When Data Becomes the Attack Surface: Positive Technologies Releases PT Data Security 1.0

Relevance Amid Rising Threat Levels

Key changes in version 1.0 include optimization of the data classification mechanism. Adjustments to the machine learning model logic significantly reduce inventory time, even in large-scale infrastructures. A new statistics module has also been introduced, enabling real-time assessment of data distribution, incidents, and risk levels for each data class.

The updated web interface allows users to manage tasks such as inventory, classification, and risk analysis from a single control plane. Security teams can track task execution progress and diagnose emerging issues. In addition, the product has been added to Russia’s national software registry, simplifying its adoption in the corporate sector and government organizations.

These changes are particularly important because PT Data Security automates core data governance processes, helping organizations quickly understand what data they have, where it is stored, and what risks it faces. This is especially relevant against the backdrop of increasing data leak threats, stricter personal data protection requirements, and expanding regulatory and cybersecurity policy enforcement at both enterprise and government levels.

Optimization and Export Potential

The export potential of Russian DSP solutions such as PT Data Security opens opportunities for entry into CIS markets and developing regions, where demand for locally controlled software and independence from foreign vendors is growing. However, due to sanctions against Positive Technologies, access to EU and U.S. markets remains limited.

From a technology perspective, the DSP segment is seeing increased integration of machine learning and artificial intelligence into data classification and inspection workflows. Further expansion is expected in automated incident response and deeper integration with SIEM and SOAR systems.

PT Data Security 1.0 is the result of close collaboration with our first customers. Based on pilot project outcomes, the development team implemented the most in-demand user scenarios in just one quarter. We optimized a number of architectural mechanisms, improved performance across key processes, and updated the interface. We will continue refining the product to make it as practical and effective as possible for daily security operations, carefully addressing the needs of organizations that own and manage data

Viktor Ryzhkov

Head of Data Protection Business Development at Positive Technologies

Additional emphasis is being placed on optimization for cloud-based and distributed environments, taking into account hybrid architectures. Within Russia, DSP platforms are becoming critical components of enterprise information security strategies, particularly in the financial sector for protecting personal and transactional data, in government for safeguarding critical information, and in industry as part of broader digital transformation initiatives.

Data Classification and Control

In summer 2025, the beta version of PT Data Security, whose MVP was first introduced by Positive Technologies in 2024, became available for pilot projects. Key features included an AI-driven module for precise data classification, flexible classification logic, and identification of business applications.

The evolution of machine learning approaches in PT Data Security marked a shift from rule-based regular expressions to ML algorithms to improve classification quality. The beta version introduced an AI module using machine learning techniques for more accurate data detection and categorization.

The DSP concept itself was introduced by Gartner in 2021. Today, DSP platforms are becoming a foundational layer of enterprise security for managing and controlling data in large organizations. They consolidate key information protection functions, including monitoring, access control, and automated data leak prevention. Globally, major vendors now offer DSP solutions as part of broader enterprise security stacks, including platforms such as Microsoft Purview and IBM Guardium.

Regulatory trends around data classification and control point toward stricter requirements for protecting personal and sensitive corporate data across many jurisdictions, including compliance frameworks such as ISO/IEC 27001/27002 and regulations analogous to GDPR.

Technological and Commercial Outlook

PT Data Security 1.0 represents an important step for the Russian DSP market, delivering automated, machine-learning–accelerated data classification that is critical to modern information security strategies. Growing interest in DSP solutions reflects broader trends driven by data volume growth, expanding threat landscapes, and increased regulatory pressure on organizations.

PT Data Security is positioned to strengthen its role in the domestic market and across CIS countries, as well as to support programs focused on import substitution and digital sovereignty. Forecasts through 2028 suggest expanded DSP functionality through integration with EDR/XDR and SIEM/SOAR systems, alongside advances in data behavior analytics and automated response capabilities.