# MIST – a tool pairing SAST and Fuzzing for smarter Bug Hunting > Source: > Published: 2026-10-28 20:04:52+00:00 **Smoothly transform static analysis findings into tailored fuzzing campaigns.** MIST orchestrates the vulnerability analysis workflow, standardizing and automating the steps unifying SAST and DAST, so that you can focus on security reasoning while it takes care of the analysis pipeline. **Designed to remain comparatively lightweight while obtaining competitive efficiency.** MIST integrates technologies, including Directed Greybox Fuzzing (DGF) and pattern-based static analysis, that once synergized can achieve results comparable to state-of-the-art approaches, such as Symbolic Execution (SE) and semantic code analysis, maintaining considerably lower time and computational complexities. **For developers.** MIST can be employed as a light, modular and extensible Python framework, to create new plugins and standalone tools. The whole project is realeased under the Apache License 2.0, and its source code is freely available to inspect, study, modify, extend, and build upon, encouraging experimentation and further development. *"Given enough eyeballs, all bugs are shallow"* Clone and enter the repository: ``` git clone https://github.com/alessandroPalazzolo/mist.git cd mist ``` - The local installation supports all features and is recommended for more in-depth and advanced use. However, when dealing with fuzz testing, some operations may directly affect the host system, so additional care is required. Some additional tweaking might be required based on your system configuration. - The containerized version provides complete isolation from the host system, making it the safest option while providing a ready-to-use environment. Nonetheless, as documented in the relevant section, some features may be limited or behave differently due to Docker's isolation mechanisms. Docker is therefore recommended for testing MIST or trying it for the first time. Below are the steps required for the **local installation**. See the [Docker](#run-mist-with-docker) section to run MIST in a container. Create and activate a virtual environment (unless you want a global install): ``` python3 -m venv .venv source .venv/bin/activate ``` Install the python3 `mist` wheel with dependencies: ``` pip install -e . ``` Mist leverages AFLGo directed greybox fuzzer for DAST. See more at [https://github.com/aflgo/aflgo](https://github.com/aflgo/aflgo). Caution AFLGo build script will attempt to apply modifications on your host system, potentially affecting your existing compiler toolchain. The AFLGo [documentation](https://github.com/alessandroPalazzolo/mist/blob/main/AFLGo/Readme.md) explains each action taken in depth, still, if you don't feel confident with it you might want to check the Docker [installation](#run-mist-with-docker). Build the fuzzer: ``` cd AFLGo sudo ./build.sh cd .. ``` You ideally only need this to make AFLGo work. If you encounter any issue refer to the official [documentation](https://github.com/alessandroPalazzolo/mist/blob/main/AFLGo/Readme.md) for better support. Note MIST only works with a slightly modified version of AFLGo, see more at [THIRD_PARTY_NOTICES](https://github.com/alessandroPalazzolo/mist/blob/main/THIRD_PARTY_NOTICES.md). You can provide a custom AFLGo version, but should only apply your edits on the one shipping with MIST. Tip if you don't wish to use a global custom `semgrep` installation you can skip this step. MIST employs Semgrep capabilities for efficient SAST. See more at [https://docs.semgrep.dev](https://docs.semgrep.dev). Semgrep conveniently exposes a python package that can be installed with `pip install semgrep`, for this reason it is already included as a `mist` wheel dependency and should be locally installed. If you wish to use a global `semgrep` installation you need to run: ``` pipx install semgrep ``` then proceed to edit your `$PATH` accordingly, so that `mist` sees it first. You can now start exploring MIST by simply typing: ``` mist ``` Seamlessly build and run MIST using Docker Compose. Assuming that you are in the `mist/` root directory, run: ``` H_WORKSPACE= docker compose run --rm mist ``` Replace `` with the path to the host directory containing the systems you want to test (SUTs), this will bind it to the container. If it's the first time you run it, Docker Compose will pull and build all the required assets (this might take a few minutes). After that, it will automatically start the container with `mist` running inside of it. You can use again the same command every time you want to start MIST. Note Some MIST features may be limited or behave differently in Docker. - **High performance fuzzing:** MIST optionally leverages the[afl-system-config](https://github.com/alessandroPalazzolo/mist/blob/main/AFLGo/afl-2.57b/afl-system-config) script to reconfigure the host system to a high performance fuzzing state. The script requires elevated privileges and performs host-level system configurations, making it not suitable for a Docker container environment. - **Split view of AFLGo and MIST Monitor UIs:** during fuzz time, by default, MIST launches[afl-fuzz](https://github.com/alessandroPalazzolo/mist/blob/main/AFLGo/afl-2.57b/afl-fuzz.c) in a separate terminal window to provide its interactive UI alongside the MIST Monitor one. This functionality is not supported in Docker containers, resulting in a less informative runtime that can only show MIST relevant metrics. If you wish to get more insights on the fuzzer runtime you can access the`//obj-aflgo/out/fuzzer_stats` host file, with SUT being your current system under test. Once installed, you can check if your MIST instance correctly works by testing it on a simple default SUT. The SUT is provided in the [test-system](https://github.com/alessandroPalazzolo/mist/blob/main/test-system) directory. Inside you'll find additional [documentation](https://github.com/alessandroPalazzolo/mist/blob/main/test-system/README.md) on how to proceed. Start your MIST instance and set your SUT to `./test-system`. The wizard will then guide you through the next steps. - `AFLGo/` is the aflgo source directory. - `mist/` is the MIST source directory. - `test-system/` contains the default system for testing MIST. - `testcases/` contains a multitude of file samples used for fuzzing. - `.gitattributes` - `.gitignore` - `Dockerfile` is the Docker configuration file for running MIST in a container. - `LICENSE.txt` is the Apache 2.0 license file. - `README.md` - `THIRD_PARTY_NOTICES.md` keeps a log of included third-party packages with their related MIST modifications. - `compose.yaml` is the Docker compose configuration file. - `pyproject.toml` is the python configuration file used to install MIST sources. - `logo.png` is MIST logo. Copyright © 2026 Alessandro Palazzolo. MIST is distributed under the [Apache License 2.0](https://github.com/alessandroPalazzolo/mist/blob/main/LICENSE.txt).