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EAGER: Finding Semantic Security Bugs with Pseudo-Oracle Testing

EAGER：通过伪 Oracle 测试查找语义安全漏洞

基本信息

批准号：
1842456
负责人：
Baishakhi Ray
金额：
$ 20万
依托单位：
Columbia University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2020-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842456&HistoricalAwards=false
关键词：
EAGER Finding Semantic Security Bugs

项目摘要

Semantic security bugs cause serious vulnerabilities across a wide range of software. For example, in a recent incident, attackers exploited a semantic security bug in Apache Struts to steal sensitive personal data of up to 143 million customers from Equifax servers. In fact, such vulnerabilities are quite common in practice. The total number of Common Vulnerabilities and Exposure Identifiers (CVEs) assigned to different types of semantic security bugs exceeds 2,000 just this year alone. The goal of this project is to improve security and reliability by automatically detecting such semantic vulnerabilities in critical software. Automatically detecting these bugs is hard because unlike crash bugs they may not show any obvious side effects. In contrast, semantic security bugs (e.g., bypassing security checks, gaining access to sensitive information, escalating privileges) usually result from violation of high-level safety/security specifications which, in practice, are rarely written formally. This project will investigate whether learning domain-specific metamorphic relations can help in detecting semantic bugs. In Software Engineering, metamorphic relations, which correlate outputs from multiple executions of a program with different inputs, have been shown to be effective at finding simple functional bugs. While metamorphic relations have promise to detect semantic security vulnerabilities, they are not able to detect semantic security vulnerabilities in their current form, as security properties cannot be expressed as simple input-output based properties. The approach uses pseudo-oracle testing techniques like differential testing and metamorphic testing. The project will use targeted path exploration techniques, with automata-learning algorithms to discover metamorphic testing rules. The project will learn how the semantics of metamorphic relations can be augmented to detect semantic security bugs. The research envisions a unified framework based on pseudo-random Oracles, which can automatically detect semantic security bugs without the need for manually creating formal specifications to compare program behaviors of related executions. As a first step, the objective of this EAGER project is to empirically measure whether there is a comprehensive range of semantically expressive pseudo-oracle relations that can detect semantic security vulnerabilities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

语义安全错误会导致大量软件出现严重漏洞。例如，在最近的一次事件中，攻击者利用Apache Struts中的语义安全漏洞从Equifax服务器窃取了多达1.43亿客户的敏感个人数据。事实上，这样的漏洞在实践中相当普遍。仅今年一年，针对不同类型语义安全漏洞的常见漏洞和暴露标识符（cve）的总数就超过了2000个。该项目的目标是通过自动检测关键软件中的语义漏洞来提高安全性和可靠性。自动检测这些bug是很困难的，因为与崩溃bug不同，它们可能不会显示出任何明显的副作用。相反，语义安全错误（例如，绕过安全检查、获得对敏感信息的访问、升级特权）通常是由于违反高级安全/安全规范而导致的，而这些规范在实践中很少被正式编写。这个项目将研究学习特定领域的变质关系是否有助于检测语义错误。在软件工程中，将程序的多次执行的输出与不同的输入相关联的变形关系，已被证明在查找简单的功能错误方面是有效的。虽然变形关系有希望检测语义安全漏洞，但由于安全属性不能表示为简单的基于输入-输出的属性，因此它们不能以当前形式检测语义安全漏洞。该方法使用伪oracle测试技术，如差分测试和变质测试。该项目将使用目标路径探索技术，以及自动学习算法来发现变形测试规则。该项目将学习如何增强变形关系的语义以检测语义安全漏洞。该研究设想了一个基于伪随机oracle的统一框架，它可以自动检测语义安全漏洞，而无需手动创建正式规范来比较相关执行的程序行为。作为第一步，这个EAGER项目的目标是经验地衡量是否存在一个全面的语义表达伪oracle关系，可以检测语义安全漏洞。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

SABER: Identifying SimilAr BEhavioR for Program Comprehension

DOI：
发表时间：
2020
期刊：
影响因子：
0
作者：
Aditya Sridhar;Guanming Qiao;G. Kaiser
通讯作者：
Aditya Sridhar;Guanming Qiao;G. Kaiser

Testing DNN Image Classifier for Confusion & Bias Errors

测试 DNN 图像分类器的混淆情况

DOI：
发表时间：
2020
期刊：
42nd International Conference on Software Engineering
影响因子：
0
作者：
Tian, Yuchi;Zhong, Ziyuan;Ordonez, Vicente;Kaiser, Gail;Ray, Baishakhi
通讯作者：
Ray, Baishakhi

Side Channel Attack on Smartphone Sensors to Infer Gender of the User

对智能手机传感器进行侧信道攻击以推断用户性别

DOI：
发表时间：
2019
期刊：
17th ACM Conference on Embedded Networked Sensor Systems (SenSys
影响因子：
0
作者：
Singh, Shirish;Shila, Devu Manikantan;Kaiser, Gail
通讯作者：
Kaiser, Gail

Ad hoc Test Generation Through Binary Rewriting

DOI：
10.1109/scam51674.2020.00018
发表时间：
2020-09
期刊：
2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)
影响因子：
0
作者：
Anthony Saieva;S. Singh;G. Kaiser
通讯作者：
Anthony Saieva;S. Singh;G. Kaiser

Binary Quilting to Generate Patched Executables without Compilation

二进制绗缝以生成修补的可执行文件而无需编译