All news with #google tag

🤖 Google’s open-source Agent Development Kit (ADK) simplifies creating autonomous AI agents that use LLMs such as Gemini as their reasoning core. The post presents three hands-on codelabs that guide developers through building a personal assistant agent, adding custom and third-party tools, and orchestrating multi-agent workflows. Each lab demonstrates practical patterns—scaffolding an agent, integrating tools like Google Search and LangChain components, and using Workflow Agents and session state to pass information—so teams can progress from experiment to production-ready agent systems.

📍 Google has introduced a dedicated form for businesses on Google Maps to report extortion attempts where threat actors post inauthentic negative reviews and demand payment to remove them. The move targets review bombing schemes that flood profiles with fake one-star reviews and then coerce owners, often via third-party messaging apps. Google also highlighted related threats — from job and AI impersonation scams to malicious VPN apps and fraud recovery cons — and advised practical precautions for affected merchants and users.

🔔 Google’s Trust & Safety team published a November 2025 advisory describing rising online scam trends, attacker tactics, and recommended defenses. Analysts highlight key categories — online job scams, negative review extortion, AI product impersonation, malicious VPNs, fraud recovery scams, and seasonal holiday lures — and note increased misuse of AI to scale fraud. The advisory outlines impacts including financial theft, identity fraud, and device or network compromise, and recommends protections such as 2‑Step Verification, Gmail phishing defenses, Google Play Protect, and Safe Browsing Enhanced Protection.

🔒 Google’s November 2025 scams advisory outlines rising, increasingly AI-driven fraud tactics and provides concrete protections. Analysts detail six prioritized threats — including online job scams, review-extortion, AI service impersonation, malicious VPNs, fraud-recovery cons, and seasonal holiday schemes — and describe associated malware and credential risks. The post highlights Gmail, Google Messages, Safe Browsing, Play Protect, and account security features like 2‑Step Verification, and gives practical guidance for individuals and merchants.

🔒 Bug bounty programs remain a core component of security testing in 2025, drawing external researchers to identify flaws across web, mobile, AI, and critical infrastructure. Leading platforms like Bugcrowd, HackerOne, Synack and vendors such as Apple, Google, Microsoft and OpenAI have broadened scopes and increased payouts. Firms now reward full exploit chains and emphasize human-led reconnaissance over purely automated scanning. Programs also support regulatory compliance in critical sectors.

🌱 Google presents a Sustainable by Design approach to reduce the environmental footprint of AI and software. The post highlights projects like Green Light and Project Contrails, improvements in hardware efficiency such as Ironwood TPUs, and a fleet-wide Power Usage Effectiveness of 1.09. It introduces the 4Ms—Machine, Model, Mechanisation, Map—to guide infrastructure and development choices. The emphasis is on embedding efficiency across the software lifecycle to cut energy use, costs, and water consumption.

⚠️Google's Threat Intelligence Group reports a surge in malware that integrates large language models to enable dynamic, mid-execution changes—what Google calls "just-in-time" self-modification. Notable examples include the experimental PromptFlux VBScript dropper and the PromptSteal data miner, plus operational threats like FruitShell and QuietVault. Google disabled abused Gemini accounts, removed assets, and is hardening model safeguards while collaborating with law enforcement.

⚠️ The Google Threat Intelligence Group (GTIG) reports that adversaries are evolving beyond simple productivity uses of AI toward operational misuse. Observed behaviors include state-sponsored actors from North Korea, Iran and the People's Republic of China using AI for reconnaissance, automated phishing lure creation and data exfiltration. The report documents AI-powered malware that can generate and modify malicious scripts in real time and attackers exploiting deceptive prompts to bypass model guardrails. Google says it has disabled assets linked to abuse and applied intelligence to improve classifiers and harden models against misuse.

🔒 The Google Threat Intelligence Group (GTIG) released a report documenting a clear shift: adversaries are moving beyond benign productivity uses of AI and are experimenting with AI-enabled operations. GTIG observed state-sponsored actors from North Korea, Iran and the People's Republic of China using AI for reconnaissance, tailored phishing lure creation and data exfiltration. Threats described include AI-powered, self-modifying malware, prompt-engineering to bypass safety guardrails, and underground markets selling advanced AI attack capabilities. Google says it has disrupted malicious assets and applied that intelligence to strengthen classifiers and its AI models.

🛡️ The Google Threat Intelligence Group (GTIG) released a November 2025 report describing how adversaries are evolving beyond productivity uses of AI to operationalize novel offensive capabilities. GTIG observed state-sponsored actors (including North Korea, Iran, and the People’s Republic of China) and criminal groups using AI for reconnaissance, tailored phishing-lure generation, prompt-based guardrail evasion, and AI-powered polymorphic malware. Google reports it has disabled malicious assets and applied this intelligence to strengthen both its classifiers and AI model defenses.

⚠️Google's Threat Intelligence team reports a shift from experimentation to operational use of AI by threat actors, including AI-enabled malware and prompt-based command generation. GTIG highlighted PROMPTSTEAL, linked to APT28 (FROZENLAKE), which queries a Hugging Face LLM to generate scripts for reconnaissance, document collection, and exfiltration, while adopting greater obfuscation and altered C2 methods. Google disabled related assets, strengthened model classifiers and safeguards with DeepMind, and urges defenders to update threat models, monitor anomalous scripting and C2, and incorporate threat intelligence into model- and classifier-level protections.

🔍 Google Threat Intelligence Group (GTIG) reports an operational shift from adversaries using AI for productivity to embedding generative models inside malware to generate or alter code at runtime. GTIG details “just-in-time” LLM calls in families like PROMPTFLUX and PROMPTSTEAL, which query external models such as Gemini to obfuscate, regenerate, or produce one‑time functions during execution. Google says it disabled abusive assets, strengthened classifiers and model protections, and recommends monitoring LLM API usage, protecting credentials, and treating runtime model calls as potential live command channels.

🧭 This guide summarizes Multi-Agent System (MAS) fundamentals and explains how Google’s Agent Development Kit (ADK) helps developers assemble cooperating agents to solve complex tasks. It outlines three agent roles — LLM Agents for reasoning, Workflow Agents for orchestration, and Custom Agents for bespoke logic — and describes hierarchical organization and orchestration patterns (sequential, parallel, loop). The post also reviews communication options (shared state, LLM delegation, explicit invocation) and points developers to samples and codelabs for rapid prototyping.

📰 In October, Google highlighted AI advances across research, consumer devices and enterprise tools, from rolling out Gemini for Home and vibe coding in AI Studio to launching Gemini Enterprise for workplace AI. The month included security initiatives for Cybersecurity Awareness Month—anti‑scam protections, CodeMender and the Secure AI Framework 2.0—and developer releases like the Gemini 2.5 Computer Use model. Research milestones included a verifiable quantum advantage result and an oncology-focused model, Cell2Sentence-Scale, aimed at accelerating cancer therapy discovery.

🤖 October updates feature major product releases, developer tools, and research milestones from Google, centered on Gemini models and new AI capabilities. Highlights include Gemini Enterprise, the Gemini 2.5 Computer Use model for UI agents, plus consumer integrations such as Gemini for Home and Samsung's Galaxy XR. The month also brought breakthroughs in quantum computing, cancer research (Cell2Sentence-Scale) and fusion-energy collaborations, alongside expanded AI security measures and developer learning resources.

🔒 Google’s AI agent Big Sleep reported five vulnerabilities in Apple’s WebKit used by Safari, including a buffer overflow, two memory-corruption issues, an unspecified crash flaw, and a use-after-free (CVE-2025-43429 through CVE-2025-43434). Apple issued patches across iOS 26.1, iPadOS 26.1, macOS Tahoe 26.1, tvOS 26.1, watchOS 26.1, visionOS 26.1 and Safari 26.1. Users are advised to install the updates promptly to mitigate crash and memory-corruption risks.

🔧 The preview of the Data Engineering Agent in BigQuery introduces a Gemini-powered assistant that automates pipeline development, maintenance, and migrations. The agent converts natural-language requirements into SQL, enforces engineering best practices, and supports custom instructions and UDFs to reflect organizational logic. Integrated with Dataplex, it uses governance metadata to improve table descriptions, data quality assertions, and PII-aware handling, and it also generates documentation and troubleshooting guidance. The feature is available in preview via BigQuery Pipelines and the Dataform UI.

🚀 Mercado Libre leverages Spanner as the core of a developer-facing platform, exposing consistent, globally-scalable transactions through its internal gateway, Fury. Fury abstracts distributed database complexity and serves both relational and key-value workloads. Integration with BigQuery via Data Boost and Change Streams enables near-real-time analytics and reverse ETL to operational systems.

🔐 Matt Kiely of Huntress examines how the OAuth 2.0 device code flow enables phishing and highlights stark differences between Microsoft and Google. He walks through the device-code attack chain — generating a device code, social-engineering a user to enter it on a legitimate site, and polling the token endpoint to harvest access and refresh tokens. The analysis shows Azure’s implementation lets attackers control client_id and resource parameters to obtain powerful tokens, while Google’s implementation restricts device-code scopes and requires app controls that significantly limit abuse. Practical examples, cURL/Python snippets, and mitigation advice are included for defenders.

📣Google says its ad business will remain central as it integrates advertising into AI-powered search experiences. Google currently offers AI Overviews and a more capable AI Mode, and has begun limited experiments placing ads within those results. Executives say ads won't disappear but may appear differently and become more personalized based on user data. Tests and further plans are expected to continue into next year.