HoundDog.ai's code scanner is designed to proactively detect issues related to sensitive data mishandling and leakages early in the development cycle. By using the application’s source code as the source of truth, security teams can ensure data security controls are integrated from the start, rather than later when the data is already in production. This shift-left approach reduces the risk of breaches from issues involving sensitive data being stored in logs, files, tokens, cookies, or when shared through APIs and with third-party systems.
- Java
- SQL
- GraphQL
- OpenAPI / Swagger
Name | Description | Default |
---|---|---|
output_format |
Output format. Allowed values are console , markdown and sarif . |
sarif |
output_filename |
Output filename. Not applicable for the console output format. |
hounddog.sarif |
For more configuration options, please see the HoundDog.ai documentation.
The GitHub Actions workflow below runs a HoundDog.ai scan on and uploads the results to GitHub Advanced Security:
name: HoundDog.ai Scan
on:
pull_request:
branches: [ main ]
jobs:
hounddog:
runs-on: ubuntu-latest
permissions:
contents: read
security-events: write
steps:
- name: Checkout repository
uses: actions/checkout@master
- name: Run HoundDog.ai scan
uses: hounddogai/hounddog-action@v1
with:
output_format: sarif
output_filename: hounddog.sarif
- name: Upload scan results to GitHub Advanced Security
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: hounddog.sarif
If you need any help or would like to send us feedback, please shoot us an email at [email protected].