Legacy Systems

Legacy systems are older software, databases, and infrastructure that organizations still rely on to run core operations, often built before modern AI tools and data practices existed. In AI governance, they matter because AI systems frequently need to pull data from or connect to these older platforms, which can expose gaps in documentation, access controls, data quality, and auditability. Compliance teams should treat legacy environments as a common source of hidden risk when assessing whether an AI deployment can be explained, monitored, and kept within regulatory requirements.

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ResearchGlobal2026-11-09

Google DeepMind AI Agents Cut RSA-1024 Attack Cost 3.5x, Forcing Cryptographic Inventory Action

Google DeepMind, with researchers from UC San Diego and Inria, used AI agents to reduce the computing cost of attacking legacy 1024-bit RSA encryption by 3.5 times. The agents completed the work in under four days with minimal human oversight. Modern key lengths of 2048 bits or larger are unaffected, but organizations still using legacy RSA-1024 in any system face elevated risk.

Google DeepMind cryptographic risk RSA AI agents AI safety research key management legacy systems