Cyber-Zero and cyber-security-llm-agents

Cyber-Zero
50
Established
Maintenance 10/25
Adoption 9/25
Maturity 15/25
Community 16/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 22/25
Stars: 77
Forks: 12
Downloads:
Commits (30d): 0
Language: Python
License:
Stars: 257
Forks: 52
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
No Package No Dependents
No License Stale 6m No Package No Dependents

About Cyber-Zero

amazon-science/Cyber-Zero

Cyber-Zero: Training Cybersecurity Agents Without Runtime

This project helps cybersecurity professionals develop and train autonomous agents to solve Capture The Flag (CTF) challenges. It takes publicly available CTF write-ups and, using simulated interactions, generates realistic training scenarios without needing actual execution environments. The output is high-quality training data for LLM-based cybersecurity agents, allowing practitioners to build more capable automated systems for vulnerability finding.

cybersecurity-training CTF-challenges vulnerability-analysis red-teaming security-automation

About cyber-security-llm-agents

NVISOsecurity/cyber-security-llm-agents

A collection of agents that use Large Language Models (LLMs) to perform tasks common on our day to day jobs in cyber security.

This project helps cyber security professionals automate common, repetitive tasks they face daily. It takes security data, system information, or task requests and uses AI agents to perform actions like identifying endpoint detection and response (EDR) systems or automating purple team exercises. Security analysts, red teamers, and detection engineers would use this to enhance their operational efficiency.

cyber-security red-teaming blue-teaming detection-engineering security-automation

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