Assess who is behind a cyberattack campaign.
What it does
Evaluates cyber-campaign evidence against competing threat-actor hypotheses to produce a confidence-weighted attribution assessment.
When to use it
Use when an incident investigation needs a defensible attribution confidence level.
How to use it
Give it campaign evidence and candidate-actor hypotheses as JSON files; it produces a ranked attribution report saved as JSON.
What you provide
- Your files
Latest review
What you need · 6
Requires Python 3.9 or later.
Lists attackcti as a required Python library.
Lists stix2 as a required Python library.
Lists networkx as a required Python library.
Access · 0
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