Top 10 Sensitive Data Discovery Software [2024]

Based on product focus areas and user experiences shared in review platforms, here are the top 10 sensitive data discovery software that helps security teams locate sensitive data—such as personally identifiable information (PII), and payment card industry (PCI) data—stored across databases, applications, and user endpoints.

Market presence

Features

Software with:

• Data loss prevention (DLP): Monitor detect and block sensitive data in motion, at rest, and in use. For more: DLP software.
• DSPM: Provide visibility into where sensitive data is and who has access to it. For more: DSPM vendors.
• High number of data classifiers offer a broad scope for categorizing data based on its sensitivity.

All software support:

• AES-256 encryption is one of the most secure encryption methods. It is highly resistant to brute-force attacks and meets strict regulatory criteria such as GDPR, HIPAA, and PCI-DSS.
• SOC 1, SOC 2, FedRAMP, and ISO27001 compliance, ensuring a comprehensive approach to regulatory requirements.

Review insights come from our experience with these solutions as well as other users’ experiences shared in Reddit, Gartner , and G2.

Top 10 sensitive data discovery software reviewed

Automated data classification tools label information according to its category, level of sensitivity, and the likelihood of data loss. Data categorization informs companies about the value of their data, identifies potential threats to that data, and implements protections to deal with those threats.

To be considered as a sensitive data discovery software, a solution needs to:

• Monitor data repositories in real-time.
• Provide contextual search features related to file type, sensitivity, user type, location, and other metadata.
• Facilitate compliance with industry regulatory standards (GDPR, CCPA, HIPAA, PCI DSS, ISO).

Sentra 

Sentra is a data security posture management (DSPM) platform that supports data detection and response (DDR). Sentra’s DDR capabilities offer real-time monitoring and alerting to assist security teams in detecting and responding to potential threats while prioritizing issues that put sensitive data at risk. Sentra:

• Discovers and classifies unstructured data using machine learning.
• Separates employee and customer data.
• Identifies toxic combinations of sensitive data.
• Identifies Uncommon Personal Identifiers to comply with GDPR, HIPAA, PCI, and NIST. For more: Data compliance.
• Adheres PII Jurisdiction to distinguish or trace an individual’s identity

The platform supports petabyte-scale data operations and offers 20 pre-built or customizable integrations, along with 200+ data classifiers.

Sentra offers broad overage, allowing companies to gain visibility across their data stores and limit shadow data. See Sentra’s coverage:

• Azure/Microsoft 365: Azure, Microsoft 365, OneDrive, SharePoint, Office Online, Teams 
• AWS: Amazon AWS, S3, DynamoDB, MySQL Memcached, PostgreSQL, ElasticSearch, Open Search, Redis, SQL Server, Oracle EC2
• GCP: Google Cloud Storage, BigQuery, Cloud Bigtable, Cloud SQL, Cloud Spanner, Dataflow, Google Workspace
• Data Warehouse: Snowflake, Databricks, BigQuery, Amazon Redshift, MongoDB Atlas

With petabyte-scalae support and extensive coverage, Sentra is a useful solution for enterprises that handle large amounts of sensitive data in IaaS, and DBaaS environments.

Choose Sentra to secure and classify your cloud data.

Pros

• No manual connectors
• DLP integrations: Sentra effectively integrates with data loss prevention (DLP) tools to protect sensitive data on their endpoints.
• Customizations: Sentra’s DSPM can be effectively customized, for example, by implementing custom classifiers and policies.

Cons

• Data assets can be improved: Data assets are designed to indicate where the same data occurs in multiple contexts, however, users haven’t found it as user-friendly as some of the other tools, particularly Sentras data threats and discovery reports.
• Coverage could be expanded: The platform can expand beyond AWS/GCP/Azure and into SaaS applications.

Sprinto

Sprinto is a compliance automation tool that enables cloud-based enterprises to categorize data based on their sensitivity, importance, and criticality and create reports for SOC2, ISO 27001, HIPAA, and GDPR compliance. It offers cloud, SaaS, and web-based deployments.

Based on the overall impact level, companies using Sprinto can assign a classification label to their data:

• High: Restricted
• Moderate: Confidential
• Low: Public

Pros

• Data discovery for compliance: Users mentioned that Sprinto was effective for discovering and classifying data for ISO 27001, GDPR prep, and SOC 2
• Ease of use: Smooth implementation process for admins and other members.

Cons

• Misalignment with auditor requirements: Sprinto lacks alignment between its pre-built controls and the requirements of auditors, which can create confusion and frustration. 
• Manual support limitations: Clients struggle to navigate the solution during the audit process.
• No penetration testing: Several users pointed out that Sprinto does not include penetration testing within its SOC 2 package

Egnyte

Egnyte is a cloud-based file-sharing system that enables small and large enterprises to communicate remotely and provide secure access to confidential data. Its features include data authentication, offline access, file locking, and audit reports.

The solution includes a content intelligence engine that allows users to categorize data as risky, regulated, or proprietary, and scan files for unusual user behavior or ransomware threats.

Egnyte synchronizes file changes in real time and keeps the most recent versions in line with industry data regulations. It also enables users to save cache files to local devices.

Pros

• Collaboration capabilities: Strong tool for team collaboration and file sharing across Google Workspace and Microsoft 365.
• Data security capabilities: The tool provides security measures (e.g., encryption, role-based access) and complies with important regulations like GDPR and HIPAA.

Cons

• Mobile app limitations: The mobile version doesn’t offer the same robustness or features as the desktop version.
• Complexity in integrations: Some users find the integration process (e.g., with Google Workspace or Salesforce).

Druva Data Security Cloud

Druva Data Security Cloud provides predefined data types and the ability to generate custom sensitive data to meet your organization’s intellectual property information. 

For example, you can construct sensitive data for Intellectual Property (IP) information. This can comprise research data (such as personally identifiable or confidential data), patent information, data about third-party agents and partners, system access passwords, etc.

Pros

• Finding data: Finding the data is practical with date-specific backups and easy to drill down into file trees.
• Backup functionality: Backups and restores of M365, Entra, and Salesforce are reliable, and the platform ensures that data integrity is maintained. 

Cons

• Complex features: Some features (like NAS proxy or Azure proxy) require technical knowledge, 
• File restore navigation: The interface for restoring files at a granular level could be improved to make navigation more intuitive.

Thales 

Thales – CipherTrust Data Security Platform is a suite of data-centric security products and solutions that combine data discovery and classification, protection (encryption, tokenization, and key management), and control (access and policy administration) in a single platform for use on-premises or in the cloud.

Thales – CipherTrust Data Discovery and Classification interfaces with data repositories via agents. The agents can be installed either locally or remotely in the data stores. The agents connect to data sources via native protocols such as NFS for Unix Share, SMB for Windows Share, and HDFS for Hadoop.

Pros

• Sensitive data discovery & classification: The tool effectively discovers PII data, helping users locate data sources, and gaining visibility into data formats.
• Integrations (JAVA, APK signing): Strong integration capabilities for Java and a secure APK signing process for application security.
• Security features: Effective HSM (Hardware Security Module) and encryption services for added security

Cons

• Complexity: The platform feels bulky and potentially difficult to operate.
• Integration challenges: Integration guides are sometimes described as poorly written
• Scalability issues: There are concerns regarding scalability in some environments, particularly about how the platform handles larger data sets.

Varonis 

Varonis provides a hierarchical picture of locations with the most sensitive and overexposed files. The tool offers classification results from petabytes of unstructured data.

Key features:

• Data classifiers: 400+ classification policies to cover compliance needs.
• Granular record counts: Report on the number of sensitive records rather than the number of files.
• Secrets discovery: Discover incorrectly stored and overexposed secrets (e.g., API keys, database credentials, encryption certificates, etc.) in your data repositories, and use the Automation Engine and Data Transport Engine to automatically remediate access. 

Integrations: Salesforce, GitHub, Zoom, Active Directory, Azure AD, Nasuni, NetApp, IBM QRadar, Panzura, NETGEAR, Splung, CorteXSOAR, CyberArk.

Deployment: Cloud, on-premise Windows,  on-premise Linux, Red Hat Enterprise Linux, Oracle Solaris.

Pros

• Data discovery and monitoring: Varonis provides actionable insights, notifying users of issues like data policy violations or unauthorized access, which enables quicker remediation.
• Reporting and logging: The platform provides detailed logs and comprehensive reports.
• Real-Time Alerts: Varonis’ alerting tools are effective for managing unstructured and structured data. 

Cons

• SaaS version reporting: Some users have noted that the SaaS version has limitations in reporting.
• Resource intensive: Running Varonis effectively can require a high-performance infrastructure. Some users have reported that it demands multiple high-horsepower virtual machines or additional servers to ensure fast scanning.
• Complex initial setup: The initial setup of Varonis can be challenging.

OneTrust 

OneTrust Privacy & Data Governance Cloud enables businesses to  monitor their data and security posture, enabling them to gain visibility in their:

• unstructured file shares
• structured databases 
• big data storage
• SaaS applications
• cloud apps

The product also offers Optical character recognition (OCR) to scan structured data across PDFs and ZIP files.

Pros

• Comprehensive privacy tools for compliance: Data mapping, cookie compliance, vendor management, and privacy assessments effectively help businesses ensure compliance with regulations like GDPR, and CCPA.
• Useful templates: OneTrust provides extensive pre-built templates and out-of-the-box reports for documentation like Records of Processing Activities (RoPA) and Data Protection Impact Assessments (DPIAs).
• Automated data mapping: The data mapping tool is particularly praised for its ability to automate the process of creating and maintaining a data map.

Cons

• Complex and expensive for small businesses: The solutions are seen as resource-intensive and expensive.
• Reporting and access management: The reporting features are seen as basic, they have access management Limitations.
• Lack of bulk deletion support: Some users have pointed out the lack of bulk deletion templates, which can make it more cumbersome to delete records or personal data in large quantities.

ManageEngine DataSecurity Plus

ManageEngine DataSecurity Plus is a comprehensive data visibility and data discovery tool that focuses on file auditing, analysis, risk assessment, leak prevention, and cloud protection.

With ManageEngine DataSecurity Plus users can execute several data management practices:

• Automate data discovery, Use multiple filters, including violated policy, risk score, and frequency of data occurrence to discover and classify files and folders containing sensitive information.
• Personalize classification labels: Create parent and sub-classification labels that best suit your organization (e.g., North division of Finance department, and catalog files based on these labels).
• Use manual data classification: Manually classify files containing valuable information into predefined labels, i.e., public, private, confidential, or restricted.`

Pros

• Comprehensive reporting for compliance: The tool is equipped with features to help with compliance reporting for various regulations such as SOX, HIPAA, GDPR, PCI, and FISMA. 
• Strong visibility into data usage: Provides detailed visibility into file accesses, changes, and sharing, 
• Data security: Includes specific protections against ransomware by identifying and responding to malicious activities in real-time.

Cons

• High pricing: Reviewers say that the licensing costs are too high.
• Lack of automation features: Users have requested more automation in tasks, especially when handling alerts and risk assessments. 
• Limited support for binary files: The tool can only track binary file content for certain types of files.

Imperva 

Imperva Data Security Fabric (DSF) examines data store contents for tag matches using pattern matching and predefined name-based or content-based data discovery and classification.

Its predefined policies enable compliance with rules such as GDPR and CCPA. With Imperva Data Security Fabric (DSF) you can add custom, customer-specific data classification categories. Imperva DSF utilizes its data classification capabilities in a variety of workflows:

• Protecting sensitive information in alerts: For example, credit card numbers are masked in alert tables to prevent unauthorized administrative users from seeing the data.
• Preventing data leaks in database responses: Identify sensitive data in SQL answers and either block them or provide an alert.
• Auditing the extraction of sensitive data.

The tool supports commonly used file repositories including:

• Microsoft Sharepoint 
• Microsoft file servers 
• CIFS network fileshares 
• Office 365 Onedrive 
• AWS S3 buckers 
• Azure Blobs 
• Google Workspace drives • 
• Unix Mail archives

Pros

• Low false positives: The tool ensures that security teams are alerted to actual threats.
• Database activity monitoring (DAM): One of the most praised features is its database activity monitoring (DAM) capabilities, which allow for comprehensive tracking of database transactions.

Cons

• High pricing: Imperva Data Security Fabric is noted as being expensive.
• Complexity for beginners: Some users report that creating access rules and configuring the system can be challenging for beginners.
• Lack of pre-defined policies: A common suggestion is the addition of pre-defined policies.

Satori Data Security Platform

Satori Data Security Platform identifies information depending on its type, level of sensitivity, and likely effect of data loss. Satori Data Security Platform can classify your data into three categories:

• High-sensitivity data: Records of financial transactions, intellectual property, and authentication data, etc.
• Medium sensitivity data: Emails and papers that do not include sensitive information, etc.
• Low sensitivity data: Content of publicly accessible websites, etc.

Satori Data Security Platform aids a company in meeting the following industry-specific compliance requirements:

• EU General Data Protection Regulation
• HIPAA
• PCI DSS
• ISO 27001
• NIST SP 800-53

Pros

• Strong data masking: Out-of-the-box masking and unmasking capabilities help organizations manage data access without requiring additional configurations. It’s customizable to fit specific needs.
• Support for GraphQL: GraphQL support is highly appreciated, providing flexibility and enabling more dynamic queries.
• Strong communication throughout setup: Customers appreciate the strong communication from the vendor throughout the setup process

Cons

• Lack of REST API Support for dynamic masking
• MongoDB dynamic masking: MongoDB dynamic masking is missing.
• Expensive exporting of audit logs: Exporting audit logs can be an expensive operation within Satori, particularly when trying to filter logs at the service level.

What is sensitive data discovery classification?

Forrester defines data discovery and categorization as “the ability to provide visibility into where sensitive data is located, identify what sensitive data is and why it’s considered sensitive, and tag or label data based on its level of sensitivity.

Sensitive data discovery and classification is useful because it indicates what needs to be protected and make it easier to implement data security policies.

This data visibility allows organizations to optimize data use and handling policies, and establish security, privacy, and data governance measures. 

The function of data discovery and classification in security

The importance of data discovery and classification relates to security posture and regulatory compliance.

The new security trend known as DSPM seeks to answer a few concerns regarding your data and its security, including the following:

• Where is my sensitive data stored?
• What sensitive information is at risk?
• What can be done to limit or eliminate that risk?

Your DSPM strategy includes sensitive data discovery and classification, as shown in the diagram below:

Read more: DSPM vendors.

Benefits of sensitive data discovery software

Improved compliance

Any health or financial data, as well as personal consumer data, that may be covered by such legislation, can be promptly segmented and stored in a secure location.

Companies that fail to comply face increasing fines. The EU’s GDPR allows the EU’s Data Protection Authorities to impose fines of up to €20M or 4% of annual global turnover.

The California Attorney-General began implementing the California Consumer Privacy Act (CCPA) and is now empowered to seek a civil penalty against anyone who fails to comply with the CCPA.

Reduced the likelihood of data breaches

Data discovery software can also help you protect data and reduce its footprint. Real-time monitoring enables you to better protect your client’s data by incorporating each new dataset and point of capture into your system, classifying it, and routing it to the appropriate protected region.

Enhanced threat detection and prevention

• Insider Threats: Sensitive data discovery tools help detect potential insider threats by monitoring and analyzing the access to and movement of sensitive data within the organization.
• Preventing data leakage: By knowing where sensitive data resides, organizations can prevent unauthorized data leakage, whether intentional or accidental, by enforcing data loss prevention (DLP) controls.

Further reading

External Links