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FBI Seizes China-Linked Hacking Platforms QScan and QTRouter Used Against Critical Infrastructure

FBI seizes China-linked QScan and QTRouter hacking platforms used by QTFY to obfuscate intrusions against US federal agencies.

The DOJ and FBI seized domains hard-coded into QScan and QTRouter, two platforms operated by China-based Nanjing Xinjiuwei Network Technology Company on behalf of state-sponsored group QTFY. QScan automatically infected thousands of IoT devices which were added to QTRouter, an obfuscation network routing malicious traffic through compromised and proxy devices outside China. Targets included NASA, the Federal Reserve, Departments of Energy, Justice, and HHS, NIH, and the US Senate, exploiting flaws in Fortinet SSL-VPN, Citrix ADC, Microsoft Exchange, F5 BIG-IP, Log4j, and others.

Security Affairs·Aug 26, 17:33 UTC · 21d agoThreat actor in the wild

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GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay

GPU-CFR compiles counterfactual regret minimization into static dataflow with CUDA Graph Replay, achieving 29.8-80.4x speedups over prior GPU solvers.

The paper presents a compiler and runtime that turns any fixed game's CFR iteration into a static dataflow graph of flat arrays and precomputed indices, cutting framework operations by up to 18.1x. Because shapes and buffer addresses never change, CUDA Graph Replay records the iteration once and replays it with a single launch. On one A100 across an eight-game suite, GPU-CFR runs 29.8-80.4x faster than the fastest prior GPU CFR and 14-258x faster than the CPU implementation LiteEFG on the four largest games, while reproducing reference iterates bitwise on CPU.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:58 UTC · 6d agoAI research3· 1 read

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FBI Disrupts China-Linked QTFY Infrastructure Used to Steal Data From U.S. Organizations

FBI and Lumen disrupted QTFY's QScan and QTRouter botnet platforms used by Chinese state-sponsored hackers to conceal intrusions into U.S. agencies.

The U.S. DoJ announced court-authorized seizure of domains behind QScan and QTRouter, operated by the Chinese state-sponsored group QTFY and employed by Nanjing Xinjiuwei Network Technology Company. QTFY has been active since May 2018 and targeted NASA, the Federal Reserve, the Department of Energy, DoJ, HHS, NIH, the U.S. Senate, and academic institutions. QScan exploits vulnerable IoT devices, feeding them into QTRouter, an OpenWrt-based proxy obfuscation network likened to an operational relay box (ORB) that masks attack origins. The group exploited zero-days such as Ivanti CSA flaws CVE-2024-8190, CVE-2024-8963, and CVE-2024-9380, plus numerous N-days, and maintained persistence with RATs, web shells, and legitimate credentials.

The Hacker News·Sep 2, 06:26 UTC · 14d agoThreat actor in the wildCVE-2018-13379CVE-2019-10068CVE-2019-19781+10 CVEs

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From 88 lines to 1: Detecting DLL hijacking with Elastic Defend

Elastic condenses 88 lines of detection logic into one Elastic Defend 9.5.0 rule catching the DLL hijacking used by a ClickFix campaign.

The ClickFix campaign side-loads a malicious mscoree.dll next to a signed Microsoft binary and also ships a driver to kill Elastic Endpoint. Elastic rebuilt the DLL as a NativeAOT library, dropped it beside the signed binary, and confirmed that Elastic Defend 9.5.0 flags the load. The post replaces 88 lines of detection logic with a single rule for DLL search-order hijacking.

Elastic Security Labs·Aug 28, 00:00 UTC · 19d agoTools in the wild

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Officials disrupt Chinese espionage operation that hit multiple federal agencies

FBI and DOJ seized QTFY infrastructure, disrupting a Chinese state-sponsored group that compromised federal agencies and critical infrastructure since 2018.

Authorities seized three domains powering QScan and QTRouter, the hacking suite of QTFY, a Chinese government-funded group operating through front company Nanjing Xinjiuwei Network Technology. Targets include the Departments of Energy, Justice, and Health and Human Services, the Federal Reserve, NASA, NIH, financial institutions, defense contractors, utilities, telecoms, and hospitals; the group exploited zero-days in Ivanti, Pulse Secure, Fortinet, Citrix, and others, intruding three DOE national labs in September 2024. QScan carried over 200 proof-of-concept exploits and processed more than two million scanning tasks in a single day in 2024.

CyberScoop·Aug 26, 19:35 UTC · 21d agoThreat actor in the wild1

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PoisonedRefresh: A Fileless Linux Rootkit That Injects PHP Web Shells Into F5 BIG-IP APM Server Memory

Sophos details PoisonedRefresh, a fileless Linux rootkit that injects a memory-resident PHP web shell into F5 BIG-IP APM after exploitation of CVE-2025-53521.

On September 8, 2026, SophosLabs published an analysis of Linux/Agnt-IC (dubbed PoisonedRefresh by ESET) found in compromised F5 BIG-IP Access Policy Manager environments. Initial access leverages CVE-2025-53521, an unauthenticated RCE in BIG-IP APM when an access policy is configured on a virtual server; F5 confirmed exploitation and links the activity to cluster c05d5254, while Shadowserver observed 795 exposed vulnerable endpoints. A first stage hidden in a modified umount binary modifies /usr/sbin/httpd and SELinux configuration and embeds itself in BIG-IP upgrade images for persistence. The second-stage ELF intercepts __libc_start_main, hooks apr_dso_load, and injects a PHP web shell into libphp memory via mmap manipulation, leaving no disk artifacts, and exposes a /bin/bash shell via a local UNIX domain socket instead of a TCP port.

Security Affairs·Sep 9, 08:50 UTC · 7d agoMalware in the wildCVE-2025-53521

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Storm-1175 Replaces Medusa With New StormEncryptor Ransomware

Microsoft reports China-linked ransomware group Storm-1175 switched from Medusa to a new C++ strain, StormEncryptor, likely exploiting N-able flaw CVE-2026-18577.

Microsoft Threat Intelligence reports that the financially motivated, China-linked group Storm-1175 began deploying a new ransomware strain called StormEncryptor on August 2, 2026, replacing its previous Medusa ransomware. StormEncryptor is written in C++, appends the .encrypted extension to files, and drops a !!!README_FIRST!!!.txt ransom note in each scanned directory. Microsoft assesses the group is likely exploiting CVE-2026-18577, an authentication bypass in N-able disclosed on August 2, 2026 and added to CISA's Known Exploited Vulnerabilities catalog the next day. Since 2023, Storm-1175 has exploited more than 16 vulnerabilities in products including Microsoft Exchange, Ivanti, ConnectWise ScreenConnect, JetBrains TeamCity, SimpleHelp, CrushFTP, and GoAnywhere MFT, often moving from initial access to data theft and ransomware deployment within days.

Security Affairs·Aug 13, 08:09 UTC · Aug 13, 2026Ransomware in the wildCVE-2026-18577CVE-2026-1731CVE-2023-21529+15 CVEs1

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OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design

OptiPrime co-designs HE-MPC protocols with hardware acceleration to remove network communication bottlenecks in private DNN inference, beating Cheetah by up to 5.7x.

OptiPrime is a protocol-hardware co-optimization framework for private deep neural network inference based on hybrid homomorphic encryption (HE) and multi-party computation (MPC). It introduces a novel HE protocol for convolutions that reduces the number of transmitted output ciphertexts, addressing the network bottleneck that limits gains from commercial HE accelerators. A lightweight compression system reduces weight plaintext memory traffic by 10x, while a specialized dataflow maximizes on-chip reuse of intermediate ciphertexts. Experiments show up to 5.7x speedup over the Cheetah baseline on CPUs and 4.2x with an accelerator.

arXiv cs.CR·Sep 15, 09:29 UTC · 1d agoResearch

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JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

JustFit MLX runtime serves 200K-token contexts for Qwen3.8-27B on a 24 GiB MacBook via just-in-time state management.

JustFit is an MLX-based inference runtime combining KVExec for compressed KV execution, PhaseSwap for component residency, and StateTrans for state-preserving serving transitions, independent of weight quantization. On a 24 GiB M4 Pro MacBook running Qwen3.8-27B MXFP4, it completed 196,608 input and 16,384 output tokens, raising single-request context from the mlx-vlm baseline's 30,720 positions to 212,992 (6.93x). Performance tests show 19.11 tokens/s on a 32K-input probe with a 16,374 MiB median peak footprint, and the runtime answered 29 of 30 AIME 2026 problems correctly.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:15 UTC · 1d agoAI research

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MIT creates method to force AI to comply with safety rules

MIT researchers published HardFlow, a method enforcing hard safety constraints on flow-matching generative models' final outputs without retraining.

MIT researchers led by Zeyang Li and Navid Azizan developed HardFlow, a trajectory-optimization method that enforces strict, non-negotiable constraints on flow-matching generative models by checking rule satisfaction only at the final generation step. Published in IEEE TPAMI, it outperformed six rival projection and guidance methods on four simulated benchmarks including D3IL robotic manipulation, Maze2D, physical process control, and image editing. All results are simulation-only, with no independent reproduction yet reported.

Hacker News · security·Sep 14, 16:18 UTC · 2d agoAI researchHN 24↑ · 25 comments

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Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security Labs·Sep 11, 00:00 UTC · 5d agoResearch

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PHAT: PHotonic Accelerator for TFHE

PHAT photonic accelerator using optically addressed phase-change memory speeds TFHE bootstrapping FFTs 2.14x-5.10x over the prior ASIC accelerator.

Researchers propose PHAT, an electro-photonic accelerator for TFHE fully homomorphic encryption built on optically addressed phase-change memory (OPCM) processing-in-memory. The architecture adds OPCM-based FFT units, a twiddle-stationary dataflow, and a scheduling mechanism to maximize FFT utilization for TFHE bootstrapping. It achieves 2.14x-5.10x speedups across four real-world TFHE workloads versus the state-of-the-art ASIC accelerator, improving feasibility of privacy-preserving computation in the cloud.

arXiv cs.CR·Sep 10, 14:30 UTC · 6d agoResearch

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Hackers deploy Linux rootkit on F5 BIG-IP APM devices, hiding web shell in memory

Sophos analyzed a Linux rootkit, tracked as PoisonedRefresh, on hacked F5 BIG-IP APM devices hiding an in-memory web shell linked to exploited CVE-2025-53521.

Sophos and ESET analyzed an implant (named PoisonedRefresh by ESET) deployed on compromised F5 BIG-IP APM appliances, which serves enterprise, financial, government, and public sector deployments. The second-stage payload intercepts __libc_start_main, hooks Apache's APR module loader (apr_dso_load), RC4-encodes key strings, and rewrites PHP file reads in memory to embed a web shell inside legitimate scripts like apm_css.php3, full_wt.php3, and webtop_popup_css.php3, leaving on-disk files unchanged. A related installer component infects /usr/sbin/httpd, persists across BIG-IP upgrade images, modifies SELinux configuration, and deploys the payload. The malware also creates a Unix domain socket at /run/bigtlog.pipe that hands authenticated local connections to /bin/bash; F5 links the activity to CVE-2025-53521, an unauthenticated RCE in BIG-IP APM already exploited in the wild.

Help Net Security·Sep 9, 11:05 UTC · 7d agoMalware in the wildCVE-2025-535211

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Hackers breach F5 BIG-IP APM devices to deploy Linux rootkit

Sophos analyzed a Linux rootkit on F5 BIG-IP APM devices that injects a fileless PHP web shell, likely after CVE-2025-53521 exploitation.

Sophos analyzed a Linux rootkit targeting F5 BIG-IP APM environments, also tracked by ESET as PoisonedRefresh, which hijacks Apache's apr_dso_load module loader to inject a fileless PHP web shell into memory. The implant intercepts __libc_start_main, hides strings with RC4, creates a password-protected local UNIX socket backdoor for interactive Bash access, and persists across BIG-IP upgrade images while modifying SELinux configuration. It is likely a second-stage payload following exploitation of CVE-2025-53521, a critical RCE flaw F5 reclassified from a DoS issue in March. The ShadowServer Foundation tracked 795 F5 BIG-IP APM endpoints exposed online.

BleepingComputer·Sep 8, 20:08 UTC · 8d agoMalware in the wildCVE-2025-53521

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Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye

METR analysis finds AI accelerating cyber vulnerability discovery, while SPADE self-play environment generation improves Qwen3 reasoning benchmark scores at 30B scale.

Import AI 470 discusses a METR research note reporting differential acceleration from AI: major acceleration in reported cyber vulnerabilities (cURL, OpenSSL, Firefox, Microsoft, NVD, OSV), minor acceleration in mathematics, and no measurable acceleration in AI-research optimization benchmarks. It also covers SPADE, a self-play framework from a multi-university team (University of Washington, Stanford, MIT, CMU, and others) that co-evolves executable training environments and agent capability using Environment Designer and Reasoning Agent roles with hint-based regret rewards. Trained on Qwen3-4B-Instruct-2507, Qwen3-8B, and Qwen3-30B-A3B-Instruct-2507 via GRPO (400 rollouts of 25 environments), SPADE lifted the 30B-A3B game-environment suite average to 58.3, +8.1 over base, and improved tool-use results across backbones. The issue also references Hawkeye for building better GPU kernels.

Import AI·Aug 24, 13:12 UTC · 23d agoAI research

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Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

Researchers introduce model-aware diffusion schedules via fiberwise optimal transport, cutting flow-matching FID on CIFAR-10 by 38.6% at 16 function evaluations.

The paper proposes constructing diffusion and flow-matching sampling schedules from a fiberwise prediction risk defined via optimal transport, combined with coefficient-path kinetic action, yielding a closed-form time allocation. Across DDPM and flow-matching experiments spanning targets, datasets, and architectures, the schedules beat model-agnostic baselines, including a 38.6% relative FID reduction for flow matching on CIFAR-10 at 16 function evaluations. Normalized fiberwise-risk profiles from independently trained models align closely, suggesting empirical universality, and a frozen analytic allocation template retains most of the gains.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:30 UTC · 6d agoAI research

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Stealth rootkit targeting F5 BIG-IP could expose enterprise identity gateways

Sophos analyzed a stealth Linux rootkit that hides a web shell in memory on compromised F5 BIG-IP APM identity gateways, evading file-based detection.

Sophos analyzed a second-stage Linux rootkit implant found in compromised F5 BIG-IP APM environments running Apache and PHP, linked to exploitation of CVE-2025-53521, an unauthenticated RCE. The implant hooks Apache's PHP-loading process and serves modified in-memory versions of three legitimate webtop PHP files (apm_css.php3, full_wt.php3, webtop_popup_css.php3), leaving on-disk files untouched so hashes and integrity checks pass. It also establishes access via an authenticated local UNIX socket that can provide an interactive /bin/bash session. Experts warn compromised APM appliances, which handle federated SSO and terminate TLS at enterprise perimeters, could enable SSO token theft and lateral movement to trusted downstream applications.

CSO Online·Sep 10, 11:51 UTC · 6d agoMalware in the wildCVE-2025-53521

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You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs

Study quantifies DPO-tuned LLMs undershooting requested emotional intensity, tracing the gap to candidate-pool extremity rather than conditioning format.

Conditioning an instruction-tuned LLM on continuous valence-arousal targets yields gain of only 0.26 for valence and 0.13 for arousal on Llama-3.1-8B, far below faithful control of 1.0. The authors attribute undershoot to neutral-heavy preference corpora like EmoBank and candidate pools lacking extreme affect, leaving DPO without extreme exemplars. Uniform target coverage with a hotter candidate pool raises valence gain to 0.40 on Llama-3.1-8B and 0.44 on Qwen3-8B, with modest in-distribution cost; arousal gains remain unstable across seeds.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:47 UTC · 9d agoAI research

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Jackrong/Qwopus3.8-27B-Flash-GGUF — new model trending #26 on Hugging Face

Community fine-tune Qwopus3.8-27B-Flash, built on Qwen3.8-27B, cuts agent reasoning latency with 12.8% faster decoding and 80.7% MTP acceptance.

Jackrong released Qwopus3.8-27B-Flash, a fine-tune of Qwen3.8-27B optimized for long-running agent workloads, reporting 12.8% faster decoding and 80.7% multi-token-prediction acceptance. Training used roughly 1.5 million teacher-scored SFT examples filtered to the top 10%, followed by reinforcement training with NVIDIA NeMo-RL and GSPO. The author notes an explicit trade-off: MMLU-Pro mixed-set scores are lower than the base model, and a known bug can produce incorrect Python indentation. Author-provided benchmarks have not been independently verified.

Hugging Face trending models·Sep 4, 12:43 UTC · 12d agoModel release1

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Metasploit Wrap Up: Lot of summer shells and fit http profiles

Metasploit 6.5 ships 13 new modules including RCEs for SonicWall SMA1000, Ghost CMS, Joomla JCE and Langflow, plus a Linux kernel LPE.

Rapid7's Metasploit wrap-up covers the 6.5 release, which adds 13 new modules, including remote code execution exploits for WordPress WP2Shell, Ghost CMS, Joomla JCE, Langflow, OpenCATS, Pterodactyl Panel, SonicWall SMA1000, Ray Dashboard and a Pix-for-WooCommerce plugin. The Fragnesia Linux kernel local privilege escalation (CVE-2026-46300) also landed. The release introduces HTTP malleable profiles, MCP functionality, Linux multi-fetch payloads and improved Windows on ARM support.

Rapid7 Blog·Aug 14, 21:27 UTC · Aug 14, 2026ToolsCVE-2026-46300

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Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

ICF-DLM, the first language-model-based inertial confinement fusion predictor, cuts peak-timing error from 11.6 to 9.2 steps versus LLaMA-3-8B.

Each National Ignition Facility shot costs roughly one million dollars, motivating accurate AI surrogates for predicting 512-step neutron-rate waveforms from laser pulses and target parameters. ICF-DLM combines physics-typed decomposition into yield, peak timing, and local waveform; bidirectional denoising that defers commitment to peak location; and a physics-driven PPO reward. On ICFBench (50,000 simulations plus 232 experimental shots) it outperforms a matched autoregressive LLaMA-3-8B, classical sequence models, and LLM-based time-series predictors.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:00 UTC · 9d agoAI research

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Speculative Decoding in vLLM on AMD GPUs

vLLM benchmarks speculative decoding on AMD Instinct MI300X and MI355X GPUs across five drafting methods including EAGLE-3 and native MTP.

The vLLM project documents draft-and-verify speculative decoding support for AMD GPUs via ROCm, comparing native MTP, Gemma 4 MTP, EAGLE-3, DFlash, and DSpark drafting approaches. Output-token throughput effects varied with drafting method, proposal length, model family, draft checkpoint, workload, and acceptance behavior. The post also covers how to enable each method plus practical tuning and observability considerations.

Hacker News · AI·Sep 7, 09:26 UTC · 9d agoAI tools & infraHN 141↑ · 52 comments1

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FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

FreeFlow is a bias-free hierarchical transformer achieving state-of-the-art optical flow results on Sintel, KITTI-2015, and Spring benchmarks.

FreeFlow replaces task-specific inductive biases like correlation volumes and iterative warping with a single feed-forward encoder-decoder combining window, shifted-window, and reduced-resolution global attention. It reaches 0.68/1.48 EPE on Sintel Clean/Final, 3.23 Fl-all on KITTI-2015, and 3.192 1px on Spring. The architecture scales consistently from small to large variants and remains memory efficient at 1080p inference.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research

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Implementing a White-Box Undetectable Backdoor for Random Fourier Features

Researchers implement Goldwasser's CLWE-based undetectable backdoor for Random Fourier Features models in numpy/scipy, confirming practical realizability with no detectable differences from clean models.

The paper provides an end-to-end implementation of the Goldwasser et al. white-box undetectable backdoor for models trained with the Random Fourier Features algorithm, using only numpy and scipy. It derives two samplers for the core GP_d(b_k) distribution: a rejection-sampling proxy and an exact closed-form sampler verified against its analytic form. Statistical indistinguishability tests covering weight-space and functional black-box comparisons found no detectable difference between backdoored and clean models across sparsity ratios. The underlying lattice hardness reduction was not reproduced, and the work demonstrates the threat is realizable with commodity scientific-computing tools rather than specialized cryptographic infrastructure.

arXiv cs.CR·Sep 14, 22:18 UTC · 1d agoResearch

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Decoy Direction Optimization: A Post-Hoc Defense Against LLM Abliteration

Researchers introduce Decoy Direction Optimization, a cheap weight-editing defense that blinds refusal-direction ablation attacks against open-weight LLM safety guardrails.

Refusal Feature Ablation bypasses safety guardrails in open-weight LLMs by projecting out a linear refusal direction, often with high attack success rates. Decoy Direction Optimization injects a high-magnitude nonlinear decoy into MLP neurons so attackers' contrastive estimators ablate a harmless orthogonal feature instead. Evaluated across six model families, DDO keeps ASR below 10% under standard RFA and on Llama-3-8B-Instruct reduces Heretic weight-level attack ASR from 88.7% to 18%. It costs 30 to 450 times less per configuration than trained defense baselines.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI safety & security

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Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost·Sep 13, 19:46 UTC · 3d agoAI research

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[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space·Sep 12, 05:56 UTC · 4d agoModel release 4 sources1

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DeepSeek v4.1 Flash Is Now Our Best Hacking Model

DeepSeek V4.1 Flash achieves 11/11 code executions on Enclave's AI hacking benchmark for $4.65 across Grafana, Jenkins, and Nextcloud targets.

Enclave AI reports DeepSeek V4.1 Flash gained code execution on all 11 vulnerable targets while all four fixed controls held, costing $4.65 accepted ($5.14 total) with 268.3 million mostly cached input tokens. A path-level audit found six runs used the planned weaknesses, such as Jenkins credential-file abuse and a Nextcloud access-control confusion, while five runs exploited alternate routes in the Grafana and Jenkins test environments. The benchmark was hardened to check attack paths, not just outcomes, underscoring that hacking agents find the fastest exploitable route.

Hacker News · AI·12:19 UTC · 7h agoAI safety & security 3 sourcesHN 54↑ · 7 comments

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Foundation Models for Generalizable Semantic and Goal-Oriented Communication

FMSGOC uses vision-language foundation model priors plus diffusion reconstruction to enable generalizable semantic communication at 0.039 bits per pixel for 6G.

FMSGOC targets generalization failures in semantic and goal-oriented communication for 6G by leveraging broad visual-linguistic foundation model priors. A vision-language model selects sparse, goal-aligned semantic anchors while a fine-tuned diffusion model performs masked completion to reconstruct images at the receiver, decoupling what to send from how to reconstruct. On CIFAR-10 it reaches 0.039 bits per pixel with cosine similarity 0.87-0.90 and 0.83-0.86 on unseen ImageNet inputs, outperforming end-to-end baselines at lower bit rates.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 18:12 UTC · 9d agoAI research

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NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

An 8.9B-parameter latent-space language model using next-concept prediction matches OLMo-3-7B pretraining loss with only 51.3% of the training tokens.

NCP-ArchPreview augments next-token prediction with Next Concept Prediction over a product-quantized concept vocabulary built from hidden states, trained jointly end-to-end. The 8.9B model was trained on 5.73T tokens from the Dolma-3 dataset, the largest latent-space language model demonstration to date. It consumes 51.3% of the tokens to reach OLMo-3-7B's final pretraining loss and outperforms it by 2.45 points on the downstream macro-average, including a 5.99-point GSM8K gain. The learned latent space also enables lightweight domain adaptation via a 17M-parameter VQ module and improves speculative drafting accepted length by 4.17%.

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

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Measuring benchmark optimization in speech recognition

Hugging Face examines how much speech recognition systems overfit benchmarks and how to measure benchmark optimization in ASR.

A Hugging Face post on measuring benchmark optimization in automatic speech recognition, analyzing how model improvements on benchmarks reflect genuine capability gains versus overfitting. It is evaluation methodology research with no direct security impact.

Hugging Face Blog·Aug 21, 00:00 UTC · 26d agoAI research

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A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost·Sep 13, 17:02 UTC · 3d agoAI research1

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Memory-Efficient Designs for Word-Wise Universal Fully Homomorphic Encryption

BXT framework mitigates FHE memory bottlenecks via ciphertext compression, serialization, delayed seeding, and digit pruning, achieving up to 3.8x CNN inference speedup.

A new paper proposes BXT, an optimization framework for word-wise Universal Fully Homomorphic Encryption that targets the memory bottleneck rather than compute. It combines four techniques: ciphertext compression via seed regeneration, bit-packed ciphertext serialization for L2-to-L1 transfers, delayed PRNG-heavy offline seed generation across aggregated operations, and fault-aware ciphertext digit pruning. On CNN inference, the BXT-CSO50 configuration achieves up to 3.8x speedup over a 100x GPU baseline with under 1% accuracy loss at 50% comparison precision.

arXiv cs.CR·Sep 4, 06:03 UTC · 12d agoResearch

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The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements

Researchers derive sufficient sample-size conditions for recovering sparse binary signals from sparse Gaussian measurements, quantifying an information-theoretic threshold of order slog(p/s)/log(ds/p).

The paper studies support recovery of sparse binary signals from noisy linear measurements. For sparse Gaussian designs, the authors identify sufficient minimal sample sizes for maximum-likelihood recovery in the high-SNR regime d*s/p -> infinity, yielding an information-theoretic threshold of order slog(p/s)/log(ds/p) that makes the price of measurement sparsity explicit. They also show a regime where the sample-complexity loss from sparsity is only logarithmic while computational gains are nearly linear, and prove that for independently sparsified dense Gaussian designs a sample size of order p/ψ² suffices for support recovery at any fixed error level.

Hugging Face daily papers·Sep 7, 20:00 UTC · 9d agoAI research

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