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chore(aaif): rename a bunch of repository references (#8152)

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Signed-off-by: Michael Neale <michael.neale@gmail.com>
Co-authored-by: Michael Neale <michael.neale@gmail.com>

continuing migration to aaif
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Jack Amadeo
2026-04-07 01:34:48 -04:00
committed by GitHub
parent 0b080faad5
commit 583acd4335
236 changed files with 1097 additions and 962 deletions
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documentation/docs/guides/security/prompt-injection-detection.md
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@@ -27,7 +27,7 @@ These checks provide a safeguard, not a guarantee. They detect known patterns bu
When enabled, goose uses a multi-layered approach to detect threats before they run:
1. **Tool call is intercepted and analyzed** - When goose prepares to execute a tool, the security system extracts the tool parameter text and checks it against [threat patterns](https://github.com/block/goose/blob/main/crates/goose/src/security/patterns.rs). If ML-based detection is enabled, it also uses machine learning to analyze the semantic content of the tool call and recent conversation messages to better understand context and reduce false positives.
1. **Tool call is intercepted and analyzed** - When goose prepares to execute a tool, the security system extracts the tool parameter text and checks it against [threat patterns](https://github.com/aaif-goose/goose/blob/main/crates/goose/src/security/patterns.rs). If ML-based detection is enabled, it also uses machine learning to analyze the semantic content of the tool call and recent conversation messages to better understand context and reduce false positives.
2. **Risk is assessed** - Detected threats are assigned confidence scores
3. **Execution pauses** - Threats that exceed your configured threshold need your decision
4. **Security alert appears** - The alert displays the confidence level, a description of the finding, and a unique finding ID. For example: