Security asset search workflow
Skill Evan-Joseph/agent-workflow-skills/skills/security-asset-search-workflow
Reusable Agent Skills for research figures, frontend refreshes, design workflows, model consultation, social research, and security asset searches.
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Plan and document authorized internet-asset searches. Use when composing queries for public asset search engines, checking exposed services, inventorying owned infrastructure, triaging search results, or turning raw findings into a source-backed security note.
SKILL.md
4.1 KB, 772 tokens by cl100k_base, as published. Nobody here has run it
Security Asset Search Workflow
Use this skill for authorized asset discovery, exposure checks, and defensive research using public internet-asset search tools.
The goal is not to collect the biggest result set. The goal is to ask a scoped question, keep evidence, and produce findings that another person can verify.
Scope first
Before writing queries, establish:
- target organization, domain, IP range, product, or technology
- authorization boundary
- time window
- allowed data sources
- what counts as a finding
- what should be excluded
If the scope is unclear, stop and ask for it. Do not expand from a single domain or product name into unrelated infrastructure without a reason.
Good use cases
- inventorying exposed assets for a domain or known IP range
- checking whether a technology, banner, certificate, or title appears in owned infrastructure
- finding stale test environments or forgotten services
- comparing results from several asset search engines
- turning search results into a short defensive report
- adapting old query notes to a different provider's syntax
Do not use this skill as a substitute for direct validation against the owner's systems, logs, or configuration.
Workflow
1. Write the search question
Use one sentence:
- "Find public web services under this owned domain that expose staging or admin-like titles."
- "Check whether this certificate name appears outside the approved IP ranges."
- "Inventory public assets that mention this product banner and belong to the approved organization."
2. Build query blocks
Break the search into small blocks:
- identity: domain, organization, certificate, ASN, IP range
- service: protocol, port, product, title, header, favicon, banner
- environment: staging, dev, test, admin, dashboard, debug
- exclusion: CDN, shared hosting, unrelated brands, known false positives
- time: first seen, last seen, recently updated if the provider supports it
Use provider-specific syntax only after the blocks are clear.
Read references/query-design.md when building or translating queries.
3. Run narrow first
Start with narrow queries and small result limits.
For each run, record:
- provider
- query string
- retrieval date
- result count if available
- fields requested
- pagination or cursor state if used
- known limitations
Avoid pulling large result sets unless the task needs it.
4. Normalize results
For each candidate asset, keep:
- host or URL
- IP
- port and protocol
- title or service name
- evidence field that matched
- source provider
- retrieval date
- confidence
- verification gap
Do not treat a search-engine row as final proof. Asset search indexes can be stale, merged, partial, or wrong.
5. Verify and classify
Classify candidates:
- in scope and confirmed
- likely in scope, needs owner-side verification
- false positive
- out of scope
- stale or inconclusive
Use direct owner-approved checks when needed. Do not interact with systems outside the authorized boundary.
Read references/evidence-and-reporting.md before writing a report.
Output
Default report shape:
| Asset | Why it matched | Evidence | Scope status | Confidence | Next check |
|---|
Then add:
- query summary
- likely false positives
- unresolved verification gaps
- recommended next action
Boundaries
- Keep authorization explicit.
- Do not include working credentials or private keys in queries, notes, or reports.
- Do not rely on a single search provider when the finding has operational impact.
- Do not use stale indexed data as proof of current exposure.
- Do not include exploitation steps unless the user explicitly asks for an authorized validation plan.
What ships with it: 3 files
4.0 KB alongside SKILL.md
agents/
- openai.yaml252 B
references/
- evidence-and-reporting.md2.0 KB
- query-design.md1.8 KB
Gives 0 of the 12 instructions most automation workflows skills give in 772 tokens
Counted across 745 of the 1,008 authors here whose files we hold, read 2026-08-07
- Write conventional commit messagesin 36 of 745, across 35 files
- Delete branches after mergein 30 of 745, across 21 files
- Make atomic commitsin 25 of 745, across 15 files
- Write minimal code to pass testsin 22 of 745, across 10 files
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- Use try-catch for error handlingin 20 of 745, across 8 files
- Run tests before committingin 20 of 745, across 12 files
- Write tests before implementationin 20 of 745, across 8 files
- Configure branch protection rulesin 19 of 745, across 5 files
- Explain the why in commit messagesin 19 of 745, across 9 files
- Refactor code while tests remain greenin 19 of 745, across 6 files
- Interact with elements using refsin 19 of 745, across 11 files
Said here and by no other author read
- establish scope before writing queries
- stop and ask if scope is unclear
- build queries from discrete logical blocks
- read query design references when building queries
- run narrow queries first
- record query metadata for each run
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.