Generation-based fuzz testing is a strategy where new test data is generated from scratch based on a predefined model that specifies the structure, type, and format of the input data. This approach is systematic and relies on a deep understanding of the format and protocol of the input data to create test cases that are both valid and potentially revealing of vulnerabilities. This contrasts with mutation-based fuzz testing, where existing data samples are modified (mutated) to produce new test cases, and log-based and protocol-based fuzz testing, which use different approaches to test software robustness and security.
[References:ECIH v3 certification materials often cover software testing techniques, including fuzz testing, to identify vulnerabilities in applications by inputting unexpected or random data., ]
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