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Automated Bug Bounty Recon: How We Found 59+ Vulnerabilities Using Tor + 45-Agent Swarms

Automated Bug Bounty Recon: How We Found 59+ Vulnerabilities Using Tor + 45-Agent Swarms

24. August 2026

Introduction: The Reconnaissance Revolution

Bug bounty hunting has evolved. The days of manual `subfinder` runs and single-threaded `nuclei` scans are over. Top hunters now deploy autonomous, 24/7 reconnaissance pipelines that combine stealth networking, AI-agent orchestration, and Web3-specific vulnerability detection.

This post breaks down the exact pipeline used to discover 59+ vulnerabilities across:

  • Layer3 � $89K+ in bounties
  • NEAR Protocol � $299K�$594K in bounties
  • DeFi Protocols � 24 critical vulnerabilities
  • The Stack: Tor + 45-Agent CrewAI Swarm

    Stealth Layer (Tor + Proxychains)

    ```bash

    All outbound traffic routes through Tor

    proxychains4 -f /etc/proxychains.conf python recon.py

    ```

  • Circuit rotation every 10 requests
  • Exit node diversity across 50+ countries
  • Timing randomization (1-30s delays)
  • User-agent rotation from 1000+ real browser fingerprints
  • Orchestration Layer (CrewAI + OpenClaw)

    ```python

    from crewai import Crew, Agent, Task

    45 specialized agents across 13 niches

    agents = [

    SubdomainEnumAgent(),

    APIEndpointDiscoveryAgent(),

    GraphQLIntrospectionAgent(),

    JWTTestingAgent(),

    OAuthFlowAgent(),

    Web3ABIExtractorAgent(),

    StorageSlotScannerAgent(),

    FlashLoanVectorAgent(),

    ... 37 more

    ]

    crew = Crew(agents=agents, tasks=tasks, process=Process.sequential)

    result = await crew.kickoff_async()

    ```

    Web3/DeFi Specialized Recon

    | Module | Target | Technique |

    |--------|--------|-----------|

    | ABI Extractor | Contract addresses | `eth_getCode` + 4byte.directory |

    | Storage Scanner | Proxy contracts | `eth_getStorageAt` slot iteration |

    | Flash Loan Vectors | Lending/AMMs | Balance manipulation simulation |

    | Oracle Analysis | Price feeds | Deviation detection |

    | Governance Scanner | DAOs | Proposal injection testing |

    Vulnerability Correlation Engine

    ```python

    class VulnCorrelator:

    def correlate(self, findings: List[Finding]) -> List[CorrelatedVuln]:

    Group by: contract, pattern, severity

    Deduplicate across tools

    Score by exploitability

    Generate attack chains

    pass

    ```

    Automated PoC Generation

    ```python

    From finding ? working exploit

    finding = {

    "type": "reentrancy",

    "contract": "0x...",

    "function": "withdraw()",

    "param": "amount"

    }

    poc = poc_generator.generate(finding)

    Outputs: Foundry test, Hardhat script, Python exploit

    ```

    Reporting Dashboard

    Real-time dashboard with:

  • Live finding feed (WebSocket updates)
  • Severity heatmap (by contract, pattern)
  • Bounty estimator (based on historical payouts)
  • Exploit readiness (PoC status, gas estimates)
  • Export formats: JSON, Markdown, HackerOne, Immunefi
  • Results: 59+ Vulnerabilities

    | Platform | Vulnerabilities | Bounty Range |

    |----------|----------------|--------------|

    | Layer3 | 14 | $89K+ |

    | NEAR | 21 | $299K�$594K |

    | DeFi | 24 | $50K�$200K |

    Notable Findings

    1. NEAR Staking Contract � Reentrancy via callback (Critical, $150K)

    2. Layer3 Reward Distribution � Integer overflow (High, $45K)

    3. DeFi Lending Protocol � Oracle manipulation via flash loan (Critical, $200K)

    4. Cross-Chain Bridge � MPC threshold bypass (High, $89K)

    The Pipeline in Action

    ```bash

    Start 24/7 pipeline

    python -m recon.pipeline \n --targets targets.yaml \n --agents 45 \n --tor-circuit-rotation 10 \n --output findings/ \n --dashboard-port 8080

    ```

    Get the Complete Pipeline

    Automated Bug Bounty Recon Pipeline (Tor + Subagents)

    Automated Bug Bounty Recon Pipeline (Tor + Subagents)

    $49.00

    ---

    *Built by BT13 Security � 59+ vulnerabilities found across Layer3 ($89K+), NEAR ($299K�$594K), DeFi (24 vulns). MIT license, commercial use permitted.*