Fuzzing

Fuzzing, also known as fuzz testing, is an automated software testing technique that involves providing invalid, unexpected, or random data (known as "fuzz") as input to a computer program. The primary goal is to discover coding errors and security vulnerabilities by causing the target program to crash, fail assertions, or handle the input in unintended ways. As a critical practice in cybersecurity, fuzzing is highly effective at uncovering exploitable flaws like buffer overflows, memory leaks, and denial-of-service weaknesses before malicious actors can find them, thereby enhancing overall software robustness and security.

1. Introduction to Fuzzing
   1. Defining Fuzz Testing
      1. Basic Definition
      2. Key Terminology
      3. Typical Use Cases
   2. Core Goals of Fuzzing
      1. Vulnerability Discovery
         1. Identifying Security Flaws
         2. Uncovering Unknown Bugs
      2. Robustness Testing
         1. Assessing Fault Tolerance
         2. Handling Unexpected Inputs
      3. Quality Assurance
         1. Improving Software Reliability
         2. Enhancing Code Quality
   3. Historical Context
      1. Origins at the University of Wisconsin
         1. Early Experiments
         2. Initial Results and Impact
      2. Evolution of Fuzzing Techniques
         1. Manual Fuzzing
         2. Automated Fuzzing
         3. Modern Developments
   4. Fuzzing vs. Other Testing Methods
      1. Static Analysis
         1. Principles of Static Analysis
         2. Strengths and Limitations
      2. Dynamic Analysis
         1. Principles of Dynamic Analysis
         2. Strengths and Limitations
      3. Manual Penetration Testing
         1. Human-Driven Testing
         2. Comparison with Automated Fuzzing
      4. Unit Testing
         1. Scope and Focus
         2. Complementarity with Fuzzing