hackerone
HackerOne bug bounty automation - parses scope CSVs, deploys parallel pentesting agents per asset, validates PoCs, and generates platform-ready submission…
Skill by gohilrajbha0312
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What's inside
- Skill name
hackerone- Description
- HackerOne bug bounty automation - parses scope CSVs, deploys parallel pentesting agents per asset, validates PoCs, and generates platform-ready submission reports.
- License
- MIT
- Instructions
- 134 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (7)
- SKILL.md
- INTEGRATION_GUIDE.md · reference/
- sensitive-data-tracking.md · reference/
- __init__.py · tools/
- csv_parser.py · tools/
- report_validator.py · tools/
- sensitive_data_tracker.py · tools/
SKILL.md (first lines)
# 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:
```python
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`:**
```python
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 inline P5 finding-validators as a provisional self-check; the `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.
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 v3.1 + business impact) — 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 v3.1 **recomputed from the vector** 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)
| Rejection | Prevention |
|-----------|------------|
| Out of Scope | Verify `eligible_for_submission=true` and asset-type match |
| Cannot Reproduce | `validate-findings` re-runs (and repairs) the PoC 3× and requires a vuln-class evidence token — only reproducible findings pass the gate |
| Duplicate | Search disclosed reports before submission; submit quickly |
| Insufficient Impact | Document realistic attack scenario; `validate-findings` recomputes risk/severity so the rating is defensible |
| Incorrect severity / CVSS | `validate-findings` recomputes the base score from the vector and cross-checks NVD + KEV; any mismatch is flagged before you submit |From gohilrajbha0312/Pentest-tool, MIT.
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- Last commit (this folder)
- Jun 9, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/gohilrajbha0312/Pentest-tool
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
hackerone skill. Agent Mart. https://agentmart.dev/skills/gohilrajbha0312-hackerone (last updated 2026-10-24)