deltarecon
AI-cybersec
deltarecon is a project born to transform reconnaissance and vulnerability assessment work into a completely automated process, scalable and supported by artificial intelligence
the goal is to integrate all bug bounty phases: from asset collection to scanning, up to reporting in a single, declarative and modular pipeline
vision
deltarecon is not “just a wrapper” of existing tools like nuclei, nikto or ffuf
it’s a complete operational framework that:
- organizes recon and scan tools in ordered and reproducible pipelines,
- normalizes results in structured formats,
- uses AI agents (via AutoGen) to filter, correlate and validate findings,
- produces automatic reports that are immediately ready for validation or submission to bug bounty platforms
operational phases
- domain: enumeration of domains, subdomains and attack surfaces
- recon: domain scanning for technology detection
- scan: integration of multiple scanners
- evaluation (AI)
- AI agents via AutoGen
- findings classification, false positive reduction, pattern correlation
- generation of credible and useful pre-reports
why it’s different
many security tools stop at the stage of “raw” scan execution
deltarecon instead focuses on three distinctive values:
- end-to-end automation → from initial domain to final report, without manual steps
- AI evaluation → faster, targeted and scalable analysis thanks to specialized agents
- distributed scalability → kubernetes orchestration, distributed jobs and resilient storage (MinIO for files, Redis for runtime state)
in summary
deltarecon is much more than a recon framework:
it’s an ecosystem that brings order, intelligence and scalability to a world dominated by isolated tools and manual processes, paving the way for an automated, intelligent and sustainable security model
releases
deltarecon - v1.0.0 haboob
autonomous penetration testing meets artificial intelligence