Early Bird (< 30th April): SGD2999
Normal (> 1st May): SGD3899
Seats Available: N/A
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Overview
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 analyze the properties of memory corruption from integer overflows, uninitialized variables, use-after-free and look at applying tools such as compiler plugins, binary instrumentation frameworks, memory debuggers, and fuzzers to discovering each one.
Next 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.
Finally we approach crash analysis through the lens of scriptable debuggers and program analysis. We will once again look at properties of how memory corruption manifests in a crashing condition. We will apply tools like reverse debugging and memory debugging scripts 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. Finally we will look at possible ways to aid in determining severity of a vulnerability.
This class will focus on x86/x64 architecture and target Windows and Linux environments, however some discussion regarding applications to ARM and mobile platforms will also be included and all of the concepts if not the direct tools will be useful in other environments.
Who should attend
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.
Key Learning Objectives
Learn an effective strategy for using the latest tools and technology to discover vulnerabilities
Understand applications of static analysis for bug hunting
Learn how to decompose programs and analyze them with powerful frameworks
Learn how to write basic clang-analyzer plugins
Introduction to intermediate languages for program analysis
Introduction to graph search, transformation, and slicing
Leverage dynamic binary translation for efficient tracing and deep program inspection
Master the latest fuzzing techniques and strategies for file and network fuzzing
Learn grammar fuzzing, evolutionary fuzzing, in-memory fuzzing, and symbolic fuzzing
Best practices for corpus generation, fuzzer deployment, and targeting
Apply powerful techniques like taint analysis and graph slicing towards crash analysis
Prerequisite Knowledge
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.
Hardware / Software Requirements
Students should have the latest VMware Player, Workstation, or Fusion working on their machine.
Agenda
Day 1: Program Analysis
Morning:
Strategies for automating vulnerability discovery
Analyze properties of memory corruption vulnerabilities
Understand capabilities and applications of program analysis
Programmatic analysis of C/C++ source code
Introduction to advanced pattern matching and AST search
Introduction to using dataflow analysis for bug detection
Introduction to writing clang-analyzer plugins
Exercise: writing clang analyzer plugins
Afternoon:
Dynamic memory analysis for blackbox bug hunting
Effectively instrument Linux and Windows with binary translation
Introduction to Valgrind and Dr. Memory
Code coverage with PIN, DynamoRIO, and DynInst
Introduction to dynamic taint analysis with BAP
Exercise: writing property checks for taint analysis
Day 2: Fuzzing & Triage I
Morning:
Attack surface analysis for blackbox vulnerability research
Enumerating trust boundaries
Enumerating inputs
Leveraging graph reachability analysis
Best practices for generational and mutational fuzzing
Triggering vulnerabilities through fuzzing
Effective mutation engines
Effective corpus generation
Creating protocol and file format grammars
Crash detection
Afternoon:
Evolutionary Fuzzing
Code coverage driven fuzzing
Modifying targets for optimal evolutionary fuzzing
Best practices for high performance
Interactive and scripted crash debugging
Root cause identification for memory corruption bug classes
Memory debuggers and code coverage
Debugger plugins and scripting APIs
Day 3: Fuzzing & Triage II
Morning:
Advanced Fuzzing
Fuzzing kernels and other architectures with QEMU
Hybrid fuzzing with concolic execution
Browser and language interpreter fuzzing
Afternoon:
Advanced crash analysis
Reverse debugging
Dynamic taint analysis and graph slicing
Forward symbolic execution for exploitability analysis