The Anatomy of Multi-Agent Hijacking Attacks
As organizations deploy networks of cooperating AI agents, a new class of attacks emerges — one that exploits inter-agent trust relationships rather than individual model vulnerabilities. We analyze three real-world attack patterns observed in enterprise environments and outline defensive strategies using Sentinel's cross-agent monitoring capabilities.
Read Article →Memory Integrity in Persistent AI Systems: A Framework
Persistent memory is what gives AI agents continuity — but it is also their greatest vulnerability. This paper introduces Qelmarit Labs' memory integrity verification framework, detailing how cryptographic attestation and behavioral baselining can detect memory corruption before it propagates through decision chains.
Read Article →Why Financial Institutions Need AI-Native Security Now
AI-driven trading, risk assessment, and customer service agents are transforming finance — but legacy security tools cannot protect systems that make autonomous decisions. We examine the regulatory landscape, emerging compliance requirements, and how enterprise trust infrastructure enables safe AI adoption in mission-critical financial workflows.
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