Open Source · 2500 New MITRE Mutations
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SYNTEX has open sourced 2,500 novel MITRE ATT&CK technique mutations generated autonomously by their Nemesis AI red team using reinforcement learning. These mutations represent new attack vectors derived from known MITRE techniques, validated against a production defense system (Guardian AI). The dataset is intended for use in threat intelligence and detection rule development. There is no indication that these mutations represent active exploits in the wild or vulnerabilities in specific products. The vectors are provided in standard formats for SIEM integration and are licensed for free use with attribution.
r/blueteamsec (opens in a new tab)u/entropiclybound0 points0 comments
I wanted to drop two repo's I've released. I plan to release at least one more dataset when I have time.
These were generated without any human input (but have been human verified) using a fully autonomous, on-prem red team I've developed.
*no LLM or data center is used in my AI. Everything has been developed using pure python stdlib - there are zero external dependencies. I am focusing on democratizing AI and providing an affordable cybersecurity stack for SMBs.
The defender is fully integrated: EDR, SIEM, SOAR, Vuln Scan, Network Anomaly detection (sits on top of firewall - can work with CSF et al)
How it work:
Two reinforcement learning systems: the red team attacks, learns from the blue team, and tries again. After ~100 cycles, a new, novel threat vector is generated based on how the blue team responded, confidence scores, and final decisions.
- If a threat is allowed, the red team leans into it until it is finally blocked/quarantined.
- if a threat is blocked/quarantined, the red team tries new methods or new combinations in order to bypass detection.
This is how all these datasets were generated without any human direction.