Tag: turbulence

In the year 2025, trust emerged as the most vulnerable aspect of modern computing. While cyber security has historically focused on weaknesses, software flaws, misconfigurations, and inadequate network defenses, recent cyber incidents signaled a significant shift. Attackers no longer relied solely on conventional methods. This transformation was evident in numerous major breaches: breaches in the supply chain exploiting trusted platforms, misuse of legitimate remote access tools and cloud services, and AI-generated content evading traditional detection methods. This highlighted that even well-protected systems could be compromised if trust was equated with safety. It is crucial for cyber security experts to learn from the events of 2025 to comprehend the evolving threat landscape and adjust their strategies accordingly. The perimeter is irrelevant – trust is the threat vector Organizations realized that attackers could exploit assumptions as effectively as vulnerabilities by leveraging overlooked trust signals. They seamlessly integrated into environments using standard tools, cloud services, and signed binaries, bypassing telemetry and behavioral controls. The rapid integration of AI into business processes played a role in this shift. AI systems began making decisions that were previously human-driven, introducing a new risk factor: automated processes inheriting trust without validation. This led to incidents where attacks were subtle and embedded within legitimate activities, prompting defenders to reassess the significance of signals, missing telemetry, and sensitive behaviors originating from trusted sources. Identity and autonomy took center stage Identity has become a critical attack surface alongside security vulnerabilities. With the rise of autonomous operations, attackers increasingly target identity systems and trust relationships between components. Once an attacker gains control of a trusted identity, they can move with minimal resistance, expanding the concept of privilege escalation. Defenders recognized the need to default to distrust not only in network traffic but also in workflows, automation, and decisions made by autonomous systems. AI as both a power tool and a pressure point AI served as both an asset and a risk in cyber security. While AI-powered tools accelerated development, they also introduced logic flaws due to incomplete instructions. AI-driven attacks became more sophisticated, making detection of phishing and fraud campaigns challenging. The key lesson was that AI amplifies existing controls, emphasizing the need for comprehensive security measures across the AI ecosystem. A shift towards governing autonomy As organizations rely more on AI agents and automation, security efforts will shift from patching vulnerabilities to controlling decision-making processes. Key defensive strategies will include enhancing AI control-plane security, data drift protection, trust verification, zero-trust compliance, behavioral baselines for AI, secure-by-design identity, and intent-based detection. The focus will be on rebuilding trust in a more secure and intentional manner in the future of cyber security. Aditya K Sood is vice president of security engineering and AI strategy at Aryaka.

Tag: turbulence

From trust to turbulence: Cyber’s road ahead in 2026

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