recon-modular - 🛡️ AI-powered reconnaissance framework unifying 13

项目说明

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🛡️ OMNISCIENT V3

The Ultimate Reconnaissance & Ad Simulation Framework

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> ⚠️ CRITICAL DISCLAIMER
> This tool is provided exclusively for authorised security assessments, educational use, and bug bounty engagements where you have explicit written permission to test.
> Unauthorised scanning, exploitation, or data exfiltration the Computer Fraud and Abuse Act (CFAA), GDPR, and similar laws worldwide.
> The de assume zero liability for misuse. Always obtain proper appro targeting any system.

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📖 Table of Contents

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🌟 Why Omniscient?

Modern attack surfaces are massive, dynamic, and increasingly complex. Traditional reconnaissance workflows are:

Omniscient V3 sol challenges by:

Whether you're a bug bounty hunter, red teamer, security researcher, or De engineer, Omniscient gives you the edge to disco faster, deeper, and more reliably than e.

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🚀 Key Features

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#### 🔍 Hyper‑Deep Reconnaissance

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#### 🧠 AI‑Augmented Analysis

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#### 🚀 Distributed & High‑Performance

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#### 🛡️ Stealth & E

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#### 📜 Blockchain Auditing & Compliance

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#### 📊 Multi‑Format Reporting

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📸 Pipeline

All phases run in parallel where possible, with dynamic thread allocation and Redis‑based caching for optimal speed.

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⚡ Quick Start

On first run, the script will attempt to auto‑install missing tools.
For a controlled installation, follow the full steps below.

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📦 Requirements

· Operating System: Linux (Kali, Ubuntu 20.04+, Parrot, Debian) – WSL2 supported with limitations.
· Architecture: x86_64 (ARM64 supported for most tools).
· Dependencies: 130+ external tools – see REQUIRED_TOOLS inside the script. The script auto‑installs missing ones.
· API Keys (optional, but highly recommended for full power):
· Shodan, ZoomEye, Censys, SecurityTrails, , GreyNoise, OTX, BinaryEdge, Netlas, Recorded Future, ThreatConnect, Dark Web API, etc.
· Hardware Minimum: 8 GB RAM, 4 CPU cores, 50 GB free disk.
· GPU (optional): NVIDIA GPU with CUDA 11+ for AI acceleration.
· Tor (optional): for anonymous routing and dark web modules.
· Wordlists: Place your custom wordlists in /opt/wordlists (subdomain, permutation, directory, user/pass lists).

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🔧 Installation

1. System Dependencies

2. Install Go (required for many modern security tools)

3. Install Core Recon Tools (example subset)

The script auto‑installs most tools, but you can pre‑install essentials:

4. Python AI Dependencies

5. API Key Configuration

Create a secured file (e.g., /etc/recon_api_keys.conf) with permissions 600:

Then source it: source /etc/recon_api_keys.conf.
Alternatively, use HashiCorp Vault (set and ) or YubiKey OATH‑TOTP (set YUBIKEY_ID). The script will attempt to load keys from the chosen source.

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⚙️ Configuration

All behaviour is controlled . Export them before execution or set them inline.

Description Default
THREADS Number of parallel threads 50000
RESOLVERS Comma‑separated DNS resolvers 8.8.8.8,1.1.1.1,9.9.9.9,…
OUTPUT_DIR Base output directory recon-<timestamp>
ENCRYPT_DUMPS AES‑384 encrypt sensiti true
ENCRYPT_KEY AES key (auto‑generated if not set) random 48 bytes
POST_QUANTUM_KEY Kyber‑1024 key for quantum‑safe ops auto‑generated
SLACK_WEBHOOK Slack incoming webhook URL (empty)
DISCORD_WEBHOOK Discord webhook URL (empty)
SIEM_WEBHOOK SIEM/Webhook endpoint for real‑time events (empty)
API_KEYS_FILE Path to API keys file /etc/recon_api_keys.conf
HashiCorp Vault address
Vault authentication token (empty)
KEYBASE_USER Keybase user for key exchange (empty)
YUBIKEY_ID YubiKey OATH ID for TOTP (empty)
HSM_DEVICE HSM device path /dev/hsm0
TOR_ENABLED Route all traffic through Tor true
STEALTH_MODE Enable anti‑detection (random UA, proxy rotation) true
OBFUSCATE_FINGERPRINT Randomise TLS/JA3 fingerprints true
DISTRIBUTED_MODE Distribute tasks across a cluster true
GPU_ENABLED Use GPU for AI models true
TPU_ENABLED Use TPU (Coral) for AI acceleration false
AI_MODEL_DIR Path to custom AI model scripts /opt/ai_models
C2_SERVER C2 server for beaconing (red‑team) (empty, disabled)
PERSISTENCE_ENABLED Enable persistence mechanisms (educational) false
SUPPLY_CHAIN_SCAN Perform supply chain analysis true
QUANTUM_SIGN Use Kyber‑1024 quantum‑safe signatures true
STEGANOGRAPHY_ENABLED Enable steganographic exfiltration true
C Perform C true
COMPLIANCE_CHECK targets against bug bounty scopes true
SIGN_LOGS Cryptographically sign all logs true
SIGN_KEY RSA‑8192 signing key (auto‑generated) auto‑generated
CACHE_DIR Redis cache directory /tmp/recon_cache
REDIS_HOST Redis host localhost
REDIS_PORT Redis port 6379
REDIS_CLUSTER Enable Redis cluster mode true
RATE_LIMIT Rate limit for scanning tools 1000
TIMEOUT Command timeout 60s
RETRY_COUNT Number of retries on failure 10
REPORT_FORMATS Comma‑separated report formats pdf,json,csv,html,graph,vr
BLIND_XSS Blind XSS callback URL
BLOCKCHAIN_NODE Ethereum node RPC URL
SMART_CONTRACT_ADDR Smart contract for audit logging (empty)
SCHEDULE_MODE Scheduled scans /cron false
AIRFLOW_HOST Apache Airflow host:port localhost:8080
PLUGIN_DIR Custom plugins directory /opt/recon_plugins

📘 A full list of 60+ tunable parameters is documented in the script header.

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📘 Usage & Examples

Basic Scan

Ad Examples

🛑 WARNING: The C2_SERVER, PERSISTENCE_ENABLED, and EXPLOIT_MODE activate acti modules. Never use them without written, legal authorisation.

Scheduled Scans (Airflow)

If SCHEDULE_MODE=true, the script registers a DAG in Airflow for recurring scans. You can then trigger it via the Airflow UI or API.

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🔄 Reconnaissance Phases

The script executes a comprehensive 14‑phase pipeline (plus reporting), each with multiple parallel tasks:

Phase Name Description
1 Setup & Tool Check Auto‑install missing tools, load plugins, initialise directories and Redis caching.
2 Compliance Check targets against HackerOne, Bugcrowd, Intigriti, YesWeHack scopes.
3 Subdomain Enumeration 20+ tools including AI‑driven GAN permutations.
4 URL & Endpoint Discovery Live host probing, historical URL extraction, JS analysis, API endpoint guessing.
5 Network Reconnaissance Mass port scanning, service detection, WAF fingerprinting, traceroute.
6 Scanning Multitude of scanners (Nuclei, Dalfox, Nikto, Zap, etc.) with C.
7 Cloud & Container Scanning CloudSploit, Tri, Kube‑Hunter, Docker benchmarks.
8 Exploit & Malicious Ops SQLi, RCE ; C2 beaconing and persistence (if enabled).
9 Threat Intelligence OTX, , GreyNoise, Censys, Recorded Future, ThreatConnect, dark web.
10 OSINT & Social Media Recon TheHar, Recon‑NG, Maltego, Deepfake detection.
11 Code Repository Scanning TruffleHog, Gitleaks, Semgrep, dependency scanning.
12 Dark Web Scanning Tor‑enabled search for leaks, marketplace mentions.
13 IoT/OT Discovery Shodan/Censys for ICS/SCADA, Modbus enumeration.
14 Supply Chain & Blockchain Analysis SBOM generation, dependency check, crypto address tracking.
15 Reporting & Steganography Generate encrypted reports in multiple formats; optional steganographic exfiltration of findings.

All phases run in parallel where possible, with dynamic thread allocation and Redis‑based caching for optimal speed.

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🧠 AI & Machine Learning

Omniscient integrates AI/ML at multiple levels:

Module Technology Purpose
Subdomain Permutation Generati Networks (GAN) Generate realistic, never‑seen subdomains from seed data.
Endpoint Prediction Neural Networks Predict API endpoints, parameters, and hidden paths.
Prioritisation Reinforcement Learning Rank by exploitability and business impact.
Exploit Chaining Graph Neural Networks Link into multi‑step attack paths.
Risk Scoring Ensemble Models Combine CVSS, dark web mentions, and supply chain data.
Deepfake OSINT Con Neural Networks (CNN) Detect manipulated media (images, audio).
Resource Optimisation Regression Models Auto‑scale threads, GPU/TPU usage based on load.

Custom AI models can be dropped into AI_MODEL_DIR and are automatically invoked if they match the expected filenames. GPU/TPU acceleration is enabled and TPU_ENABLED.

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🌐 Distributed Execution

Omniscient can scale horizontally across clusters:

· Kubernetes – Helm chart included; spawns parallel pods.
· Slurm – For HPC en.
· AWS Lambda – Ser function execution.
· Docker Swarm – Containerised workers.
· Apache Airflow – Orchestrate complex DAGs.

Set DISTRIBUTED_MODE=true and choose a backend (default: auto‑detect).
Tasks are distributed at the phase level, with each worker handling a subset of targets or tools.

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📊 Reporting &

Omniscient generates rich reports in multiple formats:

· PDF – Professional, printable reports with executi.
· HTML – Interacti with filters and drill‑downs.
· JSON/CSV – Machine‑readable for SIEM ingestion and further analysis.
· Graph – Network topology maps (Neo4j export).
· VR – Blender‑ready 3D of attack surfaces.

Real‑time notifications can be pushed to Slack, Discord, Teams, or any SIEM endpoint .

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📂 Output Structure

All results are neatly organised in a timestamped directory:

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🔐 Security, Privacy & Compliance

· Encryption at rest: All sensiti (reports, dumps, keys) are encrypted with AES‑384. Quantum‑safe Kyber‑1024 signatures are used for critical exchanges.
· Immutable audit logs: Every action is hashed (SHA‑512) and the chain can be anchored to an Ethereum smart contract, pro tamper‑proof e.
· Credential management: API keys are ne in plaintext. Use HashiCorp Vault, YubiKey TOTP, HSM, or file‑based (mode 600) with optional GPG encryption.
· Key exchange: Securely share session keys or HSM‑backed channels.
· Steganographic exfiltration: Results can be hidden in innocent‑looking images and sent to a C2 server (educational).
· No phone‑home: The tool does not transmit any telemetry. All data stays local or within your controlled infrastructure.
· Compliance: Automatic scope against bug bounty platforms and built‑in alignment with NIST 800‑53, GDPR, CCPA, ISO 27001.

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❓ Troubleshooting

Issue Solution
Missing tools The script attempts auto‑install. If a tool fails, install it manually and ensure it’s in $PATH.
Redis connection refused Ensure Redis is running: sudo systemctl start redis-server. If using cluster, check configuration.
Tor not working Tor is installed and running: sudo systemctl start tor. For dark web modules, ensure torify is functional.
GPU not detected Check NVIDIA drivers and CUDA . Set GPU_ENABLED=false to fallback to CPU.
Out of memory Reduce THREADS or limit concurrency .
API key errors keys are correctly exported and ha permissions. Use log_json to see detailed errors.
Permission denied Ensure script and output directories ha ownership: sudo chown -R $USER:$USER ..
Slow performance Enable distributed mode, increase Redis cache size, or reduce the number of phases if not needed.

For further assistance, open an issue on GitHub or consult the internal logging (logs/recon.log).

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🤝 Contributing & Support

We welcome contributions from the community! Whether it's a bug fix, new feature, documentation impro, or even a new AI model, your help is appreciated.

How to Contribute

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.

Please ensure your code is well‑documented and includes test cases where applicable.

Support

· 📧 Email:
· 💬 github: Ali-hey-0
· 🐛
· 📚 Documentation: Wiki

Sponsors

If you find Omniscient useful, consider sponsoring the project to support ongoing de and maintenance.

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📜 License

Distributed under the MIT License. See LICENSE for more information.
This project is intended for educational and authorised research purposes only.

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❗ Final Disclaimer

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<b>🧠 Happy (and ethical) hacking!</b>
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项目信息

开发语言：Shell

Star 数：17

技术要点

该项目属于安全软件方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕🛡️ AI-powered reconnaissance framework unifying 130+ security tools — subdomain enum, vuln scanning, cloud/IoT recon, dark web monitoring & blockchain-audited reporting. GAN-driven subdomain prediction, distributed execution post-quantum encryption. Built for bug bounty, red team & DevSecOps.展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。