All news with #google tag

🚀 At Google Cloud Next '26, Firestore introduced expanded agentic AI integrations, built-in full-text search, and deeper MongoDB compatibility aimed at accelerating agent-driven applications. The Enterprise edition’s reimagined query engine adds hundreds of expressive query features, JOINs via subqueries, and pipeline operations. Native connections to AI Studio and third-party coding agents plus preview tools like natural language console querying and Usage Insights simplify building agentic workflows. These capabilities are available now in Firestore Enterprise in both Native and MongoDB compatibility modes.

🔒 Chrome Enterprise Premium extends the familiar Chrome browser with enterprise-grade security, management, and healthcare-focused integrations to help clinicians access EHRs and web apps securely. It highlights advanced DLP, real-time URL scanning, phishing and malware protections, and controls to block copy/paste, printing, or screen capture of sensitive records. Google announced partnerships with Epic, Imprivata, AuthX, and Citrix to optimize EHR performance, enable passwordless authentication, streamline identity, and unify virtualized workflows. Eligible organizations are offered an extended 6-month trial, no-charge seats for the trial, $5,000 in services funding upon conversion, and high-touch onboarding.

🔐 A Vietnamese-linked operation used a Google AppSheet address as a phishing relay to distribute credential-harvesting pages and compromise roughly 30,000 Facebook accounts. Guardio, calling the scheme AccountDumpling, says stolen accounts are resold via an illicit storefront after exfiltration to Telegram channels. Lures hosted on Netlify, Vercel and Google Drive, plus Canva-generated PDFs, were used to harvest passwords, 2FA codes, IDs and business data, leaving many victims locked out.

🔒 Researchers disclosed a max-severity remote code execution (RCE) vulnerability in @google/gemini-cli and the associated GitHub Action that could load untrusted workspace configurations in headless CI environments. Google issued patches in 0.39.1, 0.40.0-preview.3 and updated the run-gemini-cli Action to 0.1.22, removing implicit workspace trust and enforcing tool allowlists. Teams that pin CLI versions are advised to upgrade and review workspace configurations immediately.

🔒 Google patched a maximum-severity remote code execution vulnerability in @google/gemini-cli and the google-github-actions/run-gemini-cli workflow that could allow attackers to run arbitrary commands on host systems. Novee Security reported the flaw, which carries a CVSS score of 10.0, and Google says the impact is limited to headless CI usage where workspace folders were auto-trusted. Affected versions include @google/gemini-cli prior to 0.39.1 (and preview releases) and run-gemini-cli prior to 0.1.22; users should update to the patched releases, explicitly set GEMINI_TRUST_WORKSPACE when inputs are trusted, or follow Google’s hardening guidance for untrusted inputs. Google also tightened allowlisting checks for --yolo mode to prevent auto-approved tool calls from bypassing restrictions.

🤖 AWS has added Google DeepMind's instruction‑tuned Gemma 4 E4B, Gemma 4 26B‑A4B, and Gemma 4 31B to SageMaker JumpStart, making multimodal foundation models directly accessible to AWS customers. The models offer configurable step‑by‑step reasoning, interleaved text and image inputs, video and image understanding, native function calling, and multilingual support across 140+ languages. Gemma 4 E4B also supports audio input for ASR and speech‑to‑translated‑text workflows. Customers can deploy these models via SageMaker Studio or the SageMaker Python SDK for rapid experimentation and production.

🚀 Google Cloud Next ’26 introduced an integrated AI stack for startups centered on Gemini Enterprise, an end‑to‑end agent lifecycle platform with an Agent Development Kit, Agent Studio, and production runtimes that support sub‑second starts and persistent memory. The Agentic Data Cloud and zero‑ETL features enable cross‑cloud data access and high‑accuracy text‑to‑SQL to avoid costly migrations. Infrastructure updates (TPU 8t/8i, Axion N4A, new networking machines, and GKE sandboxes) plus agentic security integrations and a $750M partner fund aim to accelerate prototyping, secure production deployments, and enterprise go‑to‑market.

🤖 UKG built People Fabric to unify its legacy HCM and WFM systems into a single, real-time data and intelligence platform powered by AlloyDB for PostgreSQL and Google's Agentic Data Cloud. The platform establishes a canonical data model, ingests change streams via a custom CDC pipeline and Dataflow, and serves operational queries from AlloyDB while routing analytics workloads to BigQuery and tenancy metadata to Cloud SQL. The outcome is millisecond read-after-write behavior, native vector support for AI agents, and faster developer velocity across 126 application teams and thousands of database instances.

🤖 At Google Cloud Next, public sector leaders showcased how they are using AI agents to boost productivity and mission impact across government and research organizations. Google introduced the Gemini Enterprise Agent Platform—an evolution of Vertex AI—plus the Gemini Enterprise App with Gemini 3.1 Pro and an Agent Designer for inspectable, schedule‑based workflows. The announcement also covered AI infrastructure (TPU 8 series), an Agentic Data Cloud, enhanced security and Agentic Defense, partner initiatives, and upskilling through the GEAR program.

🤖 Google Cloud Next '26 in Las Vegas showcased a broad enterprise push into the agentic era, with over 32,000 attendees and 260 product, partner, and customer announcements. Highlights include the new Gemini Enterprise Agent Platform, the Gemini Enterprise app, 8th-generation TPUs, and a host of agent-focused capabilities for development, runtime, memory, observability, and governance. The week emphasized production readiness, cross-cloud data integration, and strengthened security through the Wiz acquisition and Model Armor integrations.

🔎 Google Threat Intelligence scanned a large Common Crawl corpus to detect indirect prompt injection (IPI) patterns embedded in public web pages. The team combined signature-based pattern matching, Gemini-assisted classification, and manual review to reduce false positives and contextualize findings. Most observed injections were low-sophistication—pranks, benign guidance, or SEO-driven prompts—but a smaller and rising set attempted data exfiltration or destructive actions. The study excludes social media and login-protected content and reports a 32% increase in malicious samples between Nov 2025 and Feb 2026.

🔒 At Google Cloud Next 26, COO Francis DeSouza said Google will not release a separate cyber‑focused frontier model and instead relies on the generalist Gemini3.1 Pro for security use cases. He advised pairing a strong general model with the right tooling, governance and access controls and training it on organisation‑specific context. Google plans to combine Gemini with agent and platform capabilities to support automated detection, triage and response. Competitors such as Anthropic and OpenAI are pursuing specialised variants like Claude Mythos and GPT‑5.4‑Cyber.

🤖 At Google Cloud Next day 2, the developer keynote focused on the Gemini Enterprise Agent Platform, demonstrating tools to build, simulate, evaluate, and scale autonomous agents. Presentations covered the Agent Development Kit (ADK), Model Context Protocol (MCP) servers, Agent Runtime, Memory Bank, Agent Registry, A2UI/A2A standards, and debugging with Gemini Cloud Assist. Speakers also addressed security and governance with Agent Identity, Agent Gateway, and partner demos from Wiz, and released source code and codelabs to help teams adopt agentic development.

🛡️ Google unveiled a suite of agentic AI defenses at Google Cloud Next '26 to help SOC teams manage a surge of vulnerabilities tied to Anthropic Mythos. The launch includes three new agents in Google Security Operations — threat hunting, detection engineering, and third-party context — plus expanded Wiz integrations and an AI-BOM to inventory AI components. Additional controls like Agent Identity, Agent Gateway, and Model Armor aim to govern the emerging 'agentic web' and mitigate prompt injection, data leakage, and shadow AI risks.

🔐 Google announced a shift to agent-centric security at Google Cloud Next '26, positioning AI agents to help SOC teams respond to the potential surge of vulnerabilities tied to Anthropic's Mythos. It introduced three new agents in Google Security Operations — a threat hunting agent, a detection engineering agent and a third-party context agent — and said its existing triage agent has processed over five million alerts, reducing analysis from about 30 minutes to roughly a minute with Gemini. Additional moves include expanded Wiz integrations, an AI-BOM to inventory AI components, agentic automation features, Model Armor protections, Agent Identity and Agent Gateway controls, and modern IAM simplifications to streamline permissions.

🛡️ Google has launched the Gemini Enterprise Agent Platform, a hub for managing agentic AI that assigns each agent a unique cryptographic ID to enable traceable, auditable actions and map to authorization policies. The platform centralizes agents, tools and skills in an Agent Registry and offers an Agent Gateway to enforce agent-to-agent and agent-to-tool policies, apply Model Armor protections, and support MCP and A2A protocols. New detection and security features include real-time Agent Anomaly Detection, an Agent Security dashboard integrated with Security Command Center, and specialized security agents for threat hunting, detection engineering and third-party context enrichment.

🚀 At Google Cloud Next ’26, Google presented a unified stack to move AI into enterprise production, anchored by Gemini Enterprise as the connective tissue between data, people, and goals. Key launches include the Gemini Enterprise Agent Platform for building, scaling, governing, and optimizing agents, and the AI Hypercomputer with next-generation TPU 8 chips. Google also outlined the Agentic Data Cloud to ground agents in enterprise context, expanded security agents in Agentic Defense, Workspace Intelligence enhancements, and cross-cloud data capabilities to accelerate real-world deployment.

🚀 Google Cloud has integrated partner-built agents from its Agent Marketplace into the Agent Gallery inside the Gemini Enterprise app, creating a centrally governed hub for discovering and managing specialist, role-specific AI. Featured partners — including Accenture, Adobe, Atlassian, Palo Alto Networks, Salesforce and others — must pass a four-step evaluation to earn the Google Cloud Ready - Gemini Enterprise badge. Built-in safeguards such as cryptographic agent identities, Agent Gateway, and Model Armor protect data and prevent use for model training. Customers can trial the Gallery, while partners can apply to the AI Agents Program and access a rapid deployment framework.

🚀 Gemini Enterprise is an end-to-end system for the agentic era, combining access to frontier models, a developer platform, a collaborative app, and a partner ecosystem to build and deploy agent fleets. The offering centers on the Gemini Enterprise Agent Platform — an evolution of Vertex AI — with an enhanced Agent Development Kit (ADK), graph-based orchestration, persistent Memory Bank, and fast Agent Runtime for multi-step work. IT teams gain a unified control plane for identity, governance, Model Armor, and auditing, while knowledge workers use a no-code Agent Designer, Inbox, Projects, and Canvas to create and monitor agents.

🚀 Google announces the Virgo Network, a megascale, flat two-layer fabric purpose-built for modern AI workloads that unifies accelerators across pods into a single compute domain. The design separates a high-bandwidth scale-up domain, an east-west RDMA scale-out accelerator fabric, and the Jupiter north-south network to deliver deterministic low latency and massive non-blocking bandwidth. Virgo uses high-radix switches and multi-planar control domains to reduce layers and isolate faults, while sub-millisecond telemetry and automated straggler detection aim to preserve cluster goodput. The fabric targets predictable performance and rapid recovery for large distributed training and serving.