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Bounty Hunter Pro

该 Skill 面向已授权目标的漏洞赏金扫描:用证书透明度日志枚举子域,分析 JS 中的密钥,结合熵过滤和 LLM 做漏洞研判,输出增量发现、分析记录与 Markdown 报告,并可通过消息通道告警。仅附带说明文档,扫描脚本和工具未包含。

lugave11
lugave11
热度 93.38
最近更新 2026-05-18 12:13:08
分类:安全依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:自动化脚本 / 数据处理 / 报告撰写 / 研究 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add bounty-hunter-pro
Metadata
name
bounty-hunter-pro
description
Autonomous bug bounty hunting with scope safety. Scans targets for subdomains, secrets, vulnerabilities. Uses Certificate Transparency logs, JS analysis, entropy-based secret detection. LLM-powered vulnerability analysis. ALWAYS respects authorized targets only.
version
1.0.0
author
Jeremiah
tags
["security","bug-bounty","penetration-testing","automation"]

Bounty Hunter Pro

Purpose

Autonomous vulnerability scanning for authorized bug bounty programs.

⚠️ CRITICAL: Scope Safety

NEVER scan targets outside [AUTHORIZED_TARGETS]

Before any scan:

  1. Verify target is in authorized list
  2. Log the scope check
  3. Only proceed if authorized

Components

1. nightwatch.py — Scanner

  • Certificate Transparency (crt.sh) for subdomains
  • JS file analysis for secrets
  • Multi-threaded (10 workers default)
  • Outputs to findings_incremental.json

2. analyze_daemon.py — Analyzer

  • Watches findings_incremental.json
  • Entropy filtering to reduce false positives
  • Two-stage LLM analysis:
    • Fast: qwen2.5-coder:1.5b
    • Deep: glm-5:cloud
  • Outputs to live_analysis.md

3. watchdog.py — Alerter

  • Monitors for CRITICAL findings
  • Sends alerts via OpenClaw message bus

Setup

# Install tools
cd ~/workspace/bounty_hunting/tools
unzip subfinder.zip
unzip httpx.zip
unzip nuclei.zip

# Configure authorized targets
echo "example.com" > ~/workspace/bounty_hunting/authorized_targets.txt
echo "*.example.com" >> ~/workspace/bounty_hunting/authorized_targets.txt

Usage Prompt

Run bounty hunt on [TARGET]. Target must be in authorized list.

1. Verify [TARGET] is authorized
2. Run subdomain enumeration
3. Scan each subdomain for:
   - Exposed secrets in JS
   - Misconfigurations
   - Known vulnerabilities
4. Analyze findings with LLM
5. Generate report to ~/workspace/reports/security/[TARGET]/

Directory Structure

~/workspace/bounty_hunting/
├── authorized_targets.txt    # ONLY these can be scanned
├── nightwatch.py            # Main scanner
├── analyze_daemon.py        # LLM analyzer
├── watchdog.py              # Alert system
├── findings_incremental.json # Raw findings
├── live_analysis.md         # Analyzed results
└── tools/
    ├── subfinder
    ├── httpx
    └── nuclei

Output Format

Reports saved to: ~/workspace/reports/security/[TARGET]/YYYY-MM-DD.md

# Security Scan — [TARGET] — [DATE]

## Scope
- Authorized: [TARGET]
- Subdomains found: X
- Endpoints scanned: Y

## 🔴 CRITICAL
1. Finding — Severity — Location — Recommendation

## 🟠 HIGH
1. Finding — Severity — Location — Recommendation

## 🟡 MEDIUM
1. Finding — Severity — Location — Recommendation

## 🟢 INFO
1. Finding — Severity — Location — Recommendation

## Next Steps
1. [Recommended action]

Safety Guards

# ALWAYS check before scanning
def is_authorized(target):
    with open("authorized_targets.txt") as f:
        authorized = [line.strip() for line in f]
    return any(target.endswith(auth) or target == auth for auth in authorized)

# FAIL SAFE
if not is_authorized(target):
    raise ValueError(f"UNAUTHORIZED: {target} not in authorized_targets.txt")

Cron Schedule

# Daily scan at 2am (low-traffic time)
0 2 * * * cd ~/workspace/bounty_hunting && python nightwatch.py

Known Limitations

  • CPU-only (no CUDA)
  • Rate limiting may slow scans
  • Some false positives in entropy detection