Announcing Customer Success, New Platform Capabilities to Enable Safe Use of LLMs and Data Lakes + RSA Highlights. Read Both Announcements.

FEATURED

Gartner® Innovation Insight: Data Security Posture Management
PLATFORM
The Normalyze Platform
Supported Environments
Platform Benefits
USE CASES

Reduce data access risks

Enforce data governance
Eliminate abandoned data

Secure PaaS data

Enable use of AI

DSPM for Snowflake

MARKETS

Healthcare
Retail
Technology
Media
M&A

FEATURED

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Improve Cloud Security:
Dark Reading Interviews Ravi Ithal

FEATURED

CYBER 60: The fastest-growing startups in cybersecurity

Use cases

Find out how Normalyze helps security and data teams solve some of their biggest challenges.

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Discover & Analyze

Reduce data access risks

Govern data access and enforce least privilege

One of the most pervasive challenges security and data teams face is around user access. Without accurately classifying of all of the data they possess, organizations often find themselves in a quandary: balancing the need for access with the imperative of security. When data remains unclassified or is misclassified, it becomes nearly impossible to apply precise access controls. As a result, organizations are forced into a binary choice — either restrict data access to the point of hindering operational efficiency or grant overly broad access, which exponentially increases the risk of data breaches.

With automated discovery and classification of all sensitive data using the Normalyze One-Pass Scanner, including custom data classes and hundreds of other data classes.

With Data Risk Navigator and Data Access Graphs, teams can then review and audit data being accessed at a granular level, map role-based access and privileges, eliminate over-privileged users and adopt the least privilege model, restricting access to the minimum level required.

 

Read more about data access governance

Eliminate abandoned data

Find stale, duplicate or unknown data sources and minimize attack surface

As digital environments continue to expand, the complexity of effectively managing data increases, especially ensuring that all data assets are actively utilized and properly secured. Often, abandoned data is caused by “shadow data” practices or data migration projects.

Normalyze’s insights reveal that over 70% of these data stores have been neglected for over a year, and alarmingly, 15% have lingered unattended for three years or more. The implications are twofold: not only do these abandoned data stores lead to escalating storage costs, they also present a severe risk profile, as unmonitored and outdated data can easily become a target for cyber threats. Abandoned data stores should ideally be eliminated or at minimum, offloaded to an archive. 

Normalyze provides advanced tools specifically designed for identifying and managing abandoned or stale data stores, including backups and snapshots. Our latest update provides detailed insights into the space utilized in  backups and the storage tiers used to store them. Since storage costs are proportional to the used size, IT teams can prioritize remediation for the abandoned backups with higher usage. Teams can also get insights on the storage tier—standard or archive — where the backup is stored.

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Enable use of AI

Leverage DSPM to use Gen AI and Large Language Models confidently

Generative AI and Large Language Models (LLMs) are helping enterprises boost productivity, gain competitive advantages and accelerate innovation. These advanced technologies enable the rapid analysis and generation of content, streamlining decision-making and automating tasks. They are also introducing significant data security challenges: without proper data classification, there’s a real risk that these systems might unintentionally process and expose sensitive or valuable information. The challenge is compounded by the proliferation of ‘shadow AI’— technologies deployed directly by business teams without IT oversight. Such deployments can lead to inconsistent security practices and create vulnerabilities, as sensitive data might be used or accessed in ways that do not align with corporate data governance policies.

Normalyze DSPM for AI offers capabilities to scan, identify and classify sensitive data being used in Large Language Models (LLMs) like Microsoft Copilot or ChatGPT, ensuring that AI-generated content does not expose valuable or sensitive information. In addition, Normalyze also helps secure cloud-based AI deployments in AWS Bedrock and Azure OpenAI by detecting any sensitive data being fed into the foundational or custom models.

Normalyze also offers specialized APIs for LLM security which can be used to conduct real-time sensitivity analysis of data going into and out of LLMs, while providing full governance and visibility into data usage. These APIs can be easily integrated into existing customer workflows, helping keep data processing costs down and increasing security for services like Microsoft Copilot.

 

Read more about DSPM for AI

Enforce data governance

Continuous compliance with industry regulations and Zero Trust model

With data breaches costing companies an average of $4.24 million per incident* and regulatory fines reaching into the billions, organizations must prioritize data security regulations to safeguard their assets and avoid severe financial and reputational damage.

The cost of failure to comply with regulations is high (and very public): a multi-national hospitality company  was fined $123 million by the UK’s Information Commissioner's Office under GDPR regulations, a financial institution paid an $80 million fine for failing to establish effective risk assessment processes, and a large tech company was fined in excess of $100 million due to failures in their third-party vendor management and data privacy controls.

Normalyze streamlines the regulatory compliance process by continuously monitoring and assessing an organization's data security posture against over 500 compliance benchmarks, including NIST 800-171, GDPR, HIPAA, and SOC2. Through automated risk scans, Normalyze identifies compliance gaps and tags violations with specific regulatory frameworks and controls, ensuring teams understand the compliance impacts immediately.

Normalyze supports comprehensive remediation by automatically initiating corrective actions through notifications or tickets in tools like JIRA, complemented by AI-generated instructions for efficient resolution. Additionally, Normalyze's compliance reporting features allow organizations to view and report their compliance status across their entire infrastructure, offering detailed views by account, resource, and compliance framework. This enables teams to proactively address vulnerabilities and maintain continuous compliance, effectively preparing them for audits and ensuring ongoing data security.

* Source: IBM Security "Cost of a Data Breach Report 2021

 

Read more about regulatory compliance and
specific regulations Nomalyze can help address.
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Secure Platform as a Service data

Empower the business with the right data and access in PaaS environments

PaaS solutions, designed to simplify data management and enhance analytical capabilities, often lead to increased data movement, duplication and complex access structures. Security and data teams often lose control over who accesses what data, raising the risk of data breaches and compliance issues.

Normalyze not only simplifies the management of PaaS security but also empowers organizations to maintain stringent data protection standards effortlessly, ensuring that their PaaS environments are both powerful and secure.

The patented One-Pass Scanner automates the discovery and cataloging of data across PaaS infrastructures, enabling security teams to track and classify data down to fine details like databases, schemas, and even individual columns. The platform provides a clear, real-time view of data access across the PaaS environment, showing exactly which users have access to sensitive data and through which roles. This allows security teams to right-size privileges and reduce the risk of overprivileged access. Using tools like QueryBuilder, teams can easily adjust access controls, even if they are not experts in query language..

The platform utilizes a library of pre-built risk signatures to monitor and analyze query-level activities continuously, quickly identifying potential security threats such as data exfiltration or insider risks. Real-time alerts for sensitive activities can be customized to notify teams via popular platforms like email, Slack, Teams, or integrated ticketing systems such as JIRA and ServiceNow, ensuring that any irregular activity is addressed promptly.

 

Read more about Securing Platform as a Service (PaaS)

Control Snowflake access

Classify data accurately at scale then unleash the power of Snowflake

The flexibility of PaaS environments like Snowflake has resulted in greater movement of data, more copies of data, and more users accessing data. While this flexibility is great for data analysts, it causes security teams to more easily get visibility into and control of the sensitive data in these environments.

Using Normalyze’s native integration with the Snowflake Data Cloud, customers can now seamlessly secure their data using Snowflake Horizon’s security and compliance capabilities in leveraging the Normalyze patented Data Security Posture Management (DSPM) platform for data discovery, classification, access governance, risk management, and compliance.

Leverage Data Access Graphs to view the top risks against your Snowflake data, filterable by tags and sortable by impact and likelihood. Click the risk to find each instance of that risk and detailed remediation instructions.
Normalyze is integrated with Snowflake Horizon and the Normalyze DSPM Connector is available on the Snowflake Marketplace.

 

Read more about DSPM for Snowflake
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What creates data security challenges?

Abandoned data

Misclassified
Data

Overprivileged Access

False Results During Audits

Unenforceable Data Policies

Shadow Data

AI-Generated
Content

Complex Data Environments

Data Velocity 
and Volume

Regulatory Changes