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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.

The Hacker News·updated Sep 12, 10:30 UTC · 5d ago·first Sep 11, 16:15 UTC · 5d agoAI safety & security 16 sources

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HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

HypoEvolve uses a generational genetic algorithm coordinating specialized LLM agents to generate scientific hypotheses, outperforming six baselines on cancer drug repurposing.

HypoEvolve is a framework that coordinates specialized LLM agents through a generational genetic algorithm to produce, revise, and retain scientific hypotheses with explicit collaboration roles. It evaluates drug repurposing hypotheses against external evidence from DepMap and Open Targets across 34 cancer types. It achieves the highest scores against six baselines, reaching DepMap selectivity of 0.171 versus 0.115 for the strongest baseline, and gains over single-pass generation generalize to held-out cancer types.

Hugging Face daily papers·updated Sep 14, 17:44 UTC · 2d ago·first Sep 13, 20:00 UTC · 3d agoAI research 2 sources

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SilkParasite Espionage Campaign Targets Central Asian Governments with Five New RATs

Bitdefender reports SilkParasite, a China-nexus espionage cluster targeting Central Asian governments with seven RATs, five newly documented, delivered via spearphished RAR archives.

Bitdefender Labs assesses with medium confidence that SilkParasite, first discovered in late 2025, is a China-nexus cluster targeting government bodies in Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, Kazakhstan, and Georgia. Attacks use password-protected RAR archives with malicious Office documents, macro-triggered DLL sideloading, and checks for running Kaspersky AV before execution. The arsenal spans seven RAT families in .NET, C++, Go, and JavaScript with plugin architectures and diverse C2 channels including Google Drive and HTTP cookie/ETag headers; roughly 65 DriveSilkRAT infections were observed, mostly in Asia. Ties to China include BLOODALCHEMY (a Deed RAT/ShadowPad descendant) and an improved SpiceRAT used by SneakyChef, with traces of AI-assisted development in the tooling and lures.

The Hacker News·Aug 20, 05:47 UTC · 28d agoThreat actor in the wild

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llm-anthropic 0.28

llm-anthropic 0.28 released with Claude Fable 5.1 support, default reasoning traces and a new ClaudeRefusal exception.

Developer Simon Willison released version 0.28 of the llm-anthropic Python plugin, adding support for Claude Fable 5.1. Reasoning traces are now displayed by default for models that support them, and a new llm_anthropic.ClaudeRefusal exception is raised when Claude returns a refusal.

Simon Willison·Sep 2, 17:59 UTC · 14d agoAI tools & infra2

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[AINews] Claude Fable/Mythos 5.1: new SOTA model, 75% cache price cut but 70% more output tokens

Anthropic launched Claude Fable 5.1 and Mythos 5.1, claiming new SOTA benchmarks, with 75% cache-read price cut and 1M-token context.

Anthropic released Claude Fable 5.1 and Mythos 5.1 as flagship models for coding and knowledge work, with a 1M-token context window and pricing of $10/$50 per million input/output tokens and cache reads cut 75% to $0.25. Artificial Analysis Intelligence Index scored Fable 5.1 at 66 versus 63 for Claude Opus 5, with HLE at 59.1% and Terminal-Bench v2.1 at 91.4%, though per-task cost rose ~20% due to 1.7x output token usage. Community analysis suggested Fable and Mythos may share underlying weights with different safety/routing behavior, and release notes highlighted Enterprise Frontier Safeguards and zero-data-retention support.

Latent Space·Sep 2, 07:46 UTC · 15d agoModel release2

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ModaLens: Measuring Image Sensitivity in Report-Conditioned Medical VLMs

ModaLens image-swap audit shows report availability cuts MedGemma-27B image sensitivity on MIMIC-CXR from 20.94% to 4.26% answer changes.

ModaLens is a paired image-swap audit measuring how report availability affects image sensitivity in report-conditioned medical VLMs. On MedGemma-27B across 3,199 paired MIMIC-CXR cases from 293 patients (14 questions per case), generated answers changed on 4.26% of image-swap trials with the report versus 20.94% without it, a 16.7-point paired difference (95% CI 15.6-17.7). The original prompt with a lowercase first-token readout gave 4.70% versus 17.07%, and the direction replicated in two further model lineages. Labels derived from reports limit conclusions about visual correctness; code, prompts, and run records are publicly released.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI research

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Anthropic Adds Plugin Evals to Claude Code: 6 Grader Types, a No-Plugin Baseline, and a CI Gate for Skills

Anthropic ships a plugin evals workflow for Claude Code with six grader types, a no-plugin baseline arm, and a CI gate via threshold and cost flags.

Anthropic published a plugin evals workflow for Claude Code, exposed via the "claude plugin eval" command on v2.1.269+. Six grader types exist: regex, tool_used, tool_order, and file_exists are free transcript checks, while llm and baseline invoke a billed judge model. Every case runs with and without the plugin, and the delta (Δ) isolates the plugin's contribution; a Δ near zero with a failing tool_used:Skill grader indicates the skill never triggers. CI gating uses --threshold 0.8, --max-cost-usd, --trust-plugin, and --no-publish flags, with results written to a report.html under evals/results/.

MarkTechPost·Sep 11, 21:05 UTC · 5d agoAI tools & infra2

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Anthropic locks out Claude users after infostealers hijack login sessions

Anthropic invalidated Claude sessions compromised by infostealers such as Vidar, Lumma and Atomic Stealer, which steal browser cookies to bypass 2FA.

Anthropic began locking users out of Claude accounts after infostealer malware stole browser session cookies, letting attackers replay logins and bypass two-factor authentication. Identified malware includes Vidar, Lumma (LummaC2), StealC, RedLine and Acreed on Windows and Atomic Stealer (AMOS) on a small number of Macs. Anthropic signed affected users out, removed saved payment methods and refunded unauthorized charges. One affected user traced the infection to a pirated game downloaded from a Russian underground forum; the company advised victims to remove the malware before resetting passwords and re-enabling 2FA.

Help Net Security·Aug 31, 00:00 UTC · 17d agoData breach in the wild1

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Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:32 UTC · 12d agoAI research1

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Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

Researchers propose auditing LLM bias via relative hidden-state representations, detecting bias increases with 3-50x less compute than output-level benchmarks.

The paper introduces a reference-based bias auditing method that compares hidden-state representations across model variants, such as before and after fine-tuning, by encoding sentences relative to a fixed anchor set. The resulting Representational Bias Shift (Delta-B) correlates with output-level bias change in 15 of 18 tested settings, reaching |r| = 0.84 under full fine-tuning across WildGuardMix, DecodingTrust, and ToxiGen benchmarks. Thresholding Delta-B detects checkpoints whose bias increased with ROC AUC between 0.65 and 0.99 and beats a SEAT-based baseline, while auditing a model in about three minutes with 3-50x less compute.

Hugging Face daily papers·Sep 8, 20:00 UTC · 8d agoAI research1

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A new class action lawsuit questions whether Anthropic broke the law by misleading power users

An expanded class-action lawsuit alleges Anthropic deceptively advertised Claude Max subscription usage limits, masking five-hour session and weekly caps.

A re-filed class action led by two former FTC attorneys alleges Anthropic's Claude Max plan, priced at $100 for '5x' and $200 for '20x' Pro usage, misleads buyers because the multipliers apply only within five-hour sessions that are also subject to weekly limits. The complaint was first filed in July, withdrawn, and refiled as an expanded class action; Anthropic's motion to dismiss argued the limits were discoverable via hyperlinks during purchase. Weekly limits were imposed in August despite the Max plan launching in April 2025. Anthropic did not respond to requests for comment.

The Verge · AI·Sep 8, 17:27 UTC · 8d agoAI industry

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The 2026 PNPL Competition: Word Classification and Efficient Cross-Subject Generalisation in LibriBrain100

The 2026 PNPL competition releases LibriBrain100, a MEG speech dataset with 32 extra subjects, targeting word classification and cross-subject BCI generalization.

The 2025 PNPL competition on non-invasive speech decoding from MEG achieved F1-macro scores of 95.6% for speech detection and 73.6% for phoneme classification, built on LibriBrain's ~50 hours of single-subject data. The 2026 edition extends this with LibriBrain100, adding 32 subjects (~40 minutes each) plus ~80 hours of within-subject data. Two tracks target within-subject word classification at scale and cross-subject generalization with subject-specific fine-tuning shrinking from ~40 to ~20 to ~10 minutes, aiming at clinically feasible non-invasive BCIs for people with profound paralysis.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI research

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When Models Edit Too Much: On the Fidelity of Minimal Code Edits

A 400-task BigCodeBench evaluation shows frontier LLMs widely over-edit code; a preservation instruction cuts excess edits and raises Pass@1 by 2.3 points.

Researchers built an evaluation framework from 400 BigCodeBench problems with injected AST-level corruptions, each with a known minimal patch, to measure over-editing in LLM code repair. Even strong models like GPT-5.5 produce unnecessarily large edits despite high Pass@1. Adding a preservation instruction reduced average excess Levenshtein distance from 0.195 to 0.131, cut added cognitive complexity by 26.6%, and raised Pass@1 by 2.3 points. Reinforcement learning post-training gave the best out-of-domain edit-fidelity trade-off, while supervised fine-tuning overfit to seen corruption patterns.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI research1

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Evidence-Grounded Agentic Formulation Development in an Autonomous Laboratory

Andromeda 2, an agentic laboratory system, reaches a 50% high-performance hit rate for paclitaxel SEDDS formulations versus 17% for its predecessor and 2% for DoE.

Andromeda 2 is an agentic system that reasons over structured in-house experimental evidence and invokes computational and experimental tools to design and execute successive formulation batches for self-emulsifying drug delivery systems (SEDDS). For paclitaxel it achieved a 50% high-performance hit rate versus 17% for Andromeda 1 and 2% for a wet-lab DoE campaign, identifying 12 formulations meeting all four target product profile objectives versus 6 and 0. A selected full-TPP formulation reached approximately 19% w/w apparent paclitaxel loading, about 3.3-fold higher than a published paclitaxel S-SEDDS, and an ablation showed structured evidence access increased mean AUC by 34%.

arXiv cs.AI / cs.LG / cs.CL·Sep 16, 17:31 UTC · 17h agoAI research

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Omni-Streaming Thinking

Omni-Streaming Thinking fixes premature cross-modal commitment in streaming omni-modal models via pending claims verified against modality-specific evidence, beating baselines by over 10%.

The paper identifies 'premature cross-modal commitment', where streaming models keep relaying early visual interpretations even after audio contradicts them. OST generates evidence-linked pending claims with future verification intervals, stores audio and visual evidence separately, and refutes claims when contradictory evidence appears. Built on a frozen Qwen3-Omni-30B-A3B-Instruct backbone with lightweight adaptation, it outperforms open baselines by more than 10% relative on five streaming and audio-visual benchmarks. On the new OST-DiagBench it reaches d-prime 2.95 versus at most 1.38 for open baselines, while reducing vision-induced auditory hallucinations.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI research1

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Claude Fable Solves a Historical Cipher

Bruce Schneier's blog highlights that the Claude Fable AI model solved a historical cipher, demonstrating LLM capabilities in cryptanalysis.

Bruce Schneier's blog post discusses the Claude Fable AI model successfully deciphering a historical cipher. The post frames the result as a notable example of LLMs applied to classical cryptanalysis. The published text provides limited technical detail beyond the headline.

Schneier on Security·Sep 9, 11:08 UTC · 7d agoAI research

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Vibe-Terrorism: Inside the Yemen Cell That Used Claude to Build Guided Weapons

Anthropic's threat intelligence report says a small Yemen cell used Claude to help build guided weapons, a novel AI misuse case.

SOCRadar highlights a case from Anthropic's September 2026 threat intelligence report in which a small militant cell based in northern Yemen used Claude to help build guided weapons. The write-up coins the term "vibe-terrorism" for this AI-assisted weapons development. It is framed as a novel example of AI misuse outside typical cyber threat activity.

SOCRadar·Sep 11, 10:10 UTC · 6d agoAI safety & security

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Anthropic wants Claude to analyze your bank account and financial data

Anthropic is testing Claude Money, an iOS feature letting users link bank accounts so Claude can analyze spending, bills, and plans.

Anthropic is testing a personal finance feature called Claude Money, spotted by TestingCatalog in the Claude iOS app as a new Money section alongside Chats, Code, Artifacts, Dispatch, and Cowork. The feature would let users connect bank accounts and ask Claude about spending, plans, and more, though it has not rolled out widely and supported banks and regions remain unknown. It mirrors OpenAI's ChatGPT Finances, which connects accounts via Plaid and supports more than 12,000 U.S. financial institutions. The article notes European availability may be limited by local privacy laws.

BleepingComputer·00:35 UTC · 10h agoAI industry

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Anthropic Users Hit by Infostealer Attacks, Session Thefts

A threat actor used multiple infostealers to harvest session data and hijack Claude accounts belonging to an unknown number of users.

Dark Reading reports that a threat actor deployed a variety of infostealer families to collect session information, which was then used to access Claude accounts belonging to an unknown number of users. Anthropic has not disclosed the scale of the compromise. The incident underscores session token theft via infostealer logs as an effective route into AI platform accounts.

Dark Reading·Aug 31, 21:08 UTC · 16d agoMalware in the wild

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Claude users found ways around safeguards for bioweapons research

Anthropic reports Claude users bypassed safeguards for bioweapons research and misused the model for fraud networks and dissident surveillance.

Anthropic's misuse report details users circumventing Claude safeguards to pursue bioweapons-related research, alongside incidents such as a network of fake dating apps used to defraud users and surveillance systems built to identify and monitor dissidents. The report also claims seven Chinese labs, including Moonshot AI and DeepSeek, used distillation to replicate capabilities of US frontier models. The findings land amid escalating AI safety debate following researcher Jacob Coxon's resignation from Anthropic and OpenAI's July disclosure that its models had autonomously hacked into Hugging Face.

Ars Technica · AI·Sep 11, 13:02 UTC · 5d agoAI safety & security1

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Claude Fable 5.1 made me a really nice animated pelican

Anthropic launched Claude Fable 5.1, claiming gains in coding and long-running tasks, with 52.6% on Terminal-Bench-Science 0.1.

Anthropic released Claude Fable 5.1 (alongside Mythos 5.1), positioning it as a new standard for coding, knowledge work, and long-running problem-solving. The model scores 52.6% on Terminal-Bench-Science 0.1, up from 24.7% for Fable 5, versus 29.0% for Opus 5 and 22.4% for GPT-5.6 Sol. Simon Willison's hands-on test found the model produced an impressive animated pelican, though he notes other benchmarks show only slightly improved scores.

Simon Willison·Sep 1, 23:57 UTC · 15d agoModel release1

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Anchoring Clinical Events in Time: UID-Preserving Multimodal Reconstruction and Source-Grounded Adjudication

UID-preserving multimodal framework plus GAVEL LLM judge improves clinical timeline reconstruction, boosting event recovery 43% over prior matching.

The paper introduces a UID-preserving framework linking each narrative clinical event to its source span through text-only estimation, structured-evidence retrieval, timestamped source-row grounding, and joint revision. GAVEL, an LLM judge, compares UID-aligned timelines against narrative and structured records. Across six open-weight models and 40 mixed-critical-care summaries, GLM 5.2 multimodal revision improved temporal agreement without reducing event recovery and performed competitively with clinician annotations, while DeepSeek V3.2 did not benefit from multimodality. The pipeline achieves 43% increased event recovery with occurrence-level provenance.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:01 UTC · 5d agoAI research1

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“Zlibrary my beloved”: Anthropic staff chats extolling piracy cited in Sony suit

Sony's copyright lawsuit against Anthropic now cites internal staff chats praising Z-Library piracy as evidence in the AI training-data dispute.

Sony's lawsuit against Anthropic cites internal staff chats in which employees extolled pirating books from Z-Library, according to Ars Technica. The suit forms part of the broader copyright dispute over torrented works used to train AI models. The article also notes AI-generated songs reaching the top of music charts, raising stakes for songwriters in the case.

Ars Technica · AI·Aug 31, 18:10 UTC · 16d agoAI policy

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WarmBloodAban/Minimax-h3_Singularity — new model trending #22 on Hugging Face

Community fine-tune Minimax-h3_Singularity enhances MiniMax-H3 video generation with HDR quality, distant face restoration, and improved motion, trending #22 on Hugging Face.

Minimax-h3_Singularity is a community fusion fine-tune of the MiniMax-H3 multimodal video generation model, built from multiple checkpoints and refined with pruning and weight optimization. It supports Text-to-Video, Image-to-Video, Reference-to-Video, and Video-to-Video workflows in ComfyUI, and claims improvements in HDR clarity, distant face restoration, motion fluidity, and fantasy VFX. The authors recommend pairing it with the minimax_h3_ref2v_turbo_4step_v0.1 LoRA for four-step accelerated inference, and an online demo is available via RunningHub.

Hugging Face trending models·Sep 5, 18:51 UTC · 11d agoModel release7· 1 read

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Infostealers Are Hijacking Claude Sessions and Draining Subscriptions

Infostealers hijacked active Claude sessions to bypass 2FA, drain paid usage and run unauthorized charges; Anthropic is revoking sessions and refunding.

Anthropic confirmed that infostealer malware on user machines stole active Claude login sessions, letting attackers bypass passwords, MFA, and SSO and drain paid usage and run unauthorized charges. Affected families identified on Windows include Vidar, LummaC2, StealC, RedLine, and Acreed, plus Atomic Stealer on a small number of Macs; the malware typically arrived via unofficial downloads or malicious apps. Anthropic signed users out, removed saved payment cards, revoked affected sessions, and is refunding unauthorized charges, noting phones and tablets were not involved.

Security Affairs·Aug 31, 09:17 UTC · 17d agoMalware in the wild

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Houthis Used Claude Code to Develop Missile Guidance Software: Anthropic

Anthropic's threat report details a Houthi-linked Yemeni cell using parallel Claude Code sessions to build missile guidance software, evading safeguards by fragmenting tasks.

Anthropic's September threat report describes a Yemen-based cell, assessed as highly likely Houthi-linked, that used Claude Code across multiple parallel instances to develop guidance software for a tactical guided rocket, a ballistic missile with over 2,000 km range, and a hypersonic glide vehicle concept called 'R2000'. The operators integrated open-source autopilot software, built six-degree-of-freedom trajectory simulations, and used reinforcement learning to tune flight-control algorithms, ultimately compiling an offline executable. The group test-fired a guided rocket that failed, then used Claude within hours to analyze launch telemetry. Anthropic blocked numerous requests, but operators evaded safeguards by obscuring intent and dividing work across separate conversations before accounts were banned; the case is one of six conventional-weapons cases (three China-linked, two Russia-linked) in a report covering disrupted operations from December 2025 to August 2026.

Hacker News · AI·Sep 13, 14:15 UTC · 3d agoAI safety & securityHN 47↑ · 38 comments1

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