What is a common challenge when integrating fuzzing into CI/CD?

Fuzzing only works on open-source software

Fuzzing can be resource-intensive and may slow down the build pipeline

Fuzzing requires a human to analyze every crash

What is a key characteristic of mutation-based fuzzing?

It relies on existing seed inputs that are modified to produce new test cases

It creates test cases from scratch based on a grammar

It only works with binary file formats

It requires a detailed specification of the input format

A security researcher wants to fuzz a C++ library that is built with CMake. They want to use libFuzzer because it integrates well with their build system. What is the primary advantage of libFuzzer over a standalone fuzzer like AFL?

It does not require any code changes.

It can fuzz any binary without recompilation.

It runs in-process, which is faster for targets with many small inputs.

It automatically generates a grammar for the input format.

Why is it important to minimize a seed corpus before fuzzing?

To reduce the number of test cases that the fuzzer must execute, improving efficiency

To ensure that all seeds are valid and do not cause crashes

To make the fuzzer run faster by reducing the size of each seed

To increase the diversity of the seed inputs

A large software project wants to integrate fuzzing into its CI/CD pipeline. The project has a long build time and a large codebase. The team wants to catch regressions quickly on every commit, but also wants to run deeper fuzzing campaigns periodically. Which strategy best balances these needs?

Run fuzzing only on release branches.

Use a mutation-based fuzzer without coverage feedback in CI.

Run a full 24-hour fuzzing campaign on every commit.

Run a short coverage-guided fuzzing session on every commit and a longer campaign on a nightly schedule.

GIAC Exploit Researcher and Advanced Penetration Tester

Domain 5Objective 3

Source Code Based Fuzzing Techniques GXPN Practice Questions (Page 8)

Part of the Endpoint Evasion, Privilege Escalation, and Product Security Testing domain, which makes up ~33% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 180-minute exam (~70–120 total, ~23–40 in this domain), expect 8–13 from this objective — we provide 51 practice questions to prepare you well beyond it. (estimate)

51questions here

11free pages

10concepts

Questions 36–40

36foundation · easy
What is a common challenge when integrating fuzzing into CI/CD?
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37foundation · easy
What is a key characteristic of mutation-based fuzzing?
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38application · medium
A security researcher wants to fuzz a C++ library that is built with CMake. They want to use libFuzzer because it integrates well with their build system. What is the primary advantage of libFuzzer over a standalone fuzzer like AFL?
Select an answer first
39foundation · easy
Why is it important to minimize a seed corpus before fuzzing?
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40expert · hard
A large software project wants to integrate fuzzing into its CI/CD pipeline. The project has a long build time and a large codebase. The team wants to catch regressions quickly on every commit, but also wants to run deeper fuzzing campaigns periodically. Which strategy best balances these needs?
Select an answer first

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