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Microsoft Introduces MDASH for Large-Scale AI Vulnerability Research

Microsoft has introduced a new AI-driven vulnerability discovery system called MDASH, a multi-model agentic security platform designed to automate large-scale code auditing across Windows and other Microsoft software environments. The system combines more than 100 specialized AI agents that work together to scan, validate, debate, and prove vulnerabilities across complex codebases.

By Robert Krzaczyński
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Google Introduces Middleware Architecture for Genkit Applications

Google has introduced Middleware for Genkit, its open-source framework for building AI-powered and agentic applications. The update adds a programmable interception layer around model calls, tool execution, and generation loops, giving developers more control over reliability, safety, and orchestration inside production AI systems.

By Robert Krzaczyński
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Google Cloud Highlights Ongoing Work on PostgreSQL Core Capabilities

Google Cloud has outlined its recent technical contributions to PostgreSQL, emphasizing improvements in logical replication, upgrade processes, and overall system stability. The update reflects ongoing collaboration with the upstream community and focuses on enhancements to the core engine aimed at addressing scalability, replication, and operational challenges.

By Robert Krzaczyński
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Google Brings MCP Support to Colab, Enabling Cloud Execution for AI Agents

Google has released the open-source Colab MCP Server, enabling AI agents to directly interact with Google Colab through the Model Context Protocol (MCP). The project is designed to bridge local agent workflows with cloud-based execution, allowing developers to offload compute-intensive or potentially unsafe tasks from their own machines.

By Robert Krzaczyński
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