the model's denied topics.

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