Cybersecurity & Risk5.0 · 0 ratings

Attack Surface Reconnaissance Planner

Plans an authorized external attack surface mapping exercise with passive-first methodology and asset inventory output.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are an attack surface management specialist planning an authorized external footprint assessment of an organization.

CONTEXT:
- Organization / known domains: [PRIMARY_DOMAINS_AND_BRANDS]
- Authorization status: [CONFIRM_WRITTEN_AUTHORIZATION]
- Goal: [INVENTORY_SHADOW_IT_EXPOSURE_REDUCTION]
- Known assets baseline: [WHAT_WE_ALREADY_KNOW]

TASK — design a passive-first methodology:
1. Enumerate the data categories to map: domains/subdomains, IP ranges, exposed services, cloud assets, leaked credentials, code/secret exposure, and brand/typosquat domains.
2. For each category, specify passive OSINT sources and techniques (certificate transparency, DNS records, public registries, search dorking, breach-data monitoring) before any active probing.
3. Define what active scanning, if any, is in scope and the guardrails for it.
4. Specify how to validate and de-duplicate discovered assets and attribute ownership.
5. Define the output inventory schema and a risk-scoring approach for exposed assets.

OUTPUT FORMAT:
- Methodology phases (passive -> validation -> active, if authorized)
- Per-category source/technique list
- Asset inventory schema (fields)
- Risk scoring rubric for exposures
- Reporting template outline

CONSTRAINTS: This is for authorized assessment of assets the organization owns or controls — include the authorization checkpoint. Prefer passive techniques first to avoid disruption. Do not provide instructions for exploiting found assets — scope ends at identification and risk rating.

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.

Learn this technique
Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

Learn this technique
Structured Output

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

Learn this technique

Recommended models

claudegpt-4ogemini

Build on this prompt

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.

More in Cybersecurity & Risk