1200km Start Here

Canonical GitHub entry point for Andrey Pautov's public CTI-to-detection, malware-analysis, AI-security, and practical security-lab ecosystem.

Use this repo if you landed on GitHub and need the shortest route through the work. The full public inventory lives at:

https://1200km.com/projects.html

Fast Reviewer Paths

Role	Start with	Why
CTI / threat intelligence	AdversaryGraph	Actor/TTP research workspace, ATT&CK mapping, detection and hunting links.
Detection engineering	CTI as a Code	Evidence to ATT&CK to detection seed methodology with a working lab.
Malware analysis	AIDebug	AI-assisted function triage, ATT&CK candidates, YARA, IOC and reports.
Cloud security	StratusAI	AWS/GCP scanner with attack-chain synthesis and optional AI review.
Host assessment	AuditAI	Linux host assessment, Docker workflow, PyPI package, Kali packaging path.
Training labs	Labs index	Reproducible attack simulations and intentionally vulnerable environments.

Flagships

Project	Status	Links
AdversaryGraph	Primary flagship	Live · Hub · Docs · Repo
AIDebug	PyPI published, external submissions open	Repo · PyPI · Article
CTI as a Code	Methodology and analyst lab	Lab · Repo
Operation Desert Hydra	CTI-to-detection case study	Docs · Repo
CTI Analyst Field Manual	Tradecraft reference	Manual · Repo

Installable Tools

pip install 1200km-aidebug
pip install 1200km-auditai
pip install string-analyzer
pip install 1200km-unpacker
pip install pe-import-analyzer
pip install 1200km-fileinfo

The last three package names are the current publishing targets for the Unpacker, PE Import Analyzer, and FileInfo projects.

Public Footprint

• Main site: https://1200km.com/
• Canonical inventory: https://1200km.com/projects.html
• GitHub profile: https://github.com/anpa1200
• Medium profile: https://medium.com/@1200km
• CTI index: https://1200km.com/cti.html
• PT tools index: https://1200km.com/pt-tools.html
• AI/offensive index: https://1200km.com/ai-offensive.html

Guardrails

• CTI output is evidence-led and confidence-scoped.
• ATT&CK mapping is not attribution proof.
• AI output is untrusted until reviewed by a human analyst.
• Offensive material is for authorized labs and defensive validation only.