All news with #google tag

🛡️ Google has asked a US court to dismantle infrastructure used by the Lighthouse phishing‑as‑a‑service operation after identifying at least 107 sign‑in templates that mimic Google branding. The service is marketed to attackers who send smishing links and host fraudulent sign‑in pages to harvest credentials. Google also urged Congress to consider GUARD, Foreign Robocall Elimination and SCAM bills to bolster enforcement and funding. The company declined additional comment.

⚖️ Google has filed a lawsuit to dismantle the Lighthouse phishing‑as‑a‑service platform accused of enabling global SMS phishing (“smishing”) that impersonates USPS and toll providers. The company says Lighthouse has impacted more than 1 million victims in 120 countries and that similar scams may have exposed up to 115 million U.S. payment cards between July 2023 and October 2024. Google’s complaint invokes federal racketeering, trademark, and computer fraud laws and seeks to seize the infrastructure hosting fraudulent templates that even mimic Google sign‑in screens.

🛡️ Google has filed a lawsuit seeking to dismantle Lighthouse, a China-linked phishing-as-a-service platform accused of powering global SMS phishing ("smishing") campaigns that impersonate USPS and E-ZPass. Google says Lighthouse has impacted more than 1 million victims across 120 countries and that phishing templates even display Google's branding to trick users. The company is pursuing federal claims including RICO, the Lanham Act, and the CFAA while expanding AI and product protections.

🤖 BigQuery is introducing managed AI functions in public preview — AI.IF, AI.CLASSIFY, and AI.SCORE — that let analysts apply generative AI directly inside SQL queries. These functions enable semantic filtering and joins, label-based classification of text and images, and natural-language ranking, while BigQuery applies prompt, query-plan, and endpoint optimizations to reduce LLM calls and control cost. They complement existing Gemini inference functions and remove much of the need for complex prompt tuning or separate model selection, making AI-driven analytics more accessible within familiar SQL workflows.

🛡️ The Emerging Threats Center in Google Security Operations uses the Gemini detection‑engineering agent to turn frontline intelligence from Mandiant, VirusTotal, and Google into actionable detections. It generates high‑fidelity synthetic events, evaluates existing rule coverage, and drafts candidate detection rules for analyst review. The capability surfaces campaign‑based IOC and detection matches across 12 months of telemetry to help teams rapidly determine exposure and validate their defensive posture.

🚀 Google outlines its plan to embed Generative AI across enterprise platforms and endpoints, integrating Gemini into Chrome Enterprise, Android, Pixel phones and Chromebook Plus devices. The post highlights the general availability of Cameyo by Google to virtualize legacy and modern apps in the cloud and the launch of Gemini in Chrome with enterprise-grade controls. It also previews Android XR and Pixel features powered by Gemini Nano, while expanding data loss prevention and a one-click SecOps integration to help IT secure AI-driven workflows.

🔒 Cameyo by Google is a cloud-native Virtual App Delivery solution that streams legacy Windows and Linux applications into the browser or publishes them as Progressive Web Apps, avoiding the overhead of full VDI. Paired with Chrome Enterprise Premium, Cameyo brings legacy client apps under a single secure browsing context with advanced DLP and threat protection. IT teams benefit from faster deployments, reduced VPN and infrastructure complexity, and a clear migration path to ChromeOS while preserving critical Windows workloads.

🔍 BigQuery now supports MATCH_RECOGNIZE, a SQL clause for identifying ordered patterns across rows and time-series data. It lets analysts express complex sequence logic—using PARTITION BY, ORDER BY, PATTERN, DEFINE and MEASURES—inside a single query without heavy joins or external processing. The feature targets use cases like funnels, fraud detection, log sequencing, and financial pattern detection, and is immediately available to all BigQuery users.

⚖️ Google has filed a civil lawsuit in the U.S. District Court for the Southern District of New York against China-based operators of the PhaaS kit Lighthouse, which Google says has ensnared over one million users across 120 countries. The platform is accused of powering industrial-scale SMS phishing and smishing campaigns that impersonate trusted brands like E-ZPass and USPS to steal financial data. Google alleges the actors illegally used its trademarks on at least 107 spoofed sign-in templates and seeks to dismantle the infrastructure under the RICO, Lanham Act, and the Computer Fraud and Abuse Act. Security firms link Lighthouse to a broader PhaaS ecosystem including Darcula and Lucid, and to a smishing syndicate tracked as Smishing Triad.

🔒 Google on Tuesday introduced Private AI Compute, a cloud privacy capability that aims to deliver on-device-level assurances while harnessing the scale of Gemini models. The service uses Trillium TPUs and Titanium Intelligence Enclaves (TIE) and relies on an AMD-based Trusted Execution Environment to encrypt and isolate memory on trusted nodes. Workloads are mutually attested, cryptographically validated, and ephemeral so inputs and inferences are discarded after each session, with Google stating data remains private to the user — 'not even Google.' An external assessment by NCC Group flagged a low-risk timing side channel in the IP-blinding relay and three attestation implementation issues that Google is mitigating.

🚀 Lightricks rewrote its training stack in JAX to scale high-performance video diffusion models on TPUs after hitting limits with PyTorch/XLA. The migration enabled reliable sharding, fixed FlashAttention and data-loading issues, and delivered linear scaling across small and large TPU pods. These improvements translated to ~40% more training steps per day, faster iteration, and doubled team productivity. Their stack leverages Flax, Optax, Orbax, and the MaxText blueprint for robust, testable, and efficient large-scale training.

🔍 In early 2024 Google introduced native vector search in BigQuery, embedding semantic search directly into the data warehouse to remove the need for separate vector databases. Users can create indexes with a simple CREATE VECTOR INDEX statement and run semantic queries via the VECTOR_SEARCH function or through Python integrations like LangChain. BigQuery provides serverless scaling, asynchronous index refreshes, model rebuilds with no downtime, partitioned indexes, and ScaNN-based TreeAH for improved price/performance, while retaining row- and column-level security and a pay-as-you-go pricing model.

🔐 Genians Security Center (GSC) has attributed a recent destructive campaign to the KONNI APT, which abused Google’s Find Hub service to remotely wipe Android phones and tablets. Threat actors distributed a signed MSI via compromised KakaoTalk accounts, installed an AutoIt loader, and stole Google credentials to trigger remote resets when victims were away. GSC describes this as the first confirmed state-linked misuse of Find Hub and recommends stronger authentication, verification for remote wipes, and enhanced EDR and behavioral monitoring.

🔒 A newly disclosed exploit named Pixnapping (CVE-2025-48561) allows a malicious Android app with no special permissions to read screen pixels from other apps and reconstruct sensitive content. The attack chains intent-based off-screen rendering, translucent overlays, and a GPU compression timing side channel to infer pixel values. Google issued a September patch but researchers bypassed it, and a more robust fix is planned.

🔒 Genians Security Center (GSC) reports that North Korea–linked KONNI actors abused Google's Android device‑tracing and management service Find Hub to remotely track and wipe victims' phones. Attackers compromised legitimate Google accounts—often via spear‑phishing impersonating South Korea’s National Tax Service—and used Find Hub to confirm location and issue reset commands that silenced alerts. The campaign also spread malware through compromised KakaoTalk contacts sending apps disguised as 'stress-relief' programs.

🚀 Google details a broad set of GKE and Kubernetes enhancements announced at KubeCon to address agentic AI, large-scale training, and latency-sensitive inference. GKE introduces Agent Sandbox (gVisor-based) for isolated agent execution and a managed GKE Agent Sandbox with snapshots and optimized compute. The platform also delivers faster autoscaling through Autopilot compute classes, Buffers API, and container image streaming, while inference is accelerated by GKE Inference Gateway, Pod Snapshots, and Inference Quickstart.

🧭 This post explains when to use sub-agents versus packaging agents as tools when building multi-agent systems with Google's Agent Development Kit (ADK). It contrasts agents-as-tools — encapsulated, stateless specialists invoked like deterministic function calls — with sub-agents, which are stateful, context-aware delegates that manage multi-step workflows. The guidance highlights trade-offs across task complexity, context sharing, reusability, and autonomy, and illustrates the patterns with data-agent and travel-planner examples to help architects choose efficient, scalable designs.

🤖 Google appears set to release two new models: Gemini 3 Pro, optimized for coding and general use, and Nano Banana 2 (codenamed GEMPIX2), focused on realistic image generation. Gemini 3 Pro was listed on Vertex AI as "gemini-3-pro-preview-11-2025" and is expected to begin rolling out in November with a reported 1 million token context window. Nano Banana 2 was also spotted on the Gemini site and could ship as early as December 2025.

🚀 LMCache implements a node-local, tiered KV Cache on GKE to extend the GPU HBM-backed Key-Value store into CPU RAM and local SSD, increasing effective cache capacity and hit ratio. In benchmarks using Llama-3.3-70B-Instruct on an A3 mega instance (8×nvidia-h100-mega-80gb), configurations that added RAM and SSD reduced Time-to-First-Token and materially increased token throughput for long system prompts. The results demonstrate a practical approach to scale context windows while balancing cost and latency on GKE.

🤖 This recap of The Agent Factory features Logan Kilpatrick from Google DeepMind demonstrating vibe coding in Google AI Studio, a Build workflow that turns a natural-language app idea into a live prototype in under a minute. Live demos included a virtual food photographer, grounding with Google Maps, the AI Studio Gallery, and a speech-driven "Yap to App" pair programmer. The episode also surveyed agent ecosystem updates—Veo 3.1, Anthropic Skills, and Gemini improvements—and highlighted the shift from models to action-capable systems.