论文标题
预防次要化攻击的运行时
Runtime Prevention of Deserialization Attacks
论文作者
论文摘要
不受信任的挑选漏洞（其中使用序列化对象图来实现拒绝服务或任意代码执行）已变得如此突出，以至于它们是在2017年OWASP TOP 10中引入的。在本文中，我们介绍了一种新颖的和轻巧的方法，用于使用Markov Chains使用Markov Chains进行防空攻击。我们作品背后的直觉是，在恶意对象图中，类的功能和顺序使它们与良性的特征和订购使其与良性区分开。初步结果确实表明，我们的方法在264个序列化有效载荷的数据集上达到了0.94的F1得分，从工业Java EE应用程序服务器收集，并且是避免利用的存储库。
Untrusted deserialization exploits, where a serialised object graph is used to achieve denial-of-service or arbitrary code execution, have become so prominent that they were introduced in the 2017 OWASP Top 10. In this paper, we present a novel and lightweight approach for runtime prevention of deserialization attacks using Markov chains. The intuition behind our work is that the features and ordering of classes in malicious object graphs make them distinguishable from benign ones. Preliminary results indeed show that our approach achieves an F1-score of 0.94 on a dataset of 264 serialised payloads, collected from an industrial Java EE application server and a repository of deserialization exploits.
