AcquisitionProofpoint Expands Data Security with Normalyze Acquisition

Proofpoint Expands Data Security with Normalyze Acquisition

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Proofpoint is all set to acquire Normalyze to deepen its data security offerings in today’s complex cloud environments. This acquisition, expected to close in November, enhances Proofpoint’s human-centric platform by integrating Normalyze’s AI-powered tools for data discovery, classification, and risk management.

These capabilities address rising concerns around human-related risks in data handling across multi-cloud, SaaS, and hybrid environments—a challenge as cloud adoption surges.

Also Read: Sophos to Acquire Secureworks in $859M Deal to Expand XDR Offerings

In the data-driven era, securing sensitive information amid sprawling cloud environments is paramount. Proofpoint’s Normalyze acquisition allows it to broaden protections, focusing on human errors as significant risk factors.

Normalyze’s Data Security Posture Management (DSPM) tools promise enhanced visibility, pinpointing sensitive data while quantifying risks. This visibility is critical in cloud and SaaS systems, where traditional security models struggle.

Today, data is at risk because of human behavior. Modern applications are rapidly changing, driven by small teams of developers working independently on microservices and various data sources, leading to an explosion of data,” said Mayank Choudhary, EVP of Data Security at Proofpoint. “These modern applications are highly interconnected, making it hard for security teams to manage the heterogeneous and ever-growing sprawl of their data.”

Proofpoint’s human-centric approach now integrates Normalyze’s technology to strengthen its clients’ data security, he added.

Normalyze, was recently recognized as a Cool Vendor in the “2024 Gartner Cool Vendors™ in Data Security.” The recognition was likely for Normalyze’s innovative approach to securing data pipelines linked to Large Language Models (LLMs) like ChatGPT, Microsoft 365 CoPilot, and Amazon Bedrock, addressing the unique risks of AI-driven environments.

AI-Driven Data Classification at Scale

Normalyze’s tools leverage AI to streamline data discovery and classification, especially vital in environments where data sprawls across on-premises, cloud, and hybrid platforms. This “agentless” scanning technology ensures rapid detection without adding security overhead, offering real-time insights that support governance and regulatory compliance.

Ravi Ithal, CTO and co-founder of Normalyze, stressed on the need for streamlined data management tools. He said that Normalyze’s mission to secure critical data across vast environments aligns well with Proofpoint’s vision. “By joining forces with Proofpoint, we can empower organizations to further improve their data security posture, reducing the risk of data breaches caused by human errors and help them to prioritize data loss threats,” Ithal said.

Enhanced Risk Prioritization with AI-Powered Insights

One significant feature of Normalyze’s DSPM technology lies in its risk assessment capabilities. Using DataValuator™, it provides visibility into data vulnerabilities by assigning monetary values and showing access points that might lead to potential breaches. The tool enables security teams to prioritize risks by impact, improving operational efficiency by focusing resources on the most critical threats.

Such capabilities are crucial as companies increasingly adopt AI and generative tools, often bypassing stringent security controls for speed and innovation.

Addressing Cloud Complexity Through DSPM

Today’s security teams face unprecedented challenges due to the rise of cloud-native applications. Normalyze’s DSPM platform integrates seamlessly, facilitating collaboration between data and security teams—a necessity when addressing cloud-native apps and SaaS. With features like Data Risk Navigator and Data Access Graph, it identifies over-permissioned access and potential attack paths.

Proofpoint expects this acquisition to help customers address security gaps and manage risks associated with high-value, sensitive data that are often overlooked amid rapid innovation.

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