agentleFS
gl1tch0x1gl1tch0x1/SecAgent/skills/HuntPlanning/SKILL.md

HuntPlanning

Skill2 starsChanged 44 days agoMITView on GitHub

Use this skill to turn an authorized target and a bounded inventory into testable hypotheses. It produces a plan, never a claim that a vulnerability exists. Output a compact JSON plan with scope, assumptions, hypotheses, required_capabilities, budget, and coverage_gaps. Each hypothesis should include its proof policy and expected evidence.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill to turn an authorized target and a bounded inventory into testable hypotheses.

    line 3

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Hunt Planning

Use this skill to turn an authorized target and a bounded inventory into testable hypotheses. It produces a plan, never a claim that a vulnerability exists.

  1. State the approved domains, identities, methods, request cap, rate limit, and deadline. Mark missing inputs as coverage gaps.
  2. Map entry points by trust boundary: anonymous to authenticated, user to admin, browser to API, API to downstream service, and application to cloud resources.
  3. Rank hypotheses by impact, likelihood, evidence availability, and traffic cost. Prefer a small number of high-value tests over broad payload spraying.
  4. For each hypothesis, specify the baseline, one controlled variation, a negative control, the expected observation, and the stop condition.
  5. Require separate identities for authorization claims, browser execution for XSS, an operator-controlled callback for blind behavior, and a state read plus cleanup contract for write methods.
  6. Record unexplored paths and capability gaps as leads. Do not promote a plan or heuristic to a confirmed finding.

Output a compact JSON plan with scope, assumptions, hypotheses, required_capabilities, budget, and coverage_gaps. Each hypothesis should include its proof policy and expected evidence.

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