This project gives you access to our repository of Analytic Stories--themed security guides that contain that provide background on TTPs, mapped to the MITRE framework, the Lockheed Martin Kill Chain, and CIS controls. They include Splunk searches, machine-learning algorithms, and Splunk Phantom playbooks (where available)—all designed to work together to detect, investigate, and respond to threats.

While this content is available via Splunk Enterprise Security and Enterprise Security Content Updates (https://splunkbase.splunk.com/app/3449/), we have now made it available as an open-source project (which you just found--hi!). The Security Research Content Exchange was designed to bring the community together to improve our collective defenses. By sharing research and analytics, we can help the entire industry craft more effective strategies. This project provides a mechanism to facilitate this exchange.

Usage

The Splunk Security Content Exchange can be used via:

Splunk App

Grab the latest release of DA-ESS-ContentUpdate and install it on a Splunk Enterprise server (search head).

API

curl -s https://content.splunkresearch.com | jq
{
  "hello": "welcome to Splunks Research security content api",
  "available_endpoints": [
    "/stories",
    "/detections",
    "/investigations",
    "/baselines",
    "/responses",
    "/package"
  ]
}

How to Get Started

While you you can configure each detection individually, the real power lies in running the Analytic Stories end-to-end. Using the Analytic Story Execution (ASX) app (https://github.com/splunk/analytic_story_execution), you can funnel the results to investigations, reducing the need for manual intervention. When available, you can automatically trigger reponses, as well. The alerts you'll get include context (history, correlations, etc.), so they help you better understand their importance. The net effect is a more efficient workflow, as well as more comprehensive, effective defenses.

Follow the instructions below to get started.

What's in an Analytic Story?

Analytic Stories and their corresponding searches are composed of .yml files (manifests) and associated .conf files. The stories reside in /stories and the searches live in /detections.

Manifests contain a number of mandatory and optional fields. You can see the full field list for each piece of content here.

Writing Content

Before you begin, follow the steps to install dependencies and pre-commit hooks under "Developing".

Select the content piece you want to write.
Copy an example and edit it to suit your needs. At a minimum, you must write a story, a detection search, and an investigative search.
Make a pull request. The pull request will trigger CircleCI, a continuous-integration app thatintegrates with a VCS and automatically runs a series of steps every time that it detects a change to your repository. A CircleCI build consists of a series of steps, usually Dependencies, Testing, and Deployment. If your tests pass, you're good to go! If the CircleCI check fails, refer to troubleshooting.

For a more detailed explanation on how to contribute to the project, please see "Contributing"

Security Content Layout

Content Parts

stories/: All Analytic Stories
detections/: Splunk Enterprise, Splunk UBA, and Splunk Phantom detections that power Analytic Stories
investigations/: Splunk Enterprise and Splunk Phantom investigative searches and playbooks employed by Analytic Stories
responses/: Automated Splunk Enterprise and Splunk Phantom responses triggered by Analytic Stories
baselines/: Splunk Phantom and Splunk Enterprise baseline searches needed to support detection searches in Analytic Stories

Supporting Parts

package/: Splunk content app-source files, including lookups, binaries, and default config files
bin/: All binaries required to produce and test content

Docs

docs/: Documentation for all spec files
spec/: All spec files that describe the security content

Developing

Dependecies and Pre-Commit Hooks

Install project dependecies and tests that run before content is committed:

Create virtualenv and install requirements: virtualenv venv && source venv/bin/activate && pip install -r requirements.txt.
Install pre-commit install.

CI Tools

Tools that help with testing CI jobs:

Install CircleCI CLI Tool.
To test a local change to CircleCI or build, make sure you are running Docker, then enter circleci local execute -e GITHUB_TOKEN=$GITHUB_TOKEN --branch <your branch>.

Generate Docs from Schema

To automatically generate docs from schema:

Install https://github.com/adobe/jsonschema2md.
Enter jsonschema2md -d spec/v2/detections.spec.json -o docs.

Troubleshooting

Our Automated Tests

CI validates that the content was written to spec using validate.py. To run validation manually, run: python bin/validate.py --path . --verbose.
CI generates Splunk configuration files using generate.py. If you want to export Splunk .conf files manually from the content, run python bin/generate.py --path . --output package --verbose.
CI builds a DA-ESS-ContentUpdate Splunk package using the Splunk Packaging Toolkit.
CI tests the newly produced package using Splunk Appinspect.

note that requirements.txt hard codes the versions for packages we use dependabot to make sure we safely always upgrade to the latest versions.

Support

Please use the GitHub Issue Tracker to submit bugs or request features.

If you have questions or need support, you can:

Post a question to Splunk Answers
Join the #security-research room in the Splunk Slack channel
If you are a Splunk Enterprise customer with a valid support entitlement contract and have a Splunk-related question, you can also open a support case on the https://www.splunk.com/ support portal

Contributing

We welcome feedback and contributions from the community! Please see our contribution guidelines for more information on how to get involved.

To Dos

Build CLI for interacting and developing