Projects / In progress
In development

Threat Detection & Attribution Platform

A converged reactive-and-proactive security platform that detects threats in replayed network traffic, attributes them to known adversary groups, generates on-demand incident reports, and automatically triggers reassessment based on real-world threat intelligence.

Suricata, Python, FastAPI, PostgreSQL, MISP, MITRE ATT&CK, MaxMind GeoLite2, p0f, pytest, GitHub Actions
Build progress Phase 1 of 8
Pcap Library, IDS Parsing, Data Enrichment, Adversary Matching, Report Engine, Intel Feed, Auto Assessment, Testing & Docs
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This project builds an integrated detection and attribution pipeline that goes beyond standard IDS alerting. Suricata processes seeded/replayed pcap traffic to generate detections, which are then enriched with geolocation (MaxMind GeoLite2) and passive OS fingerprinting (p0f) before being correlated against MISP-hosted threat intelligence — including MITRE ATT&CK Groups data — to attempt adversary attribution with a confidence score rather than forced matches. A FastAPI reporting layer generates formatted case reports on demand from any logged event. A continuous threat intelligence pipeline pulls structured feeds (abuse.ch, AlienVault OTX, CISA KEV) to keep attribution data current, and an automated assessment trigger runs the existing network security scanner when newly ingested threat intelligence is relevant to the environment's exposure and the last assessment has aged past a defined threshold. The result is a system that moves from purely reactive detection toward proactive, intelligence-driven defense.

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