Early bird registration rate ends on the 31st of January
This class is designed to introduce students to the best tools and technology available for automating vulnerability discovery and crash triage with a focus on delivering a practical approach to applying this technology in real deployments at any scale.
Through an applied understanding of introductory program analysis and binary translation, techniques for finding various bug classes and methods for improved crash debugging will be discussed. We will take a deep dive into fuzzing, covering all aspects of this practical approach to finding bugs. As the most approachable and versatile of the available tools, the student will apply various fuzzing techniques to several real-world pieces of software. Students will learn strategies for analyzing attack surface, writing grammars, and generating effective corpus. We will explore in detail the latest innovations such as harnessing code coverage for guided evolutionary fuzzing and symbolic reasoning for concolic fuzzing.
We approach crash analysis through the lens of scriptable debuggers and program analysis. We will apply tools like reverse debugging and memory debuggers to assist in interactively diagnosing root cause of crashes. Then we will leverage the power of dynamic taint tracking and graph slicing to help isolate the path of user controlled input in the program and identify the exact input bytes influencing a crash. Lastly, we will look at possible ways to aid in determining severity of a vulnerability.
This class will focus on x86/x64 architecture and target file parsers, network parsers and browsers on both Windows and Linux environments.
This class is meant for professional developers or security researchers looking to add an automation component to their software security analysis. Students wanting to learn a programmatic and tool driven approach to analyzing software vulnerabilities and crash triage will benefit from this course.
Students should be prepared to tackle challenging and diverse subject matter and be comfortable writing functions in in C/C++ and python to complete exercises involving completing plugins for the discussed platforms. Attendees should have basic experience with debugging native x86/x64 memory corruption vulnerabilities on Linux or Windows.
Students should have the latest VMware Player, Workstation, or Fusion working on their machine
Analysis of generational and mutational fuzzing
Attack surface analysis
Effective mutation engines
Effective corpus generation
Protocol and file format grammars
Crash detection
Fuzzing file and network parsers with coverage guided fuzzing
Fuzz any Ubuntu/Debian package with AFL
Modifying targets and writing harnesses with LibFuzzer
Fuzzing closed source parsers with QEMU and Dyninst
Best practices for high performance fuzzing
System configuration
Corpus generation techniques
Cross-fuzzing difficult parsers
Dynamic Binary Translation for Fuzzing and Triage
Effectively instrument Linux and Windows with binary translation
Introduction to Valgrind, Dr. Memory, and Address Sanitizer
Introduction to PIN, DynamoRIO, and Dyninst internals
Identifying hook locations with Debuggers and DBI
Fuzzing parsers with WinAFL
Optimizing harnesses for exported APIs
Hooking closed source command line applications
Deep hooks into private library functions with global state
Fuzzing internal data streams in complex OLE objects
Fuzzing browsers with evolutionary grammar fuzzing
Understanding grammars and object models
Fuzzing object models with dynamic grammar fuzzing
Improving grammar fuzzers with feedback metrics
Time Travel Debugging
Introduction to time travel debugging
Crash analysis with reverse debugging on Linux
Crash analysis with reverse debugging on Windows
Taint assisted root cause analysis
Introduction to dynamic taint analysis
Taint slicing for for root cause analysis
Symbolic and Concolic Execution
Introduction to constraint solving
Concolic execution for test case generation
