Automating OSINT with Python: Hands-On Guide to AI-Powered Scrapers, Recon Tools, and Intelligence Agents

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Bol Most OSINT books hand you a toolkit. This one teaches you to build one - from raw HTTP scraping to autonomous AI agents that conduct multi-step intelligence missions without you directing every step. Every chapter ends with a working, deployable tool. Twelve hands-on chapters take you from setting up a secure Python environment through writing resilient scrapers, chaining intelligence APIs, extending SpiderFoot with custom modules, integrating LLMs for analysis, and building a complete autonomous agent that accepts a target and delivers a structured report. The OSINT Agent Stack framework - Scrape, Enrich, Reason, Report - organises every tool you build into a coherent intelligence system. - Build a resilient Python web scraper that survives anti-bot defenses including TLS fingerprinting, CAPTCHA detection, and proxy rotation - Integrate Shodan, Have I Been Pwned, and VirusTotal APIs into a unified threat intelligence pipeline with response caching and budget control - Automate subdomain enumeration, WHOIS lookups, and DNS reconnaissance with reusable Python modules and the SpiderFoot framework - Construct a social media profiling tool that enumerates usernames across 50-plus platforms and correlates findings via Gravatar and breach data - Design a metadata extraction engine that surfaces hidden intelligence from images, PDFs, documents, and Git commit histories - Deploy a dark web monitoring system using Tor automation to scan paste sites and track public threat actor channels - Build an AI agent using Claude and GPT function calling that autonomously plans and executes multi-step OSINT missions - Create an interactive intelligence graph using NetworkX and Pyvis that visualises entity relationships across all collected sources - Apply rate limiting, jitter, and ethical guardrails to produce legal, compliant, production-grade automation >Every tool in this book is built on the same base classes, the same schema, and the same pipeline - so each chapter compounds on the last rather than starting over. By the final chapter, the autonomous agent you build uses every tool from Chapters 1 through 10 as its toolset. Written for Python developers, cybersecurity professionals, and OSINT analysts who learn by building. If you can write a Python script, you can build a production intelligence system. Scroll up and grab your copy.

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Most OSINT books hand you a toolkit. This one teaches you to build one - from raw HTTP scraping to autonomous AI agents that conduct multi-step intelligence missions without you directing every step. Every chapter ends with a working, deployable tool. Twelve hands-on chapters take you from setting up a secure Python environment through writing resilient scrapers, chaining intelligence APIs, extending SpiderFoot with custom modules, integrating LLMs for analysis, and building a complete autonomous agent that accepts a target and delivers a structured report. The OSINT Agent Stack framework - Scrape, Enrich, Reason, Report - organises every tool you build into a coherent intelligence system. - Build a resilient Python web scraper that survives anti-bot defenses including TLS fingerprinting, CAPTCHA detection, and proxy rotation - Integrate Shodan, Have I Been Pwned, and VirusTotal APIs into a unified threat intelligence pipeline with response caching and budget control - Automate subdomain enumeration, WHOIS lookups, and DNS reconnaissance with reusable Python modules and the SpiderFoot framework - Construct a social media profiling tool that enumerates usernames across 50-plus platforms and correlates findings via Gravatar and breach data - Design a metadata extraction engine that surfaces hidden intelligence from images, PDFs, documents, and Git commit histories - Deploy a dark web monitoring system using Tor automation to scan paste sites and track public threat actor channels - Build an AI agent using Claude and GPT function calling that autonomously plans and executes multi-step OSINT missions - Create an interactive intelligence graph using NetworkX and Pyvis that visualises entity relationships across all collected sources - Apply rate limiting, jitter, and ethical guardrails to produce legal, compliant, production-grade automation >Every tool in this book is built on the same base classes, the same schema, and the same pipeline - so each chapter compounds on the last rather than starting over. By the final chapter, the autonomous agent you build uses every tool from Chapters 1 through 10 as its toolset. Written for Python developers, cybersecurity professionals, and OSINT analysts who learn by building. If you can write a Python script, you can build a production intelligence system. Scroll up and grab your copy.


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