mirror of
https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
synced 2026-06-11 13:44:56 +03:00
mukul975
27c6414ca5
Complete skill folder anatomy across all cybersecurity skills: - scripts/agent.py: 80-150 line Python agents using real libraries (impacket, boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.) - references/api-reference.md: real API documentation with method signatures - LICENSE: MIT license for all skill folders
60 lines
2.2 KiB
Markdown
60 lines
2.2 KiB
Markdown
# API Reference: Implementing Threat Modeling with MITRE ATT&CK
|
|
|
|
## Libraries
|
|
|
|
### attackcti (MITRE ATT&CK CTI)
|
|
- **Install**: `pip install attackcti`
|
|
- **Docs**: https://attackcti.readthedocs.io/
|
|
- `attack_client()` -- Initialize ATT&CK client
|
|
- `get_groups()` -- All threat actor groups
|
|
- `get_techniques()` -- All techniques (Enterprise, Mobile, ICS)
|
|
- `get_techniques_used_by_group(group)` -- Techniques per group
|
|
- `get_mitigations()` -- Defensive mitigations
|
|
- `get_software()` -- Malware and tools catalog
|
|
|
|
### mitreattack-python
|
|
- **Install**: `pip install mitreattack-python`
|
|
- **Docs**: https://mitreattack-python.readthedocs.io/
|
|
- `MitreAttackData(stix_filepath)` -- Load STIX bundle
|
|
- `get_groups_using_technique(technique_stix_id)` -- Groups per technique
|
|
- `get_datacomponents_detecting_technique()` -- Detection data sources
|
|
|
|
## ATT&CK Navigator Layer Format
|
|
|
|
| Field | Description |
|
|
|-------|-------------|
|
|
| `name` | Layer display name |
|
|
| `domain` | `enterprise-attack`, `mobile-attack`, `ics-attack` |
|
|
| `techniques[]` | List of technique annotations |
|
|
| `techniques[].techniqueID` | ATT&CK ID (e.g., T1059) |
|
|
| `techniques[].score` | Numeric score for heat map |
|
|
| `techniques[].color` | Hex color override |
|
|
| `gradient` | Color scale definition |
|
|
|
|
## Threat Modeling Workflow
|
|
1. Identify industry-relevant threat actors
|
|
2. Map actor TTPs to ATT&CK techniques
|
|
3. Assess current detection coverage
|
|
4. Identify coverage gaps
|
|
5. Prioritize defensive investments
|
|
6. Export Navigator layer for visualization
|
|
|
|
## Industry Threat Actor Mapping
|
|
- Financial: APT38, FIN7, Carbanak, Lazarus
|
|
- Healthcare: APT41, FIN12, Wizard Spider
|
|
- Government: APT28, APT29, Turla, Sandworm
|
|
- Technology: APT41, APT10, Hafnium
|
|
- Energy: Sandworm, Dragonfly, APT33
|
|
|
|
## Priority Scoring
|
|
- **CRITICAL**: Technique used by 3+ relevant threat actors
|
|
- **HIGH**: Technique used by 2 relevant threat actors
|
|
- **MEDIUM**: Technique used by 1 relevant threat actor
|
|
|
|
## External References
|
|
- ATT&CK Groups: https://attack.mitre.org/groups/
|
|
- ATT&CK Navigator: https://mitre-attack.github.io/attack-navigator/
|
|
- CTID Center: https://ctid.mitre-engenuity.org/
|
|
- ATT&CK STIX Data: https://github.com/mitre/cti
|
|
- Threat Modeling Manifesto: https://www.threatmodelingmanifesto.org/
|