Supply chain security lessons for AI integrations
The Miasma attack on Red Hat's npm packages highlights supply chain risks and credential theft, which are critical for AI integration security.
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AI security platform: protecting AI services from prompt injection and data leaks
Protecting AI services from prompt injection and data leaks in 2026 requires a comprehensive approach and integration with existing cybersecurity tools.
DLP for AI Systems: The New Cybersecurity Reality of 2026
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.
DLP strategies for corporate content protection in distributed work
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.
AI-powered offboarding: defending against insider threats in 2026
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.
Electronic Document Management 2026: AI-assistants and archiving automation
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
Zero Trust architecture and corporate network protection
Traditional network perimeter security approaches are no longer sufficient for modern cyber threats. Zero Trust architecture offers a radically new approach focused on continuous verification and access minimization, regardless of user or device location.