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- Implemented a status bar item for LexAI with dynamic status updates (ready, processing, notReady). - Created a suggestion panel for displaying and interacting with AI-generated suggestions. - Added functionality for accepting, regenerating, and discarding suggestions within the suggestion zone. - Introduced configuration options for writing style, prompt patterns, personas, and formats. - Integrated progress indicators for long-running tasks and improved user feedback. - Established TypeScript configuration for the vscode package.
32 lines
1.2 KiB
Markdown
32 lines
1.2 KiB
Markdown
# Attack surface
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> Living inventory of everything this project has deployed and its exposure. Updated whenever infrastructure changes and before each security review, via the `attack-surface` skill. Contains **no secrets** — only references to where secrets live.
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## Assets
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| Asset | Type | Tech / version | Hosted | Auth in | Exposure | Defenses | Review cadence |
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| --- | --- | --- | --- | --- | --- | --- | --- |
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| _[none mapped yet]_ | | | | | | | |
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## Per-asset notes
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<!--
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### [asset name]
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- **Common misconfigs / CVE classes:** [platform-specific]
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- **Known exposure:** [what an attacker reaches, and from where]
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- **Secrets location:** [vault / secret-manager path — never the value]
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- **Last reviewed:** [date + result]
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-->
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## Model / harness input surface
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Injection-relevant inputs to model calls (kept in sync by the `prompt-injection-audit` skill).
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| Input avenue | Consuming model | Reachable tools | Exposure | Defense in place |
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| --- | --- | --- | --- | --- |
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| _[e.g. web fetch results]_ | | | | |
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## Gaps / unknowns
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- Inventory not yet populated. Run the `attack-surface` skill once real infrastructure exists, and `prompt-injection-audit` once the app makes model-driven tool calls.
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