Fuzzing the i915 Driver: A Collaborative Effort with Intel and University of Bonn
Welcome, fellow security enthusiasts and Linux aficionados! Today, I’m excited to share the culmination of my research efforts in collaboration with Intel and the University of Bonn, Germany. This blog post will introduce you to my master’s thesis, finalized in 2021, which delves into the world of fuzzing the i915 graphics driver using Syzkaller and kAFL. The full thesis document is also attached to this post, allowing you to dive deeper into the technical details.
The i915 driver plays a critical role in modern Linux systems, handling graphics processing for integrated Intel graphics cards. While its importance is undeniable, ensuring its security is equally crucial. This is where fuzzing comes in – a powerful technique for uncovering software vulnerabilities by bombarding it with unexpected inputs. In this research, we explored the effectiveness of two prominent fuzzing tools: Syzkaller and kAFL.
Why Fuzz the i915 Driver?
Modern graphics drivers interact with complex hardware and software components, creating fertile ground for potential security flaws. These vulnerabilities could be exploited by malicious actors to gain unauthorized access to a system, steal sensitive data, or even disrupt system functionality. Fuzzing plays a crucial role in proactively identifying these vulnerabilities before attackers can leverage them.
The Chosen Fuzzing Tools: Syzkaller and kAFL
Syzkaller is a popular, coverage-guided fuzzer that generates random inputs based on symbolic execution. This allows Syzkaller to explore a broader range of input scenarios and identify edge cases that traditional testing methods might miss. In contrast, kAFL (kernel Address space Layout Fuzzer) is a memory-aware fuzzer that excels at detecting vulnerabilities related to memory corruption.
The Research Journey: Findings and Analysis
My research involved setting up a customized fuzzing environment specifically tailored for the i915 driver. We then configured both Syzkaller and kAFL to generate diverse input types that could potentially trigger security vulnerabilities. The fuzzing process ran for an extended period, meticulously exploring the driver’s behavior under various input conditions.
The results were insightful. Both Syzkaller and kAFL successfully ran campaigns against the i915 driver. The research also provided valuable insights into the strengths and weaknesses of each fuzzing tool in the context of graphics driver testing.
What’s Included in the Thesis?
The attached master’s thesis details the entire research journey, from the theoretical background of fuzzing and the i915 driver to the customized fuzzing environment setup and specific configurations for each tool. The document also presents a comparative assessment of Syzkaller and kAFL’s effectiveness in this context.
Conclusion and Future Directions
This research highlights the effectiveness of fuzzing for uncovering vulnerabilities in complex software components like the i915 driver. The findings of this research can contribute to further improvements in the i915 driver, ultimately enhancing the security of Linux systems.
Future avenues for exploration include integrating these fuzzing techniques into the development and testing process of the i915 driver. Additionally, exploring the potential of other fuzzing tools and techniques tailored specifically for graphics drivers could be an exciting next step.
I invite you to download the attached thesis and delve deeper into the technical details of this research. I believe this work provides valuable insights for securing the i915 driver and demonstrates the power of fuzzing in the realm of Linux driver security.