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scan-redteam

scan-redteam

Routes giskard.scan vulnerability, quality, suite-generation, knowledge-base, prompt-injection, and third-party red-team scan tasks.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: scan-redteam description: "Routes giskard.scan vulnerability, quality, suite-generation, knowledge-base, prompt-injection, and third-party red-team scan tasks." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Scan and Red-Team Workflows

Use this sub-skill when the task is about giskard.scan: vulnerability scans, RAG quality scans, generated scan suites, scan scenario generators, prompt injection datasets, KnowledgeBase, or optional third-party scanners such as garak, deepteam, and private lidar.

Read First

  • API reference for verified scan entry points, signatures, generator registries, KnowledgeBase, and item listing.
  • Workflows for planning and running native Giskard scans safely, including target design, concurrency, knowledge bases, and default generator/provider prerequisites.
  • Third-party integrations for third_party_scan(tool=...), optional extras, supported item names, and skip behavior for garak, deepteam, and lidar.
  • Troubleshooting for missing credentials, empty knowledge bases, network/Hugging Face issues, commercial-use flags, target state safety, and optional scanner failures.
  • scripts/inspect_scan_api.py for a safe installed-package inspection helper. It imports giskard.scan, prints public versions/items, builds a tiny KnowledgeBase, and checks optional scanner availability without running scans or providers.

Typical Triggers

  • "Run or configure a vulnerability_scan for my chatbot."
  • "Plan a RAG quality_scan with a knowledge base."
  • "Generate a scan Suite from specific scenario generators."
  • "List built-in scan generators or garak/deepteam probes."
  • "Use prompt-injection or Hugging Face dataset scenarios."
  • "Choose between native Giskard, garak, deepteam, and lidar scanning."
  • "Explain why scan results are skipped, errored, or grouped unexpectedly."

Boundary and Routing

Include here:

  • vulnerability_scan, quality_scan, generate_suite, and DEFAULT_TARGET_MODE.
  • KnowledgeBase, Document, KnowledgeBase.from_texts, lazy embeddings, and empty-knowledge-base behavior.
  • ScenarioGenerator, SuiteGeneratorRegistry, built-in vulnerability and quality generator registries, PromptInjectionScenarioGenerator, and HuggingFaceDatasetScenarioGenerator.
  • list_scan_items("giskard" | "garak" | "deepteam") and third_party_scan(tool="garak" | "deepteam" | "lidar") prerequisites.
  • Scan execution controls: max_scenarios, seed, group_by, parallel, max_concurrency, return_exception, target_mode, and vulnerability-only commercial_use.

Route elsewhere:

  • Suite and check-result interpretation, custom checks, JUnit export, and deterministic Scenario/Suite details -> checks-evals.
  • Default generator/provider keys, provider/model routing, provider extras, and live LLM errors -> llm-providers.
  • Designing async targets, agent workflows, tools, prompt templates, and stateful chat wrappers -> agents-workflows.

Operating Rule

Do not start an expensive or live red-team scan until the user has confirmed the provider credentials, network/commercial-use stance, target concurrency safety, and optional scanner extras needed by the selected workflow. For no-key inspection, run only the bundled inspect_scan_api.py helper.

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