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summary: "ZKDocs provides comprehensive, detailed, and interactive documentation on zero-knowledge proof systems and related primitives."
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---
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# Zero-knowledge protocols
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ZKDocs provides comprehensive, detailed, and interactive documentation on zero-knowledge proof systems and related primitives.
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At [Trail of Bits](https://www.trailofbits.com/), we audit many implementations of non-standardized cryptographic protocols and often find the same issues. As we discovered more instances of these bugs, we wanted to find a way to prevent them in the future. Unfortunately, for these protocols, the burden is on the developers to figure out all of the low-level implementation details and security pitfalls.
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We hope that ZKDocs can fill in this gap and benefit the larger cryptography community.
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{{< hint info >}}
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**For in-depth resources and interactive guides on zero-knowledge proof systems, visit https://zkdocs.com.**
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The more performant AFL++ fuzzer is compatible with fuzzing harnesses written for libFuzzer, which means transitioning from libFuzzer to AFL++ is easy and requires only changing your compiler from `clang++` to `afl-clang-fast++`.
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{{< fuzzing/intro-os >}}
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If possible, we recommend fuzzing on a local x64_64 VM or renting one on DigitalOcean, AWS, Hetzner, etc.
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If possible, we recommend fuzzing on a local x86_64 VM or renting one on DigitalOcean, AWS, Hetzner, etc.
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{{< hint info >}}
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PRO TIP: The filename of a crash gives precise information about where it originated. The name `id:000000,sig:06,src:000002,time:286,execs:13105,op:havoc,rep:4` indicates that the crash with ID 0 caused a signal 6 in the SUT. The crash input originates from the source test case with ID 2. Test case 2 originates from the seed input with the test case ID 0. Additional data indicates, for example, when the crash was discovered or which mutation led to the discovery.
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```shell
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./afl++ <host/docker> AFL_PIZZA_MODE=1 afl-fuzz -i seeds -o out -- ./fuzz
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The most comparable data is generated by tools specifically made for measuring coverage.
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{{< /hint >}}
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The following section reviews two methods to generate coverage reports: the an LLVM-based instrumentation and a GCC-based one. LLVM offers a stable and very fast way to generate coverage reports. The LLVM toolkit supports the [SanitizerCoverage](https://clang.llvm.org/docs/SanitizerCoverage.html) instrumentation that is unique to Clang and the GCC-compatible [gcov](https://gcc.gnu.org/onlinedocs/gcc/Gcov.html) instrumentation. GCC only supports the gcov instrumentation.
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The following section reviews two methods to generate coverage reports: an LLVM-based instrumentation and a GCC-based one. LLVM offers a stable and very fast way to generate coverage reports. The LLVM toolkit supports the [SanitizerCoverage](https://clang.llvm.org/docs/SanitizerCoverage.html) instrumentation that is unique to Clang and the GCC-compatible [gcov](https://gcc.gnu.org/onlinedocs/gcc/Gcov.html) instrumentation. GCC only supports the gcov instrumentation.
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Both methods allow the generation of a clear representation of coverage, with the resulting HTML report consisting of multiple pages. However, the report generation with gcov output is more inefficient and requires more time compared to the LLVM one.
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{{< /resourceFigure >}}
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**We already mentioned that gcov incrementally updates `.gcda` files over multiple runes of the coverage binaries. To start from scratch, you can manually delete all `.gcda` files after executing gcovr, or add the flag `--delete`.**
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**We already mentioned that gcov incrementally updates `.gcda` files over multiple runs of the coverage binaries. To start from scratch, you can manually delete all `.gcda` files after executing gcovr, or add the flag `--delete`.**
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