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Cloud-native DLP for GitHub
Detect sensitive data in your GitHub repositories
Nightfall leverages machine learning to detect a wide range of potentially sensitive data in GitHub repositories – ensuring data like secrets, PII, and more are kept safe.

Nightfall leverages machine learning to detect a wide range of potentially sensitive data in GitHub repositories – ensuring data like secrets, PII, and more are kept safe.
Comprehensive data loss prevention (DLP) designed for GitHub
Nightfall is a best-in-class solution that leverages machine learning to detect a broad range of sensitive data types in GitHub.
- Automatically detect a broad set of sensitive data, including PII and credentials & secrets, using Nightfall’s ML-trained detectors.
- Identify sensitive data across public and private repositories & easily manage your remediation workflow.
- Discover unknown unknowns with no prior tuning or tagging needed.

Configure your secrets and PII detection requirements to meet your organization’s needs
Nightfall enables you to configure scans to effectively prioritize and resolve data policy violations.
- Create custom detectors & detection rules.
- Configure Nightfall’s Detection Engine with context rules, confidence scores, and more.
- Unparalleled accuracy via deep learning, for low-noise results.

Streamline your cloud DLP approach
Nightfall is easy to implement and provides you with a single pane of glass to centralize your data security approach across applications.
- Integrate with GitHub in just a few clicks.
- Export scan results for use in other systems.
- Use Nightfall to discover and protect sensitive data across other cloud apps in addition to GitHub.

Acquia protects against data exposure with Nightfall
Acquia integrated Nightfall into their security stack to protect sensitive information like API tokens, secrets, and passwords from improper exposure.
Read the Acquia case study