feat: add docs for fuzzing

docs/contribute/fuzzing.md

@@ -4,7 +4,98 @@ sidebar_position: 5
 
 # Fuzzing
 
-<!-- prettier-ignore -->
-:::info
-Work in Progress
+Fuzzing is a dynamic code analysis technique used to discover coding errors and security loopholes in software applications. It involves providing invalid, unexpected, or random data as inputs to a software program. This guide will walk you through the process of setting up and running fuzz tests on WasmEdge applications.
+
+## Prerequisites
+
+- WasmEdge Runtime and API
+- C++ Compiler (e.g., GCC or Clang)
+- Fuzzing tool (e.g., AFL, libFuzzer)
+- Basic knowledge of C++ and WebAssembly
+
+## How to Fuzz Test
+
+### Step 1: Install Fuzzing Tool
+
+For this guide, we'll use [AFL (American Fuzzy Lop)](https://github.com/google/AFL) as the fuzzing tool. Install it using the package manager for your OS. 
+
+For Ubuntu:
+
+```bash
+sudo apt-get install afl
+```
+
+### Step 2: Prepare the WasmEdge Application
+
+Ensure that your WasmEdge application is compiled and ready for testing. Identify the functions that you want to fuzz. These are typically functions that handle file I/O, data parsing, or any form of external input.
+
+### Step 3: Write a Fuzzing Target
+
+Create a C++ file that will serve as your fuzzing target. This file should include the WasmEdge API and should call the function you want to fuzz.
+
+```cpp
+#include <wasmedge.h>
+
+extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) {
+  WasmEdge::Configure Conf;
+  WasmEdge::VM VM(Conf);
+
+  if (VM.loadWasm(Data, Size)) {
+    VM.validate();
+    VM.instantiate();
+    VM.execute("your_function", {/* optional args */});
+  }
+
+  return 0;
+}
+```
+
+### Step 4: Compile the Fuzzing Target
+
+Compile the fuzzing target with AFL's version of the compiler and enable the fuzzing mode.
+
+```bash
+afl-g++ -o fuzz_target fuzz_target.cpp -lwasmedge_c_api
+```
+
+### Step 5: Run the Fuzzer
+
+Run AFL to start fuzzing.
+
+```bash
+afl-fuzz -i input_dir/ -o output_dir/ ./fuzz_target @@
+```
+
+Here, `input_dir` is a directory containing sample input files, and `output_dir` is where AFL will store the results.
+
+### Step 6: Analyze Results
+
+AFL will generate a lot of data, including:
+
+- Queue: Test cases that exhibit new behaviors.
+- Crashes: Inputs that caused the program to crash.
+- Hangs: Inputs where the program took too long to execute.
+
+Review these files to understand the vulnerabilities or bugs in your application.
+
+## Best Practices
+
+- **Start Small:** Use simple input files initially to help the fuzzer understand the basic program behavior.
+- **Code Coverage:** Use tools like afl-cov to measure code coverage and ensure that the fuzzer is exercising all code paths.
+- **Continuous Fuzzing:** Integrate fuzzing into your CI/CD pipeline to catch issues early.
+
+
+Fuzzing is an effective way to discover vulnerabilities and bugs that might not be apparent through conventional testing methods. By following this guide, you can set up a robust fuzzing workflow for your WasmEdge applications, thereby enhancing their security and reliability.
+
+:::note
+If you need a Wasm specific fuzzer, this https://github.com/wasmerio/wasm-fuzz/ can give more infomation and details pertaining to your use cases
 :::
+
+### Further References
+
+- https://github.com/wasmerio/wasm-fuzz/blob/master/afl.md
+- https://github.com/rust-fuzz/afl.rs
+- https://rust-fuzz.github.io/book/introduction.html
+- https://lcamtuf.coredump.cx/afl/
+- https://afl-1.readthedocs.io/en/latest/
+- https://en.wikipedia.org/wiki/American_fuzzy_lop_(fuzzer)

i18n/zh/docusaurus-plugin-content-docs/current/contribute/fuzzing.md

@@ -4,7 +4,98 @@ sidebar_position: 5
 
 # Fuzzing
 
-<!-- prettier-ignore -->
-:::info
-Work in Progress
+Fuzzing is a dynamic code analysis technique used to discover coding errors and security loopholes in software applications. It involves providing invalid, unexpected, or random data as inputs to a software program. This guide will walk you through the process of setting up and running fuzz tests on WasmEdge applications.
+
+## Prerequisites
+
+- WasmEdge Runtime and API
+- C++ Compiler (e.g., GCC or Clang)
+- Fuzzing tool (e.g., AFL, libFuzzer)
+- Basic knowledge of C++ and WebAssembly
+
+## How to Fuzz Test
+
+### Step 1: Install Fuzzing Tool
+
+For this guide, we'll use [AFL (American Fuzzy Lop)](https://github.com/google/AFL) as the fuzzing tool. Install it using the package manager for your OS. 
+
+For Ubuntu:
+
+```bash
+sudo apt-get install afl
+```
+
+### Step 2: Prepare the WasmEdge Application
+
+Ensure that your WasmEdge application is compiled and ready for testing. Identify the functions that you want to fuzz. These are typically functions that handle file I/O, data parsing, or any form of external input.
+
+### Step 3: Write a Fuzzing Target
+
+Create a C++ file that will serve as your fuzzing target. This file should include the WasmEdge API and should call the function you want to fuzz.
+
+```cpp
+#include <wasmedge.h>
+
+extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) {
+  WasmEdge::Configure Conf;
+  WasmEdge::VM VM(Conf);
+
+  if (VM.loadWasm(Data, Size)) {
+    VM.validate();
+    VM.instantiate();
+    VM.execute("your_function", {/* optional args */});
+  }
+
+  return 0;
+}
+```
+
+### Step 4: Compile the Fuzzing Target
+
+Compile the fuzzing target with AFL's version of the compiler and enable the fuzzing mode.
+
+```bash
+afl-g++ -o fuzz_target fuzz_target.cpp -lwasmedge_c_api
+```
+
+### Step 5: Run the Fuzzer
+
+Run AFL to start fuzzing.
+
+```bash
+afl-fuzz -i input_dir/ -o output_dir/ ./fuzz_target @@
+```
+
+Here, `input_dir` is a directory containing sample input files, and `output_dir` is where AFL will store the results.
+
+### Step 6: Analyze Results
+
+AFL will generate a lot of data, including:
+
+- Queue: Test cases that exhibit new behaviors.
+- Crashes: Inputs that caused the program to crash.
+- Hangs: Inputs where the program took too long to execute.
+
+Review these files to understand the vulnerabilities or bugs in your application.
+
+## Best Practices
+
+- **Start Small:** Use simple input files initially to help the fuzzer understand the basic program behavior.
+- **Code Coverage:** Use tools like afl-cov to measure code coverage and ensure that the fuzzer is exercising all code paths.
+- **Continuous Fuzzing:** Integrate fuzzing into your CI/CD pipeline to catch issues early.
+
+
+Fuzzing is an effective way to discover vulnerabilities and bugs that might not be apparent through conventional testing methods. By following this guide, you can set up a robust fuzzing workflow for your WasmEdge applications, thereby enhancing their security and reliability.
+
+:::note
+If you need a Wasm specific fuzzer, this https://github.com/wasmerio/wasm-fuzz/ can give more infomation and details pertaining to your use cases
 :::
+
+### Further References
+
+- https://github.com/wasmerio/wasm-fuzz/blob/master/afl.md
+- https://github.com/rust-fuzz/afl.rs
+- https://rust-fuzz.github.io/book/introduction.html
+- https://lcamtuf.coredump.cx/afl/
+- https://afl-1.readthedocs.io/en/latest/
+- https://en.wikipedia.org/wiki/American_fuzzy_lop_(fuzzer)