paperbot · PL 论文追踪

全部论文 待读 收藏

P2 SADT

SADT:面向 SSL/TLS 实现证书验证的语法感知差分测试框架
ASE Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering2020匹配度 1/10 · 该论文属于 SSL/TLS 证书验证实现的差分测试,核心是树变异与测试用例共享,未涉及静态分析、LLM/Agent、浮点程序分析或贝叶斯程序分析,与用户研究画像的核心方向基本无关。引用 12 inbox
Lili Quan, Qianyu Guo, Hongxu Chen, Xiaofei Xie, Xiaohong Li, Yang Liu, Jing Hu
crossref: 2026-09-12

AI 速览

一句话:提出语法感知的差分测试框架 SADT,通过树变异与测试用例共享提升 SSL/TLS 证书验证缺陷检测能力。

SSL/TLS 的安全性依赖于 X.509 证书的正确验证,因此需要检验 SSL/TLS 实现是否正确地校验证书。现有差分测试虽能发现语义缺陷,但存在测试用例语法难以保证、多样性不足的问题。本文提出 SADT,一个语法感知的差分测试框架,用于评估 SSL/TLS 实现中的证书验证过程。该方法首先采用基于树的变异策略,保证生成证书在语法上正确;随后在所有目标 SSL/TLS 实现之间共享有趣测试用例,以增加证书多样性。这样生成的证书更可能触发不同实现之间的行为差异,从而暴露潜在缺陷。

问题
如何有效检测 SSL/TLS 实现中 X.509 证书验证的语义缺陷;现有差分测试存在生成用例语法不正确、多样性不足的问题。
方法
提出语法感知差分测试框架 SADT,使用基于树的变异保证证书语法正确,并在多个 SSL/TLS 实现间共享有趣测试用例以增强多样性。
评估
在多个目标 SSL/TLS 实现上进行证书验证差分测试,比较实现行为并寻找差异;摘要指出生成的证书更可能触发差异,但未报告具体定量结果。
原文摘要(Abstract)

The security assurance of SSL/TLS critically depends on the correct validation of X.509 certificates. Therefore, it is important to check whether a certificate is correctly validated by the SSL/TLS implementations. Although differential testing has been proven to be effective in finding semantic bugs, it still suffers from the following limitations: (1) The syntax of test cases cannot be correctly guaranteed. (2) Current test cases are not diverse enough to cover more implementation behaviours. This paper tackles these problems by introducing SADT, a novel syntax-aware differential testing framework for evaluating the certificate validation process in SSL/TLS implementations. We first propose a tree-based mutation strategy to ensure that the generated certificates are syntactically correct, and then diversify the certificates by sharing interesting test cases among all target SSL/TLS implementations. Such generated certificates are more likely to trigger discrepancies among SSL/TLS implementations, which may indicate some potential bugs.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot6010,
  title = {SADT},
  author = {Lili Quan and Qianyu Guo and Hongxu Chen and Xiaofei Xie and Xiaohong Li and Yang Liu and Jing Hu},
  booktitle = {ASE},
  year = {2020},
  doi = {10.1145/3324884.3416552}
}