ISC2 Certified Secure Software Lifecycle Professional (CSSLP) Practice Question
A software team must validate a proprietary binary message protocol used between their IoT gateway and cloud service. They decide to apply generation-based fuzzing rather than mutation-based fuzzing. Which preparatory step is most critical to make the generated fuzz cases both syntactically valid and able to explore boundary conditions of every field?
Create a detailed grammar or schema that describes every field and rule in the binary protocol.
Record a large corpus of real gateway-to-cloud traffic to serve as seed inputs.
Compile a list of publicly known exploit payloads targeting similar IoT protocols.
Add code-level instrumentation so the fuzzer can monitor execution paths during tests.
Generation-based fuzzers rely on an explicit model of the expected input. By building a formal grammar, data schema, or protocol specification that details every field, data type, length and constraint, the fuzzer can systematically create well-formed messages that vary each element at its boundaries and with invalid values. Capturing traffic is helpful for mutation fuzzing, runtime instrumentation supports IAST techniques, and collecting exploit payloads aids penetration testing, but none of these are prerequisites for generation-based fuzzing to work effectively.
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What is generation-based fuzzing?
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Why is creating a formal grammar or schema critical for generation-based fuzzing?
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How does generation-based fuzzing differ from mutation-based fuzzing?
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What is the difference between generation-based fuzzing and mutation-based fuzzing?
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What is a protocol grammar or schema, and why is it important for generation-based fuzzing?
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How do boundary conditions improve the effectiveness of fuzzing?
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ISC2 Certified Secure Software Lifecycle Professional (CSSLP)
Secure Software Testing
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