Ranking risks and countermeasures is one of the foremost goals of quantitative security analysis. One of the popular frameworks, used also in industrial practice, for this task are attack-defense trees. Standard quantitative analyses available for attack-defense trees can distinguish likely from unlikely vulnerabilities. We provide a tool that allows for easy synthesis and analysis of those models, also featuring probabilities, costs and time. Furthermore, it provides a variety of interfaces to existing model checkers and analysis tools. Unfortunately, currently available tools rely on precise quantitative inputs (probabilities, timing, or costs of attacks), which are rarely available. Instead, only statistical, imprecise information is typically available, leaving us with probably approximately correct (PAC) estimates of the real quantities. As a part of our tool, we extend the standard analysis techniques so they can handle the PAC input and yield rigorous bounds on the imprecision and uncertainty of the final result of the analysis.

翻译：风险排序与对策评估是定量安全分析的首要目标之一。攻击防御树作为该领域常用框架，已在工业实践中得到广泛应用。针对攻击防御树的现有标准定量分析方法能够区分可能性高与低的系统漏洞。本文提出的工具支持便捷合成与分析此类模型，同时整合概率、成本与时间参数。此外，该工具提供与现有模型检测器及分析工具的多类接口。然而，当前可用工具依赖精确的定量输入（攻击概率、时间或成本），这类数据往往难以获取。实践中通常仅能获得统计性、非精确信息，导致我们只能通过近似正确概率（PAC）估计真实参数。作为本工具的核心创新，我们扩展了标准分析技术，使其能够处理PAC输入，并为分析结果的非精确性与不确定性提供严格边界。