Zero Trust for legacy systems: protection architecture via IAP and microsegmentation
How to protect legacy infrastructure from unauthorized access and lateral movement without major code refactoring using Identity-Aware Proxy and microsegmentation.
INSIGHTS & PRACTICE
Practical guides to data, integrations, enterprise platforms and applied AI.
14 publications
How to protect legacy infrastructure from unauthorized access and lateral movement without major code refactoring using Identity-Aware Proxy and microsegmentation.
How to secure legacy ERP systems without rewriting code. Implement Zero Trust using IAP, PAM, and microsegmentation to mitigate access risks effectively.
Building real enterprise cyber resilience in the NIS2 era, avoiding paper audit traps, and protecting infrastructure through Security by Design.
The Miasma attack on Red Hat's npm packages highlights supply chain risks and credential theft, which are critical for AI integration security.
Protecting AI services from prompt injection and data leaks in 2026 requires a comprehensive approach and integration with existing cybersecurity tools.
By 2026, over 70% of new AI systems will experience data breaches due to inadequate Data Loss Prevention (DLP) integration, necessitating a reevaluation of sensitive information protection in the age of artificial intelligence.
The rise of hybrid and remote work models significantly complicates the task of protecting corporate content. By 2026, effective DLP strategies must adapt to these changes, focusing on preventative measures and automation.
Approximately 60% of corporate data breaches in 2025 were recorded after an employee's termination, while their access formally remained active. Insider threats continue to be one of the most complex cybersecurity challenges.
Traditional approaches to ERP system security are outdated and struggle to cope with modern threats. The Zero Trust concept offers a radical shift, requiring continuous verification of every user and device, regardless of their location.
Companies face daily challenges in processing large volumes of data, automating routine processes, and making decisions. AI agents are becoming a key tool for addressing these tasks, providing a new level of efficiency and adaptability.
The challenge of disparate data and the absence of a single source of truth for key entities is critical to business efficiency. System integration and MDM are key to resolving this.
The integration of artificial intelligence into electronic document management systems, particularly Megapolis.DocNet, opens new opportunities for automating routine tasks, enhancing efficiency, and improving information security. This enables a reevaluation of approaches to archiving and corporate