Collaborative Research: SaTC: CORE: Medium: Rethinking Fuzzing for Security

在软件中，漏洞是代码中的缺陷，可以被恶意行为者利用来执行未经授权的活动或更改软件的行为。虽然安全研究人员大量研究的一个主题，发现软件漏洞正变得越来越具有挑战性，因为在日常生活中广泛使用的软件越来越大，越来越复杂。该项目通过重新思考一种称为模糊的经典技术来解决这一挑战，该技术用于从大型软件中查找漏洞。模糊化的高级思想是创建大量的随机输入来运行软件，并反过来触发漏洞。该项目的新颖之处在于新的方法、技术和工具，它们彻底改变了模糊测试，使几乎随机的测试过程更加智能和有针对性。通过这种方式，该项目将增强从Web浏览器到服务器端程序的各种广泛使用的软件的安全性。为此，该项目正在研究可验证性覆盖率驱动的模糊。现有的模糊技术主要遵循一种称为代码覆盖率驱动模糊的方法，其动机是相信代码覆盖率和漏洞发现是密切相关的。支持这一广泛持有的信念，该项目表明，代码覆盖率与漏洞的联系弱于预期，代码覆盖率驱动的模糊不适合漏洞发现。该项目开创性地提出了一系列新技术，以（1）获得漏洞覆盖率的反馈（2）优先考虑可以到达更多漏洞的测试输入（3）最大化触发测试输入到达的漏洞的机会。该项目还产生了新的指标，新的基准，和新的框架，全面评估使用模糊漏洞发现。本计画结合研究人员在软体安全与系统安全研究的经验，提供一群教育、训练与研究的机会给本科生与研究生。该奖项反映了NSF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。

In software, a vulnerability is a flaw in the code that can be exploited by a malicious actor to perform unauthorized activities or change the behavior of the software. Although a topic heavily studied by security researchers, finding software vulnerabilities is becoming increasingly challenging because the software widely used in day-to-day life is growing larger and more complicated. This project addresses this challenge by rethinking a classic technique called fuzzing for finding vulnerabilities from large software. The high-level idea of fuzzing is to create a large number of random inputs to run software and in turn trigger vulnerabilities. The novelties of this project are the new approaches, techniques, and tools that revolutionize fuzzing and make the nearly random testing process more intelligent and targeted. This way, this project will enhance security of various types of widely used software, ranging from web browsers to server-side programs.To that end, this project is investigating vulnerability-coverage-driven fuzzing. Existing fuzzing techniques primarily followed an approach called code-coverage-driven fuzzing, motivated by the belief that code coverage and vulnerability finding are strongly correlated. Challenging this widely held belief, this project shows that code coverage has weaker-than-expected ties with vulnerabilities and code-coverage-driven fuzzing is not well suited for vulnerability finding. Pioneering vulnerability-coverage-driven fuzzing, this project invents a series of novel techniques to (1) obtain feedback on vulnerability coverage (2) prioritize test inputs that can reach more vulnerabilities and (3) maximize the chance to trigger vulnerabilities reached by the test inputs. This project also produces new metrics, new benchmarks, and new frameworks for comprehensively evaluating the use of fuzzing for vulnerability finding. With the investigators' experience in research of software security and system security, this project provides a group of education, training, and research opportunities for both undergraduate and graduate students. Through industry outreach, the investigators pursue technology transfers and raise the awareness of software security.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.