Keepit announced AI Truth Cloud, transforming backup from a compliance requirement into the strategically valuable data asset an organization can hold. As AI agents take on business-critical decisions, AI Truth Cloud positions Keepit as the sovereign source of truth that enterprise AI can safely build on: data that is verifiable, governed, immutable, and proven. From backup to trusted enterprise o

Keepit has announced a new offering, AI Truth Cloud, designed to provide a verifiable, governed, and immutable data foundation for enterprise artificial intelligence systems. The company positions this new service as an evolution from traditional data backup, transforming it into a strategic asset that ensures the integrity and trustworthiness of data used by AI agents for critical business decisions.
The AI Truth Cloud aims to address the challenge of ensuring AI systems operate on reliable data by establishing Keepit as an independent, tamper-proof source of truth. This independence is crucial for verifying the authenticity, provenance, and integrity of data before it is ingested into any AI system, thereby ensuring that AI reasoning is based on trusted information.
According to Keepit, the platform is built on five core pillars: Protect, Observe, Recover, Prove, and Integrate. These pillars form a comprehensive framework for data trust, moving beyond simple backup and recovery.
Three immediate capabilities form the foundation of the AI Truth Cloud roadmap. First, AI Connector Backup extends Keepit's existing data protection to AI tools, covering elements such as agent configurations, AI skills, projects, and models. This allows for point-in-time restoration of any AI asset and provides a verified recovery point in cases of unexpected AI agent behavior or compromise.
Second, the Keepit MCP (Model Context Protocol) platform is introduced as a headless API layer. This protocol enables AI systems to programmatically query, audit, and interact with managed data, positioning Keepit as an active node within an enterprise's trust fabric rather than a passive data repository.
Third, Keepit AI Safe Room addresses the risk of running AI models directly on live production data. It provides an immutable copy of data within an isolated environment for AI training, inference, and testing. This setup prevents production data from being exposed to risk and allows for full rollback if a model, prompt, or agent produces unintended results, leaving production untouched and enabling immediate recovery.
Looking ahead, Keepit plans to develop additional capabilities across all five pillars. These include AI agent behavioral monitoring, automated compliance evidence generation, cryptographic data provenance, and AI-powered threat rollback, all intended to further establish the platform as a trusted data layer for enterprise AI.
Keepit emphasizes that AI Truth Cloud is a natural progression for the company, building on its existing data foundation. The company intends to expand its connector coverage as organizations increasingly adopt AI-driven and agentic workflows, focusing on protecting the data that AI agents create and consume. Additionally, Keepit is launching an ISV partnership strategy, allowing software vendors to embed sovereignty, immutability, governance, and trusted AI capabilities directly into their products through deep integrations with the Keepit platform, aiming to establish Keepit as an underlying trust layer across the enterprise software ecosystem.
A weakness has been identified in Tenda CP3 27.5.57.101. This issue affects some unknown processing of the file Net/NetCheckPing.cpp. This manipulation of the argument interface_name/host causes os command injection. The attack can be initiated remotely.
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In BPF instructions that load/store a value from/to a scratch memory register the register index is an unsigned 32-bit integer and must not exceed 15, but libpcap BPF interpreter does not validate the value. In particular uncommon use cases a crafted filter program can cause the interpreter to try reading and writing the OS process memory in the 16GiB starting at the current stack frame on 64-bit architectures and in the entire address space on 32-bit architectures.

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