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Detect and Remediate the risk of exposing secrets and credentials
TL;DR:
In today's fast-paced development environment, GitHub has become an indispensable tool for product and engineering teams. However, with its extensive use comes the increased risk of inadvertently exposing sensitive data, such as credentials, secrets, Personally Identifiable Information (PII), and Protected Health Information (PHI). Strac's Data Loss Prevention (DLP) solution for GitHub is designed to address these challenges, ensuring your repositories are secure and compliant with industry regulations.
GitHub repositories often contain sensitive information that, if exposed, can lead to significant security breaches. These breaches can compromise your customer data, intellectual property, and internal communications. By implementing a robust DLP solution, you can proactively detect and remediate these risks, protecting your organization's valuable assets.
With regulations such as GDPR, HIPAA, and CCPA becoming more stringent, compliance is a top priority for organizations. A DLP solution for GitHub helps ensure that your repositories adhere to these regulations by automatically identifying and managing sensitive data, reducing the risk of non-compliance and potential fines.
Even the most diligent developers can accidentally commit sensitive information. A DLP solution provides an additional layer of protection, scanning code for sensitive data and preventing it from being exposed in the first place. This minimizes the risk of human error and helps maintain a secure development environment.
Strac's GitHub DLP integrates seamlessly with your existing workflow. With just a few clicks, you can set up the integration and start protecting your repositories. There's no need to install any agents, and the solution works in the background, providing continuous protection without disrupting your team's productivity.
Strac utilizes machine learning-based detectors to identify sensitive data across 100+ file types, including images and unstructured data. These detectors are trained to recognize a wide range of sensitive information, such as PII, PCI, PHI, credentials, and secrets. By leveraging context-based ML detectors, Strac ensures high accuracy and minimizes false positives.
Strac provides real-time alerts for any detected sensitive data, allowing you to take immediate action. Automated remediation workflows can be set up to quarantine, delete, or alert on sensitive findings, reducing the compliance workload and enabling proactive protection. Notifications and coaching can also be provided to end-users, educating them on data security best practices and fostering a culture of strong data security hygiene.
With Strac, you can manage all your security tasks from a single, intuitive dashboard. Create flexible DLP policies for targeted scans and customize detectors with thresholds and rules to meet your organization's specific needs. The centralized dashboard provides visibility into security risks, enabling you to minimize them effectively and ensure continuous compliance.
Strac's GitHub DLP solution goes beyond mere detection and remediation. By educating users on data security best practices and involving them in the remediation process, you can build a strong first line of defense against security threats. This not only enhances security but also empowers your team to take an active role in protecting sensitive data.ni
Please contact hello@strac.io for any questions
