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A learned relaxation includes hostile traffic

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A learned relaxation includes hostile traffic

A fictional web application is protected by a policy linked to a Web App Firewall profile. During an observation period, the supplied traffic includes ordinary order submissions and a request from an untrusted actor containing an unexpected field pattern. A learning view proposes a relaxation covering that field, and a colleague wants to accept every suggestion because the product has already seen the traffic. The application owner can provide a documented legitimate field format and representative test requests. No policy is changed in this exercise and no suspicious payload is sent. The task is to compare observed traffic with trusted requirements, define the scope of any justified exception and retain evidence about legitimate service behavior and security outcomes.

1. Why is the learned proposal insufficient by itself?

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Observation does not establish legitimacy. Untrusted input may influence suggestions, so compare the field and proposed relaxation with trusted application requirements and representative authorized evidence.

2. What distinguishes a controlled exception?

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Use the narrowest justified application/field scope, record ownership and reason, test enforcement and legitimate workflows, and preserve verification and recovery. Do not disable the whole check merely to eliminate an alert.