solsticestudioai/nemesis-cyber-pack

Nemesis网络威胁模拟包（样本）是一个合成的对抗性代理网络操作数据集，用于检测模型训练、SOC分析师分类研究和蓝队评估。每一行记录了一个完整的模拟攻击事件：触发异常、环境上下文、对抗性规划者推理、相关遥测跟踪、执行摘要和最终决策结果（检测到/阻止/影响实现/保持隐蔽/外泄完成）。该数据集由SolsticeAI构建，作为更大商业包的免费样本。100%合成，不包含真实事件、受害者或漏洞数据，也不包含有效的攻击代码。TTP标签与MITRE ATT&CK词汇对齐，因此该样本可用于训练和基准测试防御者。数据集包含10,000个事件，按结果类别分层，覆盖AWS-Cloud、Active-Directory、Kubernetes和Web-App-Gateway等环境。

The Nemesis Cyber Threat Simulation Pack (Sample) is a synthetic adversarial-agent cyber operations dataset for detection-model training, SOC analyst triage research, and blue-team evaluation. Each row captures a complete simulated attack episode: triggering anomaly, environment context, adversarial planner reasoning, correlated telemetry trace, execution summary, and final decision outcome (detected / blocked / impact achieved / stealth maintained / exfiltration complete). Built by SolsticeAI as a free sample of a larger commercial pack, it is 100% synthetic with no real incident, victim, or exploit data — and no working offensive code. TTP labels align with MITRE ATT&CK vocabulary, making this sample suitable for training and benchmarking defenders. The dataset includes 10,000 episodes, stratified by outcome class, and covers environments such as AWS-Cloud, Active-Directory, Kubernetes, and Web-App-Gateway.