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mquery: Blazingly fast Yara queries for malware analysts

Ever had trouble searching for malware samples? Mquery is an analyst-friendly web GUI to look through your digital warehouse.

It can be used to search through terabytes of malware in a blink of an eye:

mquery web GUI a query on 2.1M files

Under the hood we use our UrsaDB, to accelerate yara queries with ngrams.


Public instance will be created soon, stay tuned...


1. Install and start

The easiest way to do this is with docker-compose:

git clone --recurse-submodules
cd mquery
vim .env  # optional - change samples and index directory locations
docker-compose up --scale daemon=3  # building the images will take a while

The web interface should be available at http://localhost.

(For more installation options see the installation manual ).

2. Add the files

Put some files in the SAMPLES_DIR (by default ./samples in the repository, configurable with variable in the .env file).

3. Index your collection

If you use the default configuration, just click "reindex" button on the status page:

This will scan samples directory for all new files and index them. You can monitor the progress in the tasks window on the left:

You have to repeat this process every time you want to add new files!

After indexing is over, you will notice new datasets:

Merging datasets takes time, but having too many datasets slows mquery down. Click compact button to merge some datasets with each other (or use the compactall script).

After this process, you end up with a nice, clean index:

This is a good and easy way to start, but if you have a big collection you are strongly encouraged to read indexing page in the manual.

4. Test it

Now your files should be searchable - insert any Yara rule into the search window and click Query. Just for demonstration, I've indexed the source code of this application and tested this Yara rule:

rule mquery_exceptions {
    strings: $a = "Exception"
    condition: all of them

Learn more

See the documentation to learn more. Probably a good idea if you plan a bigger deployment.

You can also read the hosted version here:


See the installation instruction.


If you want to contribute, see our dedicated documentation for contributors.


Learn how the project has changed by reading our release log.


If you have any problems, bugs or feature requests related to mquery, you're encouraged to create a GitHub issue.

If you have questions unsuitable for github, you can email CERT.PL ( directly.