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Microsoft unveils method to detect sleeper agent backdoors

Researchers from Microsoft have unveiled a scanning method to identify poisoned models without knowing the trigger or intended outcome. Organisations integrating open-weight large language models (LLMs) face a specific supply chain vulnerability where distinct memory leaks and internal attention patterns expose hidden threats known as “sleeper agents”. These poisoned models contain backdoors that lie dormant […]

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Datadog: How AI code reviews slash incident risk

Integrating AI into code review workflows allows engineering leaders to detect systemic risks that often evade human detection at scale. For engineering leaders managing distributed systems, the trade-off between deployment speed and operational stability often defines the success of their platform. Datadog, a company responsible for the observability of complex infrastructures worldwide, operates under intense

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How the MCP spec update boosts security as infrastructure scales

The latest MCP spec update fortifies enterprise infrastructure with tighter security, moving AI agents from pilot to production. Marking its first year, the Anthropic-created open-source project released a revised spec this week aimed at the operational headaches keeping generative AI agents stuck in pilot mode. Backed by Amazon Web Services (AWS), Microsoft, and Google Cloud,

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Adversarial learning breakthrough enables real-time AI security

The ability to execute adversarial learning for real-time AI security offers a decisive advantage over static defence mechanisms. The emergence of AI-driven attacks – utilising reinforcement learning (RL) and Large Language Model (LLM) capabilities – has created a class of “vibe hacking” and adaptive threats that mutate faster than human teams can respond. This represents

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