Strelka is a real-time, container-based file scanning system used for threat hunting, threat detection, and incident response. Originally based on the design established by Lockheed Martin's Laika BOSS and similar projects (see: related projects), Strelka's purpose is to perform file extraction and metadata collection at enterprise scale.

Strelka differs from its sibling projects in a few significant ways:

• Core codebase is Go and Python3.10+
• Server components run in containers for ease and flexibility of deployment
• OS-native client applications for Windows, Mac, and Linux
• Built using libraries and formats that allow cross-platform, cross-language support

Strelka is a modular data scanning platform, allowing users or systems to submit files for the purpose of analyzing, extracting, and reporting file content and metadata. Coupled with a SIEM, Strelka is able to aggregate, alert, and provide analysts with the capability to better understand their environment without having to perform direct data gathering or time-consuming file analysis.

Running a file through Strelka is simple. In this section, Strelka capabilities of extraction and analysis are demonstrated for a one-off analysis.

Please review the documentation for details on how to properly build and deploy Strelka in an enterprise environment.

# Ubuntu 23.04
sudo apt install -y wget git docker docker-compose golang jq && \
sudo usermod -aG docker $USER && \
newgrp docker

git clone https://github.com/target/strelka.git && \
cd strelka

rm configs/python/backend/yara/rules.yara && \
git clone https://github.com/Yara-Rules/rules.git configs/python/backend/yara/rules/ && \
echo 'include "./rules/index.yar"' > configs/python/backend/yara/rules.yara

Note: You can skip the go build process and use the Strelka UI at http://0.0.0.0:9980 to analyze files.

docker-compose -f build/docker-compose-no-build.yaml up -d && \
go build github.com/target/strelka/src/go/cmd/strelka-oneshot

Note: You can skip the go build process and use the Strelka UI at http://0.0.0.0:9980 to analyze files.

docker-compose -f build/docker-compose.yaml build && \
docker-compose -f build/docker-compose.yaml up -d && \
go build github.com/target/strelka/src/go/cmd/strelka-oneshot

Use any malware sample, or other file you'd like Strelka to analyze.

wget https://github.com/ytisf/theZoo/raw/master/malware/Binaries/Win32.Emotet/Win32.Emotet.zip -P samples/

./strelka-oneshot -f samples/Win32.Emotet.zip -l - | jq

1. Strelka determined that the submitted file was an encrypted ZIP (See: taste.yara backend.yaml)
2. ScanEncryptedZip used a dictionary to crack the ZIP file password, and extract the compressed file
3. The extracted file was sent back into the Strelka pipeline by the scanner, and Strelka determined that the extracted file was an EXE
4. ScanPe dissected the EXE file and added useful metadata to the output
5. ScanYara analyzed the EXE file, using the provided rules, and added numerous matches to the output, some indicating the file might be malicious

The following output has been edited for brevity.

{
  "file": {
    "depth": 0,
    "flavors": {
      "mime": ["application/zip"],
      "yara": ["encrypted_zip", "zip_file"]
    },
    "scanners": [
      "ScanEncryptedZip",
      "ScanEntropy",
      "ScanFooter",
      "ScanHash",
      "ScanHeader",
      "ScanYara",
      "ScanZip"
    ]
  },
  "scan": {
    "encrypted_zip": {
      "cracked_password": "infected",
      "elapsed": 0.114269,
      "total": {"extracted": 1, "files": 1}
    }
  }
}

{
  "file": {
    "depth": 1,
    "flavors": {
      "mime": ["application/x-dosexec"],
      "yara": ["mz_file"]
    },
    "name": "29D6161522C7F7F21B35401907C702BDDB05ED47.bin",
    "scanners": [
      "ScanEntropy",
      "ScanFooter",
      "ScanHash",
      "ScanHeader",
      "ScanPe",
      "ScanYara"
    ]
  },
  "scan": {
    "pe": {
      "address_of_entry_point": 5168,
      "base_of_code": 4096,
      "base_of_data": 32768,
      "checksum": 47465,
      "compile_time": "2015-03-31T08:53:51",
      "elapsed": 0.013076,
      "file_alignment": 4096,
      "file_info": {
        "company_name": "In CSS3",
        "file_description": "Note: In CSS3, the text-decoration property is a shorthand property for text-decoration-line, text-decoration-color, and text-decoration-style, but this is currently.",
        "file_version": "1.00.0065",
        "fixed": {"operating_systems": ["WINDOWS32"]},
        "internal_name": "Callstb",
        "original_filename": "NOFAstb.exe",
        "product_name": "Goodreads",
        "product_version": "1.00.0065",
        "var": {"character_set": "Unicode", "language": "U.S. English"}
      }
    },
    "yara": {
      "elapsed": 0.068918,
      "matches": [
        "SEH__vba",
        "SEH_Init",
        "Big_Numbers1",
        "IsPE32",
        "IsWindowsGUI",
        "HasOverlay",
        "HasRichSignature",
        "Microsoft_Visual_Basic_v50v60",
        "Microsoft_Visual_Basic_v50",
        "Microsoft_Visual_Basic_v50_v60",
        "Microsoft_Visual_Basic_v50_additional",
        "Microsoft_Visual_Basic_v50v60_additional"
      ],
      "tags": [
        "AntiDebug",
        "SEH",
        "Tactic_DefensiveEvasion",
        "Technique_AntiDebugging",
        "SubTechnique_SEH",
        "PECheck",
        "PEiD"
      ]
    }
  }
}

If Strelka was deployed and ingesting files in your environment, you might be collecting these events in your SIEM. With this analysis, you could write a rule that looks for events matching the suspicious yara tags, alerting you to a potentially malicious file.

scan.yara.tags:("Technique_AntiDebugging" && "SubTechnique_SEH")

Strelka's UI is available when you build the provided containers. This web interface allows you to upload files to Strelka and capture the events, which are stored locally.

Navigate to http://localhost:9980/ and use the login strelka/strelka.

With over 50 file scanners for the most common file types (e.g., exe, docx, js, zip), Strelka provides users with the ability to gain new insights into files on their host, network, or enterprise. While Strelka is not a detection engine itself (although it does utilize YARA, it can provide enough metadata to identify suspicious or malicious files. Some potential uses for Strelka include:

More documentation about Strelka can be found in the README, including:

• Installation
• Deployment
• Design
• Architecture
• FAQ

Guidelines for contributing can be found here.

Users are advised to precompile their YARA rules for optimal performance and to avoid potential issues during runtime. Using precompiled YARA files helps in reducing load time and resource usage, especially in environments with a large set of rules. Ensure to use the compiled option in the Strelka configuration to point to the precompiled rules file.

See issues labeled bug in the tracker for any additional issues.

• Laika BOSS
• File Scanning Framework
• Assemblyline

Strelka and its associated code is released under the terms of the Apache 2.0 License.