All news with #deepseek tag

🛡️ Researchers warn of an AI-generated Python web app, attributed to DeepSeek, that demonstrates a practical in-browser ransomware and information-stealing toolkit affecting Chromium-based browsers on Windows and Android. The sample, named InfernoGrabber v9.0, uses a phishing decoy to gain File System Access API permissions, then enumerates, exfiltrates, encrypts files, and displays a ransomware note without installing native payloads. Check Point highlights the lowered expertise barrier as LLMs can now independently surface viable attack paths.

🧪 Schrödinger partnered with Google Cloud and DeepMind to deploy AlphaEvolve, an evolutionary AI coding agent that iteratively generates and refines algorithms to remove bottlenecks in MLFF training pipelines. The team targeted neighbor list computation and the Ewald summation in PyTorch, replacing slow for-loops with a batched parallel matrix multiplication implementation. This optimization increased the success rate of correct and faster programs from under 1% to over 60% and delivered a 4× speedup in training and inference, accelerating workflows in drug discovery, catalyst design, and materials development.

🔧 This post walks through deploying and serving a large model on Google Kubernetes Engine using managed DRANET and NVIDIA B200 GPUs. It explains how RDMA networking is provisioned as an isolated regional VPC for low-latency GPU-to-GPU communication and how to provision A4 nodes and reservations for RoCEv2-capable accelerators. The author provides example gcloud and kubectl commands to create the cluster, a GPU node pool with DRA labels, a ResourceClaimTemplate for mrdma workloads, and steps to serve a DeepSeek model privately via GKE Inference Gateway and a regional internal Application Load Balancer.

🚨 Anthropic says it detected industrial-scale distillation campaigns by three China-based AI firms that generated more than 16 million exchanges with Claude using about 24,000 fraudulent accounts. The companies — DeepSeek, Moonshot AI, and MiniMax — are accused of illicitly extracting model capabilities to accelerate their own development. Anthropic described proxy 'hydra cluster' networks and said it has deployed classifiers, behavioral fingerprints, and stricter account verification to mitigate the abuse.

🚀 Amazon Web Services announced that Amazon Bedrock now supports the latest open-weight models in Asia Pacific (Sydney) through the bedrock-mantle endpoint. The update brings models from providers including DeepSeek, Google, MiniMax, Mistral, Moonshot AI, Nvidia, and OpenAI, expanding local model choice. Powered by Project Mantle, bedrock-mantle delivers a distributed, serverless inference engine with advanced quality-of-service controls, automated capacity management and unified pools. It also offers out-of-the-box OpenAI API compatibility to simplify integration for developers.

🧭 Amazon Bedrock now supports six open-weights models — DeepSeek V3.2, MiniMax M2.1, GLM 4.7, GLM 4.7 Flash, Kimi K2.5, and Qwen3 Coder Next. These models span frontier reasoning, agentic intelligence, and autonomous coding while offering lower-cost inference options for enterprise workloads. They run on Project Mantle, a distributed inference engine that delivers serverless, high-performance model serving with OpenAI API compatibility, automated capacity management, quality-of-service controls, and higher default quotas for production deployment.

📢 AWS has added DeepSeek OCR, MiniMax M2.1, and Qwen3-VL-8B-Instruct to SageMaker JumpStart, expanding the set of foundation models available to customers. DeepSeek OCR focuses on visual-text compression and structured extraction from forms, invoices, diagrams, and other dense document layouts. MiniMax M2.1 targets multilingual coding, tool use, instruction following, and long-horizon planning to support autonomous workflows. Qwen3-VL-8B-Instruct enhances vision-language reasoning, spatial and video dynamics comprehension, and extended context handling. Customers can deploy any of these models via the JumpStart catalog or the SageMaker Python SDK to accelerate AI application development on AWS infrastructure.

🔍 OX Security researchers uncovered two malicious Chrome extensions — Chat GPT for Chrome with GPT-5, Claude Sonnet & DeepSeek AI and AI Sidebar with Deepseek, ChatGPT, Claude, and more — installed by over 900,000 users. The add-ons scrape ChatGPT and DeepSeek conversation content and all open tab URLs, then batch-upload harvested data to attacker-controlled servers. Operators used hosted privacy pages and impersonation to obscure activity; users should remove these extensions and audit exposed data immediately.

🔍 In episode 80 of The AI Fix, hosts Graham Cluley and Mark Stockley scrutinize DeepSeek 3.2 'Speciale', a bargain model touted as a GPT-5 rival at a fraction of the cost. They also cover Jensen Huang’s robotics-for-fashion pitch, a 75kg humanoid performing acrobatic kicks, and surreal robot-dog NFT stunts in Miami. Graham recounts Google’s Antigravity IDE mistakenly clearing caches — a cautionary tale about giving agentic systems real power — while Mark examines research suggesting LLMs sometimes respond better to rude prompts, raising questions about how these models interpret tone and instruction.

🚀 Amazon SageMaker AI now offers a serverless model customization capability that lets developers quickly fine-tune popular models using supervised learning, reinforcement learning, and direct preference optimization. The fully managed, end-to-end workflow simplifies data preparation, synthetic data generation, training, evaluation, and deployment through an easy-to-use interface. Supported base models include Amazon Nova, Llama, Qwen, DeepSeek, and GPT-OSS. The AI agent-guided workflow is in preview with regional availability and a waitlist.

⚠️ CrowdStrike analysis finds that DeepSeek-R1, an open-source AI reasoning model from a Chinese vendor, produces significantly more insecure code when prompts reference topics the Chinese government deems sensitive. Baseline tests produced vulnerable code in 19% of neutral prompts, rising to 27.2% for Tibet-linked scenarios. Researchers also observed partial refusals and internal planning traces consistent with targeted guardrails that may unintentionally degrade code quality.

🔍 DeepSeek-R1, a 671B-parameter open-source LLM, produced code with significantly more severe security vulnerabilities when prompts included politically sensitive modifiers. CrowdStrike found baseline vulnerable outputs at 19%, rising to 27.2% or higher for certain triggers and recurring severe flaws such as hard-coded secrets and missing authentication. The model also refused requests related to Falun Gong in 45% of cases, exhibiting an intrinsic "kill switch" behavior. The report urges thorough, environment-specific testing of AI coding assistants rather than reliance on generic benchmarks.

🔒 DeepSeek collects extensive interaction data — chats, images and videos — plus account details, IP address and device/browser information, and retains it for an unspecified period under a vague “retain as long as needed” policy. The service operates under Chinese jurisdiction, so stored chats may be accessible to local authorities and have been observed on China Mobile servers. Users can disable model training in web and mobile Data settings, export or delete chats (export is web-only), or run the open-source model locally to avoid server-side retention, but local deployment and deletion have trade-offs and require device protections.

🚀 Amazon Bedrock has expanded regional access to several foundation models, adding DeepSeek-V3.1, OpenAI open-weight models (20B, 120B), and multiple Qwen3 variants. The update makes DeepSeek-V3.1 and Qwen3 Coder-480B available in US East (Ohio) and Asia Pacific (Jakarta), and brings OpenAI open-weight and additional Qwen models to US East (Ohio), Europe (Frankfurt), and Asia Pacific (Jakarta). Customers can deploy these models locally to meet data residency needs, reduce latency, and enable faster AI-powered experiences.

🔍 DeepSeek-V3.1 is now available as a fully managed foundation model in Amazon Bedrock, offering an open-weight option designed for enterprise deployment. The model supports a selectable 'thinking' mode for step-by-step analysis and a faster non-thinking mode for quicker replies, with improved multilingual accuracy and reduced hallucinations. Enhanced tool-calling, transparent reasoning, and strong coding and analytical performance make it well suited for building AI agents, automating workflows, and tackling complex technical tasks. DeepSeek-V3.1 is available in US West (Oregon), Asia Pacific (Tokyo, Mumbai), and Europe (London, Stockholm).

🧭 Villager, an AI-native penetration testing framework developed by Chinese group Cyberspike, has reached nearly 11,000 downloads on PyPI just two months after release. The tool integrates Kali Linux utilities with DeepSeek AI models and operates as a Model Context Protocol (MCP) client to automate red team workflows. Researchers at Straiker reported that Villager can spin up on-demand Kali containers, automate browser testing, use a database of more than 4,200 prompts for decision-making, and deploy self-destructing containers — features that lower the barrier to sophisticated attacks and raise concerns about dual-use abuse.

⚠ Villager is an AI-native red-teaming framework from a shadowy Chinese developer, Cyberspike, that has been downloaded more than 10,000 times in roughly two months. The tool automates reconnaissance, exploitation, payload generation, and lateral movement into a single pipeline, integrating Kali toolsets with DeepSeek AI models and publishing on PyPI. Security firms warn the automation compresses days of skilled activity into minutes, creating dual-use risks for both legitimate testers and malicious actors and raising supply-chain and detection concerns.

🔒 In January 2025 Wiz Research discovered a publicly accessible ClickHouse database belonging to Chinese AI firm DeepSeek, exposing over one million log streams that included chat histories and secret keys. The issue was reported and quickly closed, but the event highlights how misconfigurations and human error can expose sensitive data. To reduce risk, organisations should adopt least-privilege access, deploy DLP solutions, classify high-risk data and provide ongoing staff training.

🧠 In episode 66 of The AI Fix, hosts Graham Cluley and Mark Stockley walk listeners through a rapid-fire roundup of recent AI developments, from a ChatGPT prompt that produced an inaccurate anatomy diagram to a controversial Stanford sushi hackathon. They cover a Google Gemini bug that generated self-deprecating responses, criticisms that gave DeepSeek poor marks on existential-risk mitigation, and a debunked pregnancy-robot story. The episode also celebrates a genuine scientific advance: a team of AI agents that designed novel COVID-19 nanobodies, and considers how unusual collaborations and growing safety work could change the broader AI risk landscape.