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hackerone

HackerOne bug bounty automation - parses scope CSVs, deploys parallel pentesting agents per asset, validates PoCs, and generates platform-ready submission reports.

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transilienceai/communitytools스타 595(GitHub 595 + cccskills 0)

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설치 방법 보기

포함된 파일(7)

  • SKILL.md7.7 KB
  • reference/INTEGRATION_GUIDE.md7.3 KB
  • reference/sensitive-data-tracking.md4.1 KB
  • tools/__init__.py0 B
  • tools/csv_parser.py5.2 KB
  • tools/report_validator.py9.6 KB
  • tools/sensitive_data_tracker.py15.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

HackerOne Bug Bounty

Automates: scope parsing → parallel testing per asset → authoritative finding validation → submission reports.

Quick start

  1. Input: HackerOne program URL or scope CSV.
  2. Parse scope and program guidelines.
  3. Spawn one coordinator per eligible asset (parallel).
  4. Each coordinator runs the standard engagement flow (see skills/coordination/SKILL.md).
  5. Run the validate-findings workflow per asset (authoritative submission gate). Generate HackerOne reports from the validated set ONLY — never submit a finding that is not VALID/REPAIRED.

Scope CSV format

Expected columns:

  • identifier — asset URL/domain.
  • asset_type — URL, WILDCARD, API, CIDR.
  • eligible_for_submission — must be true.
  • max_severity — critical / high / medium / low.
  • instruction — asset-specific notes.

Parse with skills/hackerone/tools/csv_parser.py. Filter for eligible_for_submission=true.

Agent deployment

One coordinator per asset, spawned in parallel:

coordinator_role = Read("skills/coordination/SKILL.md")
Agent(prompt=f"{coordinator_role}\n\nTARGET: {asset_url}\nSCOPE: {program_guidelines}\nOUTPUT_DIR: ...",
      run_in_background=True)

10 assets → 10 parallel coordinators (~2-4 h vs 20-40 h sequential). Each coordinator follows skills/coordination/SKILL.md and reference/role-matrix.md.

Finding validation (authoritative submission gate)

Every finding requires poc.py (executable exploit), poc_output.txt (timestamped execution proof), manual repro steps, and evidence (screenshots / HTTP captures / video). This is the input the validator consumes.

After each asset's coordinator returns, the orchestrator runs the validate-findings workflow for that asset and submits ONLY findings it marks VALID or REPAIRED:

v = Workflow(name="validate-findings", args={
    "output_dir": asset_output_dir,   # the coordinator's OUTPUT_DIR
    "target": asset_url,
    "business_tier": "revenue",       # production/external bug-bounty scope; else "unknown"
    "votes": 3,                       # adversarial refuters per finding (bounty = stricter)
    "repair": True,                   # regenerate broken/absent PoCs so each finding has a runnable evidence script
    "strict": True,                   # one failed gate => REJECTED
})
# v.counts -> {total, valid, repaired, rejected}; v.validated[] / v.rejected[]
# Verdicts at {asset_output_dir}/artifacts/validated/{id}.json (+ false-positives/).
# Asset report at {asset_output_dir}/reports/validation-report.md.

validate-findings is the authoritative gate because it directly preempts the most common HackerOne rejections: it verifies each CVE against NVD + a recomputed CVSS base score (from the vector) + CISA KEV + the vendor advisory, runs (and repairs) every PoC until it emits the evidence that proves the issue, recomputes the risk/severity, corroborates every claim against raw evidence, and kills false positives via adversarial refutation.

The orchestrator is the only layer that runs this workflow (it is top-level; the workflow is one level below — legal nesting). To avoid double work, coordinators may treat their interleaved per-finding validators (run the instant each candidate is materialized) as a provisional self-check; the standalone validate-findings verdict is authoritative for submission. A REJECTED finding is a false positive — it never enters a submission, an appendix, or a count; its artifacts/false-positives/{id}.json is the sole record. Likewise a coordinator-dropped candidate (uncured DEMOTED, in artifacts/dropped/) is never submitted.

The HackerOne PoC contract is a superset of the standard finding contract (skills/coordination/reference/validator-role.md).

Submission report format

Build each report from a validated finding only. Required sections per HackerOne standard:

  1. Summary (2-3 sentences).
  2. Severity (CVSS + business impact; v4.0 primary, v3.1 → v3.0 → v2.0 fallback) — use the score validate-findings recomputed from the vector and the risk bucket it assigned, not a hand-typed number.
  3. Steps to Reproduce (numbered, clear) — mirror the validated verification-script.py.
  4. Visual Evidence (from evidence/validation/).
  5. Impact (realistic attack scenario).
  6. Remediation (actionable fixes).

Validate report format with skills/hackerone/tools/report_validator.py (complements the finding validation).

Output structure

Standard OUTPUT_DIR (skills/coordination/reference/output-discipline.md) plus a per-asset reports/submissions/ containing the platform-ready markdown. validate-findings writes the verdicts under artifacts/validated|false-positives/ and the asset reports/validation-report.md.

{OUTPUT_DIR}/
├── findings/
│   └── finding-NNN/evidence/validation/   # validate-findings proof packages
├── reports/
│   ├── submissions/                        # built ONLY from artifacts/validated/
│   │   ├── H1_CRITICAL_001.md
│   │   └── H1_HIGH_001.md
│   ├── validation-report.md                # validate-findings asset report
│   └── SUBMISSION_GUIDE.md
├── recon/
├── logs/
└── artifacts/
    ├── validated/          # {id}.json — submit these
    └── false-positives/    # {id}.json — never submit these

Program selection

High-value: new programs (< 30 days), fast response (< 24 h), high bounties, large attack surface. Avoid: slow response (> 1 week), low bounties, restrictive scope.

Submission checklist

  • validate-findings verdict = VALID or REPAIRED (artifacts/validated/{id}.json exists). Never submit a REJECTED finding.
  • CVSS recomputed from the vector (v4.0 primary; v3.1 → v3.0 → v2.0 fallback) and matching NVD when a CVE applies (evidence/validation/cve-verification.md).
  • Working PoC with poc_output.txt (the validator re-ran/repaired it and confirmed the evidence token).
  • Step-by-step reproduction.
  • Visual evidence.
  • Realistic impact (risk score/bucket from evidence/validation/risk-assessment.md).
  • Remediation guidance.
  • Sensitive data sanitized.
  • Asset is eligible_for_submission=true.

Common rejections (preempt)

RejectionPrevention
Out of ScopeVerify eligible_for_submission=true and asset-type match
Cannot Reproducevalidate-findings re-runs (and repairs) the PoC 3× and requires a vuln-class evidence token — only reproducible findings pass the gate
DuplicateSearch disclosed reports before submission; submit quickly
Insufficient ImpactDocument realistic attack scenario; validate-findings recomputes risk/severity so the rating is defensible
Incorrect severity / CVSSvalidate-findings recomputes the base score from the vector and cross-checks NVD + KEV; any mismatch is flagged before you submit

Tools

  • skills/hackerone/tools/csv_parser.py — parse HackerOne scope CSVs.
  • validate-findings workflow — authoritative per-asset finding validation (NVD/CVSS-math/KEV/exploit-run/repair/risk/adversarial). The submission gate; run once per asset.
  • skills/hackerone/tools/report_validator.py — validate report format completeness (the 6 submission sections). Complements validate-findings (which validates the finding); run it on each report built from a validated finding.
  • skills/coordination/SKILL.md — coordinator scaffold.

Usage

/hackerone <program_url_or_csv_path>

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