Git Product home page Git Product logo

github-action-add-sarif-contextual-training's Introduction

GitHub Action

This GitHub Action adds Secure Code Warrior contextual application security training material to SARIF files. This training material will be displayed within Code Scanning alerts if the resulting SARIF file is imported using the github/codeql-action/upload-sarif Action, and includes links to secure coding exercises and short explainer videos where available.

This Action currently supports adding training material based on CWE references (e.g. CWE 89) and common vulnerability phrases (e.g. use-after-free vulnerability) included in static analysis findings.

Usage

Individual SARIF file

    steps:
      # Fetch SARIF - for example:
      # - Checkout the repository using `actions/checkout` if the SARIF file is committed. This example assumes the SARIF file is located at `sarif/findings.sarif` within the repository.
      #     - name: Checkout repository
      #       uses: actions/checkout@v2
      # - Fetch the SARIF file from your SAST tool. The vendor may already have a GitHub Action for this. This example assumes the SARIF file is fetched and saved to `sarif/findings.sarif`.
      #     - name: Download SARIF
      #       uses: vendor/sast-tool-sarif@v1
      #       with:
      #         user: ${{ secrets.USER }}
      #         key: ${{ secrets.KEY }}
      #         scan-id: ${{ secrets.SCAN_ID }}
      #         output-file: sarif/findings.sarif
      # - Convert a SAST tool report into SARIF. The vendor may already have a GitHub Action or script for this. This example assumes the converted SARIF file is located at `sarif/findings.sarif`.
      #     - name: Convert report to SARIF
      #       uses: vendor/sast-tool-sarif-converter@v1
      #       with:
      #         report-file: reports/sast-scan.xml
      #         output-file: sarif/findings.sarif

      - name: Add SCW Training
        uses: SecureCodeWarrior/github-action-add-sarif-contextual-training@v1
        with:
          inputSarifFile: sarif/findings.sarif
          outputSarifFile: sarif/findings.processed.sarif
          githubToken: ${{ secrets.GITHUB_TOKEN }}

      - name: Import Results
        uses: github/codeql-action/upload-sarif@v1
        with:
          sarif_file: sarif/findings.processed.sarif

Multiple SARIF files using glob path

    steps:
      # Fetch SARIF - see additional examples above
      - name: Download SARIF
        uses: vendor/sast-tool-sarif@v1
        with:
          user: ${{ secrets.USER }}
          key: ${{ secrets.KEY }}
          scan-id: ${{ secrets.SCAN_ID }}
          output-dir: ./sarifs # in this example we assume the tool outputs multiple SARIF files as .json files

      - name: Add SCW Training
        uses: SecureCodeWarrior/github-action-add-sarif-contextual-training@v1
        with:
          inputSarifFile: ./sarifs/*.json
          outputSarifFile: ./processed-sarifs
          githubToken: ${{ secrets.GITHUB_TOKEN }}

      - name: Import Results
        uses: github/codeql-action/upload-sarif@v1
        with:
          sarif_file: ./processed-sarifs

Multiple SARIF files in directory

    steps:
      # Fetch SARIF - see additional examples above
      - name: Download SARIF
        uses: vendor/sast-tool-sarif@v1
        with:
          user: ${{ secrets.USER }}
          key: ${{ secrets.KEY }}
          scan-id: ${{ secrets.SCAN_ID }}
          output-dir: ./sarifs # in this example we assume the tool outputs multiple SARIF files in nested directories within the specified output directory

      - name: Add SCW Training
        uses: SecureCodeWarrior/github-action-add-sarif-contextual-training@v1
        with:
          inputSarifFile: ./sarifs
          outputSarifFile: ./processed-sarifs
          githubToken: ${{ secrets.GITHUB_TOKEN }}

      - name: Import Results
        uses: github/codeql-action/upload-sarif@v1
        with:
          sarif_file: ./processed-sarifs

Inputs

inputSarifFile

The SARIF file(s) to add Secure Code Warrior contextual training material to. This can be a path to a single file (e.g. ./findings.sarif), a glob path (e.g. ./scans/**/*.sarif) or a directory (d.g. ./scans), in which case all .sarif files recursively in the specified directory will be processed. Default value: ./findings.sarif

outputSarifFile

The output path of the resulting SARIF file(s) with Secure Code Warrior contextual training material appended. If a glob path or a directory was provided as the inputSarifFile input then the resulting SARIF files will be output to the ./processed-sarifs directory, which can then simply be the path provided in the sarif_file input of the github/codeql-action/upload-sarif action. Default value: ./findings.processed.sarif

githubToken (optional)

Provide ${{ secrets.GITHUB_TOKEN }} to use the GitHub access token automatically supplied by GitHub Workflows. This enables language-specific training links to be generated (where available) by fetching the repository language from the GitHub API.

github-action-add-sarif-contextual-training's People

Contributors

cwong-scw avatar dependabot[bot] avatar awildbrysen avatar

Stargazers

Gérard jourdain avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.