FuzzerAid: Grouping Fuzzed Crashes Based On Fault Signatures

TL;DR

FuzzerAid introduces a fault signature-based method to accurately group fuzzing crashes by their root causes, significantly reducing duplicate bug reports and improving bug diagnosis efficiency.

Contribution

The paper presents FuzzerAid, a novel fault signature approach for crash grouping that outperforms existing heuristics in accuracy and bug deduplication.

Findings

Correctly grouped 99.1% of crashes

Reported only 17 (+2) unique bugs

Outperformed state-of-the-art fuzzers

Abstract

Fuzzing has been an important approach for finding bugs and vulnerabilities in programs. Many fuzzers deployed in industry run daily and can generate an overwhelming number of crashes. Diagnosing such crashes can be very challenging and time-consuming. Existing fuzzers typically employ heuristics such as code coverage or call stack hashes to weed out duplicate reporting of bugs. While these heuristics are cheap, they are often imprecise and end up still reporting many "unique" crashes corresponding to the same bug. In this paper, we present FuzzerAid that uses fault signatures to group crashes reported by the fuzzers. Fault signature is a small executable program and consists of a selection of necessary statements from the original program that can reproduce a bug. In our approach, we first generate a fault signature using a given crash. We then execute the fault signature with other crash inducing inputs. If the failure is reproduced, we classify the crashes into the group labeled with the fault signature; if not, we generate a new fault signature. After all the crash inducing inputs are classified, we further merge the fault signatures of the same root cause into a group. We implemented our approach in a tool called FuzzerAid and evaluated it on 3020 crashes generated from 15 real-world bugs and 4 large open source projects. Our evaluation shows that we are able to correctly group 99.1% of the crashes and reported only 17 (+2) "unique" bugs, outperforming the state-of-the-art fuzzers.