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‎LICENSE

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‎MANIFEST.in

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include LICENSE
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include README.md
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include requirements.txt

‎README.md

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stringsifter will be released on Sept 7
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<div align="center">
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<img src="misc/stringsifter-flat-dark.png" width="400">
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</div>
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--------------------------------------------------------------------------------
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StringSifter is a machine learning tool that automatically ranks strings based on their relevance for malware analysis.
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# Quick Links
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* [Technical Blogpost - *Learning to Rank Strings Output for Speedier Malware Analysis*](https://www.fireeye.com/blog/threat-research/2019/05/learning-to-rank-strings-output-for-speedier-malware-analysis.html)
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* [Announcement Blogpost - *Open Sourcing StringSifter*](https://www.fireeye.com/blog/threat-research/2019/09/open-sourcing-stringsifter.html)
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* [DerbyCon Talk - *StringSifter: Learning to Rank Strings Output for Speedier Malware Analysis*](https://docs.google.com/spreadsheets/d/1zgI0grAFNQJEtelIudSCZ1A00XcunMCubVK5RCg0VIo/edit#gid=0)
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# Usage
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StringSifter requires Python version 3.6 or newer. Run the following commands to get the code, run unit tests, and use the tool:
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## Installation
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Use `pip` to get running immediately:
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```sh
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pip install stringsifter
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```
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Alternatively, you can install an editable version locally using `git` and `pip`:
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```sh
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git clone https://github.com/fireeye/stringsifter.git
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cd stringsifter
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pip install -e .
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```
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## Running Unit Tests
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To run unit tests from the StringSifter installation directory:
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```sh
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pytest
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```
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## Running from the Command Line
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The `pip install -e <repo>` command installs two runnable scripts `flarestrings` and `rank_strings` into your python environment. `flarestrings` mimics features of GNU binutils' `strings`, and `rank_strings` accepts piped input, for example:
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```sh
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flarestrings <my_sample> | rank_strings
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```
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`rank_strings` supports a number of command line arguments. The positional argument `input_strings` specifies a file of strings to rank. The optional arguments are:
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Option | Meaning
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--- | ---
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--scores (-s) | Include the rank scores in the output
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--limit (-l) | Limit output to the top `limit` ranked strings
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--min-score (-m) | Limit output to strings with score >= `min-score`
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--batch (-b) | Specify a folder of `strings` outputs for batch processing
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Ranked strings are written to standard output unless the `--batch` option is specified, causing ranked outputs to be written to files named `<input_file>.ranked_strings`.
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`flarestrings` supports an option `-n` (or `--min-len`) to print sequences of characters that are at least `min-len` characters long, instead of the default 4. For example:
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```sh
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flarestrings -n 8 <my_sample> | rank_strings
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```
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will print and rank only strings of length 8 or greater.
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## Running from a Docker container
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- After cloning the repo, build the container. From the the package's top level directory:
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```sh
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docker build -t stringsifter -f docker/Dockerfile .
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```
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- Run the container using the `-v` flag to expose a host directory to the container:
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```sh
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docker run -v <my_malware>:/samples -it stringsifter
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```
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where `<my_malware>` contains samples for analysis, for example:
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```sh
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docker run -v $HOME/malware/binaries:/samples -it stringsifter
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```
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- At the container prompt:
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```sh
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flarestrings /samples/<my_sample> | rank_strings <options>
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```
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All [command line arguments](#running-from-the-command-line) are supported in the containerized script.
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## Running on FLOSS Output
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StringSifter can be applied to arbitrary lists of strings, making it useful for practitioners looking to glean insights from alternative intelligence-gathering sources such as live memory dumps, sandbox runs, or binaries that contain obfuscated strings. For example, [FireEye Labs Obfuscated Strings Solver (FLOSS)](https://github.com/fireeye/flare-floss) extracts printable strings just as *Strings* does, but additionally reveals obfuscated strings that have been encoded, packed, or manually constructed on the stack. It can be used as an in-line replacement for Strings, meaning that StringSifter can be similarly invoked on FLOSS output using the following command:
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```sh
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$PY2_VENV/bin/floss –q <options> <my_sample> | rank_strings <options>
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```
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Notes:
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1. The `–q` argument suppresses headers and formatting to show only extracted strings. To learn more about additional FLOSS options, please see its [Usage Docs](https://github.com/fireeye/flare-floss/blob/master/doc/usage.md).
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2. FLOSS requires Python 2, while StringSifter requires Python 3. In the example command at least one of `floss` or `rank_strings` must include a relative path referencing a python virtual enviroment.
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## Notes on running `strings`
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This distribution includes the `flarestrings` program to ensure predictable output across platforms. If you choose to run your system's installed `strings` note that its options are not consistent across versions and platforms:
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### Linux
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Most Linux distributions include the `strings` program from GNU Binutils. To extract both "wide" and "narrow" strings the program must be run twice, piping to an output file:
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```sh
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strings <my_sample> > strs.txt # narrow strings
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strings -el <my_sample> >> strs.txt # wide strings. note the ">>"
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```
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### MacOS
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Some versions of BSD `strings` packaged with MacOS do not support wide strings. Also note that the `-a` option to strings to scan the whole file may be disabled in the default configuration. Without `-a` informative strings may be lost. We recommend installing GNU Binutils via Homebrew or MacPorts to get a version of `strings` that supports wide characters. Use care to invoke the correct version of `strings`.
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### Windows
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`strings` is not installed by default on Windows. We recommend installing [Windows Sysinternals](https://docs.microsoft.com/en-us/sysinternals/), [Cygwin](https://www.cygwin.com/), or [Malcode Analyst Pack](http://sandsprite.com/iDef/MAP/) to get a working `strings`.
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# Discussion
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This version of StringSifter was trained using *Strings* outputs from sampled malware binaries associated with the first [EMBER dataset](https://github.com/endgameinc/ember). Ordinal labels were generated using weak supervision procedures, and supervised learning is performed by [Gradient Boosted Decision Trees](https://github.com/microsoft/LightGBM) with a learning-to-rank objective function. See [Quick Links](#quick-links) for further technical details. Please note that neither labeled data nor training code is currently available, though we may reconsider this approach in future releases.
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## Issues
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We use [GitHub Issues](https://github.com/fireeye/stringsifter/issues) for posting bugs and feature requests.
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## Acknowledgements
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- Thanks to the FireEye Data Science (FDS) and FireEye Labs Reverse Engineering (FLARE) teams for review and feedback.
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- StringSifter was designed and developed by Philip Tully (FDS), Matthew Haigh (FLARE), Jay Gibble (FLARE), and Michael Sikorski (FLARE).
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- The StringSifter logo was designed by Josh Langner (FLARE).
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- `flarestrings` is derived from the excellent tool [FLOSS](https://github.com/fireeye/flare-floss/blob/master/floss/strings.py#L7-L9).

‎docker/Dockerfile

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FROM conda/miniconda3
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WORKDIR /src/stringsifter
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COPY . /src/stringsifter
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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cmake \
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build-essential \
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gcc \
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g++ \
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less && \
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conda update -n base -c defaults conda && \
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pip install -r ./requirements.txt
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RUN pip install -e /src/stringsifter

‎misc/stringsifter-flat-dark.png

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