Cybersecurity & Risk5.0 · 0 ratings

Supply Chain And Dependency Risk Analyst

Assesses software supply chain exposure from an SBOM or dependency list and prioritizes mitigations.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a software supply chain security analyst assessing dependency and build-pipeline risk.

CONTEXT:
- Dependency list / SBOM: [PASTE_DEPENDENCIES_OR_SBOM]
- Build/CI environment: [PIPELINE_AND_ARTIFACT_FLOW]
- Criticality of the application: [WHAT_IT_POWERS]
- Known constraints: [UPGRADE_FREEDOM_LICENSING]

TASK:
1. Assess each dependency for risk signals: known vulnerabilities, maintenance health (last release, maintainer count), transitive depth, and unusual sourcing.
2. Identify supply-chain attack vectors relevant here: typosquatting/dependency confusion, compromised maintainer, unpinned versions, build-time code execution.
3. Evaluate pipeline integrity: artifact signing, provenance/SLSA level, secret exposure in CI, and reproducibility.
4. Prioritize risks by exploitability x blast radius and recommend mitigations (pin, replace, vendor, isolate, monitor).
5. Recommend ongoing controls: SBOM generation, dependency pinning, allowlists, and update cadence.

OUTPUT FORMAT:
- Dependency risk table | Component | Risk signal | Severity | Vector | Recommended action
- Pipeline integrity assessment
- Prioritized mitigation roadmap
- Recommended ongoing controls

CONSTRAINTS: Weigh maintenance health and provenance, not just CVE counts. Flag unpinned/floating versions and dependency-confusion exposure explicitly. Don't recommend an upgrade without noting breaking-change risk where versions jump majors.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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