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DeepSeek, Alibaba and Chinese AI Firms Extract Billions of Tokens From U.S. AI Models

NSA, CISA and FBI advisory AA26-251A accuses DeepSeek, Alibaba and four other Chinese AI firms of industrial-scale distillation of US frontier models.

Joint advisory AA26-251A from NSA, CISA and FBI accuses DeepSeek, Alibaba, Moonshot AI, MiniMax, StepFun and Z.AI of extracting billions of tokens from Claude, GPT, Gemini and Grok variants since at least late 2024, likely with Chinese government awareness. Campaigns allegedly used API proxy 'transfer stations', account pools, metadata sanitization and prompt injection to harvest reasoning, coding, agentic and reinforcement-learning capabilities, with techniques mapped to MITRE ATLAS. DeepSeek's R1 and V3 and Alibaba's Qwen families reportedly trained on harvested outputs, and DeepSeek's $5.6 million training-cost claim is disputed as excluding distilled data value. Agencies urge anomaly monitoring, output alteration for suspected extractors, and intelligence sharing across vendors, clouds and aggregators.

GBHackers · 7d agoAI safety & security in the wild1· 1 read

Threat Actors Are Posing as OpenAI, Anthropic and DeepSeek to Target Credentials and Secrets

GreyNoise observes scanners spoofing OpenAI, Anthropic, and DeepSeek crawler user agents to hunt leaked credentials and secrets.

GreyNoise is observing automated scanners that pose as the web crawlers of OpenAI, Anthropic, DeepSeek, and Fortune 500 companies. The scanners use forged user agents while requesting files where misconfigured web servers frequently leak secrets and credentials. This activity abuses trust in AI crawler traffic to discover exposed credentials for follow-on attacks.

GreyNoise · 20d agoExploit / PoC in the wild

DeepSeek launching v4.1 flash cheaper and more capable than v4 pro

DeepSeek will launch V4.1 Flash around September 10, 2026, claiming it outperforms V4 Pro on performance, cost, and speed while routing Pro traffic to it.

DeepSeek announced V4.1 Flash, launching around September 10, 2026, stating it surpasses V4 Pro across performance, cost, speed, and task completion time. After launch and before V4.1 Pro ships, all Pro requests will be routed to Flash and billed at Flash pricing. Off-peak prices are $0.003 for input cache hits, $0.15 for cache misses, and $0.60 for output, with peak-hour rates doubled.

Six Chinese AI firms accused of aggressively copying US frontier models

NSA, CISA, and FBI accuse DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI of industrial-scale distillation of US frontier models via API abuse.

A joint NSA, CISA, and FBI release alleges six Chinese AI firms have extracted capabilities from US frontier models, including Claude, GPT, Gemini, and Grok, since at least late 2024, likely with Chinese government awareness. Tactics include bulk procurement of premium subscriptions with fraudulent accounts, proxy routing to evade geo-restrictions, and prompt injection to force models to reveal hidden chain-of-thought reasoning. Agencies recommend stronger identity verification, monitoring of anomalous usage, and quietly downgrading or adding noise to responses for suspected distillers, while warning these mitigations could frustrate legitimate users.

Ars Technica · AI · 7d agoAI safety & security in the wild

Chinese AI firms are siphoning capabilities from American models, CISA warns

CISA, NSA and FBI warn Chinese AI firms including DeepSeek and Moonshot AI extracted billions of tokens from US frontier models via distillation campaigns.

A joint CISA, NSA and FBI advisory says China-based firms including DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z.AI have run industrial-scale knowledge distillation campaigns against US frontier models such as Claude, GPT, Gemini and Grok since at least late 2024, likely with Chinese government knowledge. The campaigns used gray-market API proxies called transfer stations, premium account pools and traffic routing to bypass restrictions, evade safeguards and exfiltrate billions of tokens used to train models like DeepSeek R1/V3 and Kimi. The agencies challenge DeepSeek's reported $5.6 million training cost and recommend identity verification, usage monitoring, response variation, differential privacy and indicator sharing as defenses.

Help Net Security · 7d agoAdvisory in the wild1

nex-agi/Nex-N2.5-Pro — new model trending #30 on Hugging Face

Nex-AGI launches Nex-N2.5 agentic model family (mini/Pro/Max), with Max built on a 1.6-trillion-parameter MoE foundation.

Nex-AGI introduced Nex-N2.5, a next-generation family of agentic models in three sizes (mini, Pro, Max) focused on long-horizon agentic tasks including computer use, web browsing, and autonomous program execution. Nex-N2.5-Max is built on a 1.6-trillion-parameter text-only Mixture-of-Experts foundation, marking the company's first complete post-training effort at trillion-parameter scale. Weights will be released open-source on Hugging Face and ModelScope, with hosted access via OpenRouter. Benchmark comparisons against Claude Opus 5, GPT-5.6 Sol, Kimi-K3, GLM-5.3, DeepSeek-V4-Pro-0813, and Qwen3.8-Max show competitive scores on Terminal-Bench 2.1 and SWE-Bench Pro, though weights were listed as "coming soon" at publication.

Hugging Face trending models · 8d agoModel release1

nex-agi/Nex-N2.5-mini — new model trending #30 on Hugging Face

Nex-AGI releases Nex-N2.5 agentic model family (mini, Pro, Max) with a 1.6-trillion-parameter MoE Max, open weights, and hosted access via OpenRouter.

Nex-AGI launched Nex-N2.5, a family of agentic models in mini, Pro, and Max sizes, with the Max version built on a 1.6-trillion-parameter text-only Mixture-of-Experts foundation and the company's first complete post-training effort at trillion-parameter scale. The models target long-horizon computer use, web browsing, and visually grounded agentic tasks, with expanded agent training environments. Reported benchmarks include Max scoring 86.1 on Terminal-Bench 2.1 and 65.7 on SWE-Bench Pro, trailing Claude Opus 5. Weights are being released openly on Hugging Face and ModelScope, with hosted access through OpenRouter.

Hugging Face trending models · 8d agoModel release1

Chinese Hackers Use AI Agents in Multi

China-linked campaign used the SecFlow AI-agent framework (Claude, Qwen, DeepSeek) to automate intrusions against government targets in Taiwan, Indonesia, China and Vietnam.

Hunt.io documented a second China-linked campaign wiring commercial AI models into live cyberespionage, reconstructing the SecFlow orchestration system from five accidentally exposed open directories. Targets included Taiwan's Kuomintang Party archives, Indonesia's Ministry of Foreign Affairs, mainland Chinese government and education systems, and Vietnamese industrial hosts. The most extensive compromise hit a Fengtai District government Office Automation environment, yielding LSASS and registry hive theft, 822 user records and 1.28GB of attachments including patient health data. Tooling included a GLUTTON webshell hiding payloads in PNG pixels via steganography and a fake MySQL deserialization service for client-side code execution.

Security Affairs · 12d agoThreat actor in the wild

[AINews] 10% worse, 100x cheaper, 10000x faster: Why Simulation is taking over

Latent Space argues AI training pipeline stages—rewards, data, teachers, curricula, environments—are flipping from human-made to model-made simulation.

Latent Space's AINews essay traces how each component of AI training has turned synthetic since 2022: reward models (InstructGPT, RLAIF), synthetic pretraining data (Microsoft Phi, NVIDIA Nemotron-4 340B), model teachers (Alpaca, DeepSeek-R1 distillation), and self-generated curricula (Self-Rewarding Language Models, SPIN). In 2026 it highlights Karpathy's autoresearch loop—700 experiments yielding 20 kept improvements, cutting GPT-2 training time from 2.02 to 1.80 hours—and Z.ai's GLM-5.3 fully synthetic RL environment, judging, and verification stack. It frames these shifts as 'simulation': 10% worse but 100x cheaper and 10,000x faster than human equivalents.

Latent Space · 25d agoAI industry

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space · 1d agoAI safety & security

Anthropic Says Seven China-Based AI Labs Ran Industrial-Scale Claude Distillation Attacks

Anthropic disrupted industrial-scale unauthorized Claude distillation by seven China-based AI labs, including Alibaba, DeepSeek, Moonshot, and Z.ai.

Anthropic identified and disrupted six illicit distillation campaigns since February 2026 run by seven China-based labs: Alibaba, Moonshot, DeepSeek, Z.ai (Zhipu), MiniMax, Xiaomi, and SenseTime. The largest, GTG-16005, involved 151 million exchanges targeting Claude Opus 4.6/4.7 chain-of-thought transcripts, peaking at roughly 3 million exchanges per day from more than 3,500 fraudulent accounts. Labs used proxy/relay services with fictitious identities, fake or stolen credit cards, harvested API keys, and purchased conversation transcripts from third-party resellers. Anthropic is countering by banning reseller accounts, summarizing internal reasoning before responding, and introducing preserved thinking in Fable 5.1, which encrypts reasoning and prevents context edits before it.

US Agencies Warn Chinese AI Firms Are Extracting Advanced AI Models

NSA, CISA, and FBI accuse six Chinese AI firms including DeepSeek and Alibaba of industrial-scale distillation of US frontier models.

A joint NSA, CISA, and FBI advisory alleges DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI extracted billions of tokens across millions of requests from US frontier models including Claude, GPT, Gemini, and Grok since at least late 2024. DeepSeek reportedly ran an organized campaign against Claude, GPT, and Gemini between late 2024 and mid-2025 that aided R1 and V3 development, including chain-of-thought reasoning extraction. Reported techniques included shared premium accounts, gray-market proxy 'transfer stations,' automated failover, and prompt injection that made Claude Code believe it was a MiniMax product. The advisory recommends detection signals such as 24/7 multi-IP account usage and covertly serving degraded responses to suspected distillers.

Security Affairs · 7d agoAI safety & security in the wild1

U.S. Agencies Accuse China AI Firms of Distilling Claude, GPT, Gemini, and Grok

NSA, CISA and FBI accuse Chinese AI firms including DeepSeek of industrial-scale distillation of Claude, GPT, Gemini and Grok since late 2024.

A joint bulletin from the NSA, CISA and FBI accuses China-based AI firms including DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun and Z.AI of systematic, industrial-scale distillation of U.S. frontier models. The agencies say billions of tokens were extracted from Claude, GPT, Gemini and Grok variants since at least late 2024 through APIs, cloud relays, obfuscated accounts and gray-market proxies, likely with Chinese government backing. Firms allegedly shared premium subscriptions across developer teams and used chain-of-thought extraction and automated failover to evade blocks. Mitigations include subtly altering responses to suspected distillers and correlating activity across providers, clouds and aggregators.

The Hacker News · 7d agoAI policy

Feds accuse China of ‘systematic’ distillation of U.S. AI models

NSA, CISA, and FBI jointly accuse Chinese AI firms including DeepSeek and Moonshot AI of industrial-scale distillation of US frontier models.

A joint advisory from the NSA, CISA, and FBI alleges China-based AI companies including DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI have systematically extracted capabilities from US frontier models since at least late 2024. The companies allegedly spent billions of tokens across millions of requests against Claude, ChatGPT, Gemini, and Grok, routing traffic through multiple accounts, platforms, proxies, and third-party aggregators to evade detection. Moonshot AI allegedly distilled 18 US models, including Anthropic's most advanced model, to train its Kimi-K2 and Kimi K3 models.

CyberScoop · 8d agoAI policy

[AINews] Fal’s H3 Max Live breaks the infinite videogen barrier

Fal post-trained MiniMax H3 into a 'Max' variant with 35x-faster inference, enabling faster-than-realtime AI video generation and infinite streams.

Fal post-trained MiniMax's H3 model into a 'Max' variant and optimized it for its in-house inference engine, achieving roughly 35x the speed of the official endpoint. The optimization enables faster-than-realtime video generation, demonstrated by an infinite interactive AI-generated stream productized by levels.io. The roundup also notes Meta Muse Code's general availability with an SDK, open DeepSeek-V4-Flash-Vision-Exp weights, GLM-5.3-Flash's strong agentic cost/performance rankings, and Tencent's 770B-parameter Hy4 Preview MoE with 49B active parameters.

Latent Space · 15d agoAI industry

NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

NVIDIA's Vera Rubin NVL72 debuts in MLPerf Inference v6.1 with up to 3.7x higher throughput than GB300 NVL72 and 99% scaling efficiency at 288 GPUs.

In its first MLPerf Inference preview submission, NVIDIA's Vera Rubin NVL72 achieved up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1. A 288-GPU GB300 NVL72 submission across four racks reached 99% scaling efficiency on the DeepSeek-R1 offline benchmark. Software optimizations delivered up to 1.6x gains over v6.0, leveraging TensorRT-LLM, vLLM, Dynamo, disaggregated serving, and NVFP4 precision.

NVIDIA Blog · 9h agoAI industry 2 sources

Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery

Architecture explainer separates agent harnesses, frameworks, and MCP by which layer owns the loop, state, permissions, and recovery.

The article distinguishes agent harnesses (OpenAI Codex, Claude Agent SDK), which own the execution loop, sandbox, permission model, and recovery; frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework), which supply composable primitives; and MCP, a stateless JSON-RPC wire protocol governed by the Linux Foundation's Agentic AI Foundation since December 2025. An ownership matrix maps the execution loop, state, tool transport, permissions, recovery, sandboxing, and multi-agent orchestration to each layer. The 2026-07-28 MCP specification made the protocol fully stateless, retiring the initialize handshake and session headers.

MarkTechPost · 2d agoAI research1

Detect and disrupt AI-themed attacks with Microsoft Defender

Microsoft Threat Intelligence reports criminal campaigns impersonating ChatGPT, Copilot, Claude, and DeepSeek in phishing, AiTM, and malvertising attacks reaching 100,000 emails daily.

Microsoft Threat Intelligence observed a growing set of campaigns that abuse trust in popular AI brands: a ChatGPT-themed phishing campaign sent up to 100,000 emails in one day to steal payment card data, and a Claude-themed campaign used adversary-in-the-middle techniques to harvest credentials and access tokens. Other campaigns included malvertising for a fake AI Windows plugin delivering the Vidar stealer and fraudulent DeepSeek installers distributed via GitHub. Initial access broker Storm-3075 used AI-themed malvertising to distribute payloads for multiple downstream actors, and Microsoft notes the AI services themselves were not compromised. Microsoft also details Defender protections such as Safe Links, Safe Attachments, and attack disruption against these multi-stage lures.

Microsoft Security Blog · 6d agoPhishing & fraud in the wild1