BigBasket Reduces Risks and Costs in AWS with Sentra

The Risk: Leveraging IP Creates Exposure

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For manufacturers, intellectual property is everything. Formulas, patents, designs, and recipes are the secret sauce that fuel competitiveness. This critical data must flow through R&D teams, testing labs, and production lines to keep the business moving and thriving.

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But in the cloud, this same accessibility that fuels innovation becomes a liability. Blueprints get duplicated in public OneDrives, recipes are stored in shared folders, and patents are over-permissioned to contractors or partners. A single accidental exposure can mean stolen IP, lost contracts, and potentially catastrophic business, financial, or reputational damage.
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Security leaders need an accurate, efficient way to know exactly where intellectual property lives across their entire environment, who has access, and when and where it is copied or moved.
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How Sentra Helps Security Teams Protect Critical IP

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Sentra is built to transform how enterprises safeguard the data that matters most, at the speed and scale of modern cloud enterprises. The AI-powered platform automatically and continuously discovers, classifies, and protects both proprietary intellectual property and regulated customer data across multi-cloud and on-premises environments.

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• Automatically discovers and classifies critical data, finding intellectual property everywhere it lives, including patents, designs, CAD files, formulas, communications, images, audio, and video files.
• Alerts about over-exposed IP to enforce least-privilege access so only the right teams and partners can access sensitive files.
• Automatically apply DLP labels for consistent controls across Microsoft 365 Purview, Google Drive, and AWS resource tagging.
• Continuously monitor in real time when files containing IP are overshared or moved and
  automatically detect similar sensitive data.
• Securely adopt AI while preventing privacy and compliance violations and sensitive corporate data
  leakage.
• Reduce risk at scale with agentless scanning that avoids outages, API throttling, or compute spikes.

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With Sentra, organizations can embrace cloud and AI with confidence; securing their most valuable IP assets without slowing down innovation or production.

Why Security Teams Choose Sentra to Stop Insider Threats Faster

• Detect and mitigate insider-driven data loss in real-time
• Block risky sharing and apply encryption in SaaS tools like Google Drive and Microsoft 365
• Gain continuous visibility across multi-cloud and SaaS with a cloud-native architecture
• Automate least-privilege access control for unstructured and sensitive data
• Prioritize threats using context-aware insights from identity, behavior, and sensitivity
• Enhance DLP tools like MicrosoftPurview to extend coverage and control

How an Aerospace Firm Secured Proprietary Designs

An aerospace manufacturer used Sentra to discover, classify and remediate exposure risk to proprietary data such as; patents, algorithms, and CAD designs across Microsoft 365 and Google Workspace. Sentra quickly discovered duplicate blueprints in employee OneDrives and flagged overshared design files that could have leaked via collaboration. They also used Sentra to enforce their policy of masking all data stored on Snowflake by accurately identifying data as masked or unmasked. Finally, they created a ticketing workflow to automate and streamline remediation of urgent issues. The company cut exposed IP by over 80% in the first month. Deploying Sentra was simple and the scan quickly found exposed proprietary data, IP, and other critical data that if compromised or exfiltrated could cause catastrophic business, financial, or reputational damage.

One of the largest U.S. mortgage lenders manages over $350 billion in loans across a complex ecosystem of production and non-production cloud environments. They rely on data-intensive applications to support underwriting, processing, and customer management.

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Given the nature of their business, mortgage lenders and financial institutions are subject to stringent and multi-layered data protection and privacy regulations, such as; FTC Safeguards Rule, Gramm-Leach-Bliley Act (GLBA), Consumer Financial Protection Bureau (CFPB), SOX, FFIEC guidelines, and increasingly state-level privacy laws like the California Consumer Privacy Act (CCPA). Compliance requires rigorous control over non-production data environments where customer data often gets replicated for development and testing. Most relevant regulations either require or recommend data masking for sensitive customer data.

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The mortgage lender had a legacy DSPM solution that generated large volumes of false positives, and lacked the precision to support automated masking workflows needed to ensure compliance. This created significant manual overhead for the data security team. 

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The financial institution’s data security and compliance teams turned to Sentra and within weeks, they gained column-level visibility into regulated data, automated classification and masking of workflows, and uncovered hundreds of orphaned data stores that could be deleted to both significantly improve regulatory compliance, reduce storage costs and reduce manual workload for the security team.

The Challenge: Manual Masking and Limited Data Visibility

The mortgage lender uses a data masking tool to mask regulated data in non-production environments. Their previous DSPM solution lacked depth and breadth of classification and created too many false positives, leading to over-masking and a labor intensive manual verification process. This made it very difficult to spot what data needed to be masked. Like all financial institutions, the lender also has many sensitive data classifications unique to its business operations that had to be manually tagged. Together, all these classification limitations made it difficult to create data reports to feed to their data masking tool.

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For known and correctly classified sensitive data, their data masking tool was able to transform it into realistic synthetic records. Once the original required data masking was performed, there was no reliable way to confirm whether data remained masked after refreshes, especially since the masked data resembled real data so closely. The mortgage lender needed visibility into where PII/PCI and toxic data combinations lived across non-production environments and accurately classified sensitive data before and after being masked.

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“The challenge wasn't just masking data; it was the persistent uncertainty of whether that data stayed masked after system refreshes. We needed a reliable way to verify ongoing compliance at a granular level.”

— Chief Compliance Officer, Leading US Mortgage Lender

Why Sentra: Column-Level Precision, Workflow Automation, and Immediate ROI

After a thorough evaluation of leading DSPM vendors, the mortgage lender chose Sentra due  to several key capabilities. Its flexible classifier system, which supports both regex and contextual logic using AI-powered classifiers, made it easier to identify masked and unmasked data accurately. The platform’s policy engine offered automated scanning for missing or reverted markers, helping teams detect issues early. Sentra also seamlessly integrated into existing workflows without requiring invasive changes to systems or processes.

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Key Outcomes:

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• Fast AI-Driven Column-Level Classification: Sentra’s precise tagging engine classified sensitive data across their entire environment in just six weeks, outperforming other vendor tools by automatically identifying PII/PCI, financial data, and compliance-relevant data types.
  
• Improved Accuracy: With Sentra the compliance and data security teams are able to create a clear view of all the data that needs to be masked and feed this information into their data masking tool for future masking. Sentra can detect whether a dataset contains markers like "@example.com" emails or specially formatted SSNs.
  
• Automated Data Masking via Jira: Sentra integrated with their existing data masking tool to mask data and pushed alerts to Jira, enabling end-to-end remediation workflows with executive visibility.
  
• Granular Visibility: By using data classifications and logical negation (e.g., “does not contain marker”), the compliance team can isolate and track both compliant and non-compliant datasets.
  
• Policy-based Automation: Sentra’s automatic policies engine is set to run on a regular schedule, identifying data assets without expected markers, allowing the compliance and data security teams to take action before audits or incidents occur.
• Compliance Confidence
  Able to ensure compliance with multi-layered data protection and privacy regulations and internal security mandates for precise access and masking.
  

Implementation: From Manual Compliance Burden to Automated Remediation

The mortgage lender deployed Sentra in under six weeks, scanning thousands of data stores across AWS, Snowflake and other cloud and SaaS environments and applied accurate sensitivity labels. Sentra’s classification output determined user roles based on data sensitivity. The integration with Jira and their data masking tool enabled an automated masking workflow, flagging issues to executives and eliminating manual triage.

Following the initial deployment, the financial institution decided to build on this momentum and extend Sentra’s coverage to Google Workspace.

Real Business Impact: Data Visibility, Accurate Masking, and Compliance Confidence‍

With Sentra, the data security and compliance teams gained deep visibility into sensitive and regulated data across cloud environments and SaaS applications, transforming how they enforce compliance and scale a proactive, automated data protection strategy.

Mortgage Lender and Sentra: Turning Compliance into a Competitive Advantage

What started as a goal to streamline masking and compliance has become a long-term foundation for cloud data governance. The data security team replaced an underperforming legacy DSPM and gained deep visibility into sensitive and regulated data across cloud environments and SaaS applications, transforming how they enforce compliance and scale a proactive, automated data protection strategy. They also implemented a strategic, automated framework for protecting customer data across every environment and ensuring compliance.

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Together, the mortgage lender and Sentra have transformed how the financial institution security team supports excellence in development speed, data protection, and regulatory compliance.