What’s new for Normalyze customers
Get the most current releases, features and capabilities in the Normalyze platform.
Enhanced Risk Detection and Remediation
New risk features enable teams to identify and remediate risks associated with user accounts.
- Eliminate Risky Links in SaaS Apps: Take control of your shared data with the ability to remove public access links, organization-wide shares, and domain-wide access for Google Workspace and Microsoft 365 right in the user interface. This helps prevent unauthorized access to sensitive data, ensuring that only intended recipients can view or collaborate on your documents.
- Expanded SaaS User Risk Identification: Normalyze alerts on Google Cloud Platform (GCP) and Microsoft 365 user risks, such as users with access to sensitive data who don’t have MFA enabled.
- Auto-Discovery of New GCP Project: Automated detection of newly created GCP projects ensures no new project flies under the radar, helping you maintain continuous security coverage and avoid unmonitored assets that could become potential vulnerabilities.
- Snowflake User Access Risks: 17 Snowflake-specific risk signatures empower enforcement of stronger authentication practices and ensure under-protected users do not go unnoticed when they have access to sensitive data across your org. Examples include flagging non-admin users with drop table or truncate table privileges, accounts with more than 10 admin users, users who have been inactive more than 90 days, and more.
- OCR for images in PDFs: With improved accuracy and support for images in various formats such as PDFs, DSPM for Optical Character Recognition (OCR) further strengthens the security of our customers’ sensitive PDF files.
- Zero-Friction Azure DB Scanning: New support for passwordless scanning for Azure PostgreSQL, snapshot-based scanning for Azure Datastores, and the ability to scan private Azure data stores, offering seamless and efficient risk detection.
Hybrid LLM-Based Data Classification
The Normalyze hybrid approach to data classification, combining large language models (LLMs) with traditional methods like regular expressions and NLP models, represents a significant leap in accuracy and efficiency. While regular expressions and NLP have been effective for identifying patterns and structures, LLMs provide a deeper understanding of unstructured data by analyzing context, language patterns, and semantics.
Normalyze uses regular expressions and NLP for an initial pass to reduce data volume, and then applies LLMs for deeper contextual analysis. This powerful combination boosts classification accuracy, reduces false positives, and enhances the detection of sensitive information in complex environments. Together, these methods deliver a more intelligent and effective classification system, strengthening data protection strategies.
DSPM for AI: Sensitive Data Import Detection
Normalyze has enhanced the detection of sensitive data imports into machine learning models across Azure ML, Google Vertex, and AWS Bedrock, as well as within Retrieval-Augmented Generation (RAG) workflows. These updates build on previous capabilities, which focused on identifying data accessed by custom models, by now detecting and flagging instances where sensitive data has been imported or trained directly within machine learning models on Azure ML, Google Vertex, and AWS Bedrock.
Additionally, we’ve expanded capabilities to include detection of sensitive and valuable data in RAG workflows, ensuring even the most advanced AI techniques are monitored for privacy risks. These features empower organizations to strengthen their data protection, maintain regulatory compliance, and safeguard against unauthorized exposure of sensitive information across their AI and ML environments.
Data Detection and Response (DDR)
We’ve expanded our Data Detection and Response (DDR) capabilities to AWS, Azure and GCP, enhancing protection for authentication, resource access, and compliance across these platforms. This expansion not only increases visibility and accelerates threat detection but also enhances protection of critical assets.
With real-time monitoring and advanced threat detection, DDR capabilities now offer extensive coverage in cloud security and operational efficiency, enabling organizations to proactively manage risks such as unauthorized access, misconfigurations, and privilege escalations across both Azure and GCP environments. The integration of these capabilities speeds up threat responses and provides continuous monitoring and unified visibility across multi-cloud environments, simplifying security operations and helping prevent security incidents before they escalate.
Key benefits to customers include real-time risk detection, faster threat response, and a unified view of security risks across multiple cloud environments.
Microsoft Information Protection (MIP) Label Integration
Support for Microsoft Information Protection (MIP) sensitivity labels enables seamless management and protection of sensitive and valuable data within Microsoft environments. By mapping MIP labels to specific critical data entities within Normalyze, organizations can automatically identify and fix gaps in label application. This helps ensure critical data is consistently labeled, minimizing risks and enhancing governance.
With this integration, customers can:
- Govern and control access to critical data, preventing unauthorized access.
- Prevent accidental leakage by Microsoft Copilot.
- Ensure data is encrypted according to security policies.
- Streamlining compliance with GDPR, HIPAA, and other regulations.
- Mitigating operational risks caused by misconfigurations or human error.
Expanded Coverage: Salesforce Support
Normalyze support for Salesforce allows organizations to secure sensitive data, manage user access, and monitor share states.
Key capabilities include:
- File and Attachment Classification: Automatically scan, classify, and identify sensitive data across Salesforce files and attachments.
- User Access Insights: Track who has access to specific files, ensuring visibility into potential risks.
- Permission Management: See who has access to sensitive files to better manage access.
- Sharing State Identification: Monitor whether files are shared publicly or privately, with metadata for informed security decisions.
Compliance: Support for CMMC and NIST CSFv2
CMMC Compliance Support: Normalyze supports organizations in highly regulated sectors like healthcare, government contracting, and financial services to adhere to the US Department of Defense (DoD) Cybersecurity Maturity Model Certification (CMMC) Program requirements to protect federal contract information (FCI) and controlled unclassified information (CUI). Capabilities include:
- Sensitive Data Protection: Identifies and safeguards FCI and CUI, aligning with CMMC standards.
- Access Controls: Enforces strict access policies, ensuring only authorized personnel can access sensitive data.
- Compliance Auditing: Detailed audit trails and reports streamline certification and ensure continuous adherence to CMMC.
NIST CSF v2.0 Compliance Support: Normalyze has expanded support for NIST CSF v2.0 with updated mappings to controls and the ability to track and report compliance issues in real time via the dashboard, enabling faster identification and remediation of compliance gaps
More New Features
Visit the new features history archive.