CI Fuzz, AFL++, LibFuzzer, or Honggfuzz: Which Fuzzer is
Right for You?
to decide whether a Buy or Build strategy best fits your team’s needs.
CI Fuzz vs AFL++ vs LibFuzzer vs Honggfuzz
| Criteria | CI Fuzz by Code Intelligence | libFuzzer | AFL++ | Honggfuzz |
|---|---|---|---|---|
| Fuzzing Technique | ||||
| Access to source code required | Yes | Yes | Yes. It can also work with binaries. | Yes |
| Testing approach: whitebox (coverage-guided) vs. blackbox (random and heuristic) | Whitebox | Whitebox | Whitebox | Whitebox |
| Support for structure-aware fuzzing | A Supports standard protocols such as CAN, SPI, and DIO. |
B Structure-aware via custom mutators (manual setup) |
B Structure-aware via custom mutators (manual setup) |
C Supports it using external mutator commands |
| Fuzz Testing Process & Automation | ||||
| Expertise required | A Accessible to users with beginner to intermediate knowledge |
C Expert-level knowledge in fuzz testing is essential |
C Expert-level knowledge in fuzz testing is essential |
C Expert-level knowledge in fuzz testing is essential |
| Automated entry point identification | A The most important functions are automatically identified using advanced static analysis |
C Manual identification |
C Manual identification |
C Manual identification |
| Automated fuzz test (harness) creation | A Fuzz tests are created, executed, and validated automatically using LLMs |
C Manual fuzz test creation |
C Manual fuzz test creation |
C Manual fuzz test creation |
| Autonomous fuzz testing | A Spark, the AI Test Agent, generates and runs fuzz tests until they reach the specified code coverage goal without human intervention |
C Every fuzz test has to be run manually each time |
C Every fuzz test has to be run manually each time |
C Every fuzz test has to be run manually each time |
| Regression testing | A Built-in regression testing (reuses previously reached states and findings) |
C Manual management of corpus and crashing input is needed |
C Manual management of corpus and crashing input is needed |
C Manual management of corpus and crashing input is needed |
| Bug Detection & Reporting | ||||
| Bug deduplication | A Automated |
C Manual |
C Manual |
C Manual |
| Code coverage report | A HTML, LCOV report; calculates it for every line of code; aggregates reports of multiple fuzz tests for a project’s overview |
C Manual |
C Manual |
C Manual |
| Vulnerability Exploitability eXchange (VEX) support | A Supports VEX (valuable for regulated industries) |
C Doesn’t support VEX |
C Doesn’t support VEX |
C Doesn’t support VEX |
| Integration | ||||
| Debugging support | A Supports test framework GTest |
C | C | C |
| Build systems Support | A CMake, Bazel |
C No built-in support; manual configuration is required |
C No built-in support; manual configuration is required |
C No built-in support; manual configuration is required |
| Integration into existing CI/CD pipelines | A Can support any CI solution, incl. GitHub Actions, Jenkins, GitLab |
C Manual setup is required |
C Manual setup is required |
C Manual setup is required |
| Technical specifications | ||||
| Supported programming languages | C, C++; Java, JS are supported by Code Intelligence’s open-source tools | C, C++ | C, C++ | C, C++ |
| Supported compilers | Clang, GCC | Clang | Clang, GCC | Clang, GCC |
| Installation: on-premise vs. cloud | On-premise | On-premise | On-premise | On-premise |
| Supported operating systems | Linux, Windows, MacOS | Linux, MacOS, Windows | Linux, MacOS | Linux, MacOS, Windows |
| AUTOSAR compatibility | A Using AUTOSAR simulator for hardware layers |
C | C | C |
| General | ||||
| Licensing model | B Per company (unlimited users) |
A Free of charge |
A Free of charge |
A Free of charge |
| Customer support | A Dedicated customer manager, training, and consulting services |
C Relies on community-driven support with open-source documentation. |
C Relies on community-driven support with open-source documentation. |
C Relies on community-driven support with open-source documentation. |
CI Fuzz vs AFL++ vs LibFuzzer vs Honggfuzz
| Criteria | CI Fuzz by Code Intelligence | libFuzzer | AFL++ | Honggfuzz |
|---|---|---|---|---|
| Fuzzing Technique | ||||
| Access to source code required | Yes | Yes | Yes. It can also work with binaries. | Yes |
| Testing approach: whitebox (coverage-guided) vs. blackbox (random and heuristic) | Whitebox | Whitebox | Whitebox | Whitebox |
| Support for structure-aware fuzzing | A | B | B | C |
| Fuzz Testing Process & Automation | ||||
| Expertise required | A | C | C | C |
| Automated entry point identification | A | C | C | C |
| Automated fuzz test (harness) creation | A | C | C | C |
| Autonomous fuzz testing | A | C | C | C |
| Regression testing | A | C | C | C |
| Bug Detection & Reporting | ||||
| Bug deduplication | A | C | C | C |
| Code coverage report | A | C | C | C |
| Vulnerability Exploitability eXchange (VEX) support | A | C | C | C |
| Integration | ||||
| Debugging support | A | C | C | C |
| Build systems Support | A | C | C | C |
| Integration into existing CI/CD pipelines | A | C | C | C |
| Technical specifications | ||||
| Supported programming languages | C, C++; Java, JS are supported by Code Intelligence’s open-source tools | C, C++ | C, C++ | C, C++ |
| Supported compilers | Clang, GCC | Clang | Clang, GCC | Clang, GCC |
| Installation: on-premise vs. cloud | On-premise | On-premise | On-premise | On-premise |
| Supported operating systems | Linux, Windows, MacOS | Linux, MacOS, Windows | Linux, MacOS | Linux, MacOS, Windows |
| AUTOSAR compatibility | A | C | C | C |
| General | ||||
| Licensing model | B | A | A | A |
| Customer support | A | C | C | C |
Launch and Run Fuzz Harnesses With a Single Command
What our clients say about Code Intelligence
ANDREAS LACKNER
SENIOR SOFTWARE DEVELOPMENT ENGINEER, VECTOR INFORMATIK
“By reducing the manual effort for creating and integrating fuzz tests, we are able to bring our cycle time down and further improve the quality of our embedded software.”
MICHAEL VON WENCKSTERN
PRODUCT CYBERSECURITY GOVERNANCE, RISK AND COMPLIANCE SPECIALIST, CONTINENTAL AG
“One of the biggest advantages of instrumented fuzz testing is that you can execute your code in a Software-in-the-Loop simulator. My favourite part of instrumented fuzzing is that finding the root cause is so easy, and for a manager, it means I can save budget.”
ANDREAS WEICHSLGARTNER
SENIOR TECHNICAL SECURITY ENGINEER, CARIAD
"Thanks to Code Intelligence fuzzing approaches, our security testing became significantly more effective. All our developers are now able to fix business critical bugs early in the development process, without false-positives."
THOMAS DOHMKE
CEO, GITHUB
”Code Intelligence helps developers ship secure software by providing the necessary integrations to test their code at each pull request, without ever having to leave their favorite environment. It's like having an automated security expert always by your side.”
THOMAS TSCHERSICH
CHIEF SECURITY OFFICER, DEUTSCHE TELEKOM AG
”With Code Intelligence, securing your software can take new paths in terms of quality and efficiency.”
ECKART HEYNE
PRODUCT CYBERSECURITY AND PRIVACY OFFICER, CONTINENTAL AG
“Using fuzz testing by Code Intelligence helped our team pass ASPICE for Cybersecurity assessments and obtain ISO 21434 certification. Our products are now more secure. We presented the OEM with the fuzzing results and received positive feedback.”
SALEH HEYDARI
VP OF SOFTWARE ENGINEERING, XOS TRUCKS
”Thanks to Code Intelligence we were able to remediate deeply hidden issues, allowing us to ensure our vehicular software’s optimal functionality and safety. Coming up with the right unit tests for these cases would have been super difficult. With Code Intelligence’s AI-powered tests, we had the first finding within hours!”
From 0 to 80 in 2 seconds. Code Coverage with CI Fuzz.
Find truly relevant and hidden issues and dig deeper every minute
Resolve issues seamlessly with instant access to a full stack trace at your fingertips.
Boost efficiency and reduce the number of tests needed
Let CI Fuzz automatically search for issues in the code and dig deeper every minute.
Fix business critical bugs early in the development process
Maximize pipeline performance that doesn't compromise software integrity.
What is Fuzz Testing?
