# rabobank-cdc/DeTTECT

Detect Tactics, Techniques & Combat Threats

Repository: https://github.com/rabobank-cdc/DeTTECT
Canonical: https://ross.abutalabs.com/products/dettect
Language: SCSS
License: GPL-3.0
License Family: copyleft
Last push: 2026-08-06T01:26:07+00:00

## Health v2 (maintenance only)
Score: 75/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 34, longevity 100
- inputs: {"age_days": 2714, "days_push": 28, "days_rel": 224, "gap_med": 212.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2334, forks 350 (observed 2026-08-28T04:06:37.967502+00:00)

## What it is
DeTT&CT is a Python CLI tool and framework that helps blue teams score and map data source quality, visibility, detection coverage, and threat actor behaviours against MITRE ATT&CK. It generates ATT&CK Navigator visualisations and works with YAML administration files and a web-based editor.

## Use cases
- map detection coverage to MITRE ATT&CK
- score the quality of my log data sources
- visualise visibility coverage across endpoints
- compare threat actor behaviours against my detections
- prioritise blue team detection engineering efforts
- generate ATT&CK Navigator heatmaps for coverage

## When to choose
- your blue team uses MITRE ATT&CK and wants structured scoring of visibility and detections
- you need to compare detection coverage against threat actor TTPs
- you want Navigator-compatible visualisations of coverage gaps

## When to avoid
- you need an automated detection engine or SIEM - DeTT&CT only maps and scores, it does not detect
- you want a GUI-only tool without working with YAML files
- your organisation does not use the ATT&CK framework

## Facets
- artifact type: cli-tool
- maturity: active
- function: security, analytics, developer-tools
- domain: security, developer-tools
- platform: python, cli, cross-platform
- tags: mitre-attack, blue-team, threat-detection, attack-navigator, yaml, cyber-threat-intelligence

## Member repositories
- rabobank-cdc/DeTTECT (main) score 75

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:37.967502+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:37:47.017770+00:00, confidence not recorded.
  - readme: https://github.com/rabobank-cdc/DeTTECT (fetched 2026-08-28T04:06:37.967502+00:00, sha 34a74997f2dd)
- Data as of 2026-08-30T08:39:29.467469+00:00.