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This release of `libddwaf` includes several new features designed to enhance usability and configurability for both users and rule writers. The following sections provide detailed descriptions of each significant addition.
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**Note:** This release contains **no breaking changes**.
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### Improved WAF Builder
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Although not a direct feature, the WAF builder has been improved to support empty configurations or configurations without side-effects, such as configurations lacking compatible items.
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### SSRF Operator Configuration
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New configuration settings have been introduced to provide enhanced control over the SSRF heuristic's sensitivity.
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**Heuristic Options:**
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***`authority-inspection` (default: true):**
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* When set to `true`, scans the authority component (RFC-3986::Authority) for injections.
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* If `false`, the authority is ignored unless `enforce-policy-without-injection` is enabled, in which case the authority is checked against denylists regardless of injection.
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***`path-inspection` (default: false):**
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* When set to `true`, inspects the path (RFC-3986::Path) for injections.
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* If `false`, path injections are ignored.
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***`query-inspection` (default: false):**
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* When set to `true`, inspects the query (RFC-3986::Query) for injections.
* **`output`**: Pointer to the object populated with JSON content.
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* **`json_str`**: JSON data as a string.
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* **`length`**: Length of the JSON string.
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The function returns a boolean indicating success (`true`) or failure (`false`). Both the input string and resulting object remain owned by the caller.
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### Release changelog
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#### Changes
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- Add helper for object creation from JSON string ([#430](https://github.com/DataDog/libddwaf/pull/430))
@@ -8,6 +122,8 @@ This release introduces a new operator, `hidden_ascii_match`, designed to detect
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Hidden ASCII characters have been increasingly leveraged to inject concealed instructions into prompts provided to LLMs, manipulating their behavior without explicit visibility to users or systems. The introduction of the `hidden_ascii_match` operator represents the first step toward a deterministic AI security strategy, proactively identifying and flagging these character sequences to support the effective monitoring and mitigation of potential Unicode-based prompt injection exploits.
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