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Re: Retrospective by 'gpg.fail' authors

GnuPG's Werner Koch says gpg.fail samples only crash GnuPG via DER-as-printf format string in --debug x509; RCE claim remains unproven.

Werner Koch replied to the gpg.fail retrospective, noting that GnuPG versions above 2.2 produce garbled stderr or crash when the project's certificates are used with --debug x509 because DER data is passed as a printf format string. Testing the certificates from the researchers' Git repo yielded only a segfault, not demonstrated code execution. Koch states how remote code execution would be achieved is unclear and asks for a real reproducer.

oss-securityupdated 05:03 UTC · 7h agofirst Sep 15, 15:24 UTC · 20h agoVulnerability 6 sources

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending modelsAug 28, 11:26 UTC · 19d agoModel release

CVE-2026-85630: HTML::FormHandler versions before 0.410002 for Perl render field attributes into HTML without escaping using the process_attrs method

CVE-2026-85630: HTML::FormHandler Perl versions before 0.410002 render field attributes into HTML unescaped, enabling HTML injection.

The Perl module HTML::FormHandler before version 0.410002 renders field attributes into HTML without escaping via the process_attrs method, per an oss-security disclosure. Applications using affected versions could allow unescaped markup to be injected into generated HTML. Users should upgrade to version 0.410002 or later.

oss-securitySep 8, 20:30 UTC · 7d agoVulnerability 2 sources CVE-2026-856301

Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project ZeroSep 8, 07:00 UTC · 8d agoResearch1

Hillingar - MirageOS Unikernels on NixOS

A technical write-up details Hillingar, enabling reproducible Nix-based builds and NixOS deployment of MirageOS OCaml unikernels such as authoritative DNS servers.

This blog post (published December 2022, updated February 2025) describes Hillingar, work from the author's master's thesis enabling reproducible builds and deployments of MirageOS OCaml unikernels using Nix and a custom NixOS module, demonstrated with an authoritative DNS server. MirageOS unikernels embed application and low-level OS code in a single kernel, allowing dead-code elimination that reduces attack surface and improves efficiency. The post covers challenges such as solving opam dependency version constraints when linking a single dependency set.

Lobsters · securitySep 4, 09:17 UTC · 12d agoTools1

WireGuard-Linux Stack-Based Buffer Overflow in lsiio (Linux IIO Userspace Tool) Due to Unbounded fscanf

The Linux IIO userspace tool lsiio has a stack buffer overflow in find_type_by_name() caused by unbounded fscanf reads of oversized filesystem-backed attribute values.

A stack-based buffer overflow exists in the Linux Industrial I/O (IIO) userspace utility lsiio. In the find_type_by_name() function, the program reads an unbounded string from a filesystem-backed attribute into a fixed-size stack buffer using fscanf("%s", ...). A crafted or oversized attribute value causes a write beyond the bounds of the destination buffer. Despite the title's reference to WireGuard-Linux, the flaw described is in the IIO lsiio utility.

Full DisclosureSep 4, 00:13 UTC · 12d agoVulnerability

wp2shell: incident response guide (CVE-2026-63030 + CVE-2026-60137)

Eye Security published forensic IR tooling for wp2shell (CVE-2026-63030/CVE-2026-60137), the unauthenticated WordPress core RCE chain, after WordPress.org forced auto-updates.

wp2shell chains a REST API batch-endpoint route-confusion bug (CVE-2026-63030) with an SQL injection in WP_Query's author__not_in parameter (CVE-2026-60137), giving unauthenticated attackers rogue admin and code execution on default installs. Adam Kues of Searchlight Cyber discovered the flaw, a public PoC exists on GitHub, and WordPress.org forced automatic updates across an estimated 200M+ sites. Eye Security released a compromise-scanner WordPress plugin and browser extension and notes database artifacts (oEmbed cache rows, changesets) are the primary evidence since the attack is log-blind; fixed versions are 6.8.6, 6.9.5, and 7.0.2.

Web discovery (articles for new exploits & KEV entries)Sep 8, 16:27 UTC · 7d agoExploit / PoC in the wild 2 sources CVE-2026-63030 CVE-2026-601371

27.5KB language-agnostic WebGPU syntax highlighter

A developer released gpu-lexer, a 27.5KB language-agnostic syntax highlighter that uses a tiny WebGPU model to label code tokens in the browser.

gpu-lexer splits source into words, whitespace, and symbols, then a small WebGPU model uses local and whole-file context to assign nine token classes, working on languages never seen in training. On held-out files, 12.57% of token labels differ from Shiki, though this measures agreement with Shiki rather than objective correctness. In benchmarks against Shiki 4.4.3, Prism.js, Highlight.js, Sugar High, and Starry Night, it highlighted 10 concatenated copies of three.min.js (5.56M characters) about 10x faster on an Apple M4 Pro in Chrome 152. The author frames it as an experiment, not a grammar-equivalent highlighter.

Hacker News · securitySep 9, 01:14 UTC · 7d agoAI tools & infra HN 21↑ · 5 comments1

CVE-2026-85484: HTML::FormHandler versions before 0.410002 for Perl render option group labels and radio button labels into HTML without escaping

HTML::FormHandler before 0.410002 for Perl renders option group and radio button labels unescaped into HTML, enabling XSS (CVE-2026-85484).

Robert Rothenberg disclosed CVE-2026-85484 on the oss-security mailing list, affecting HTML::FormHandler versions before 0.410002 for Perl. The module renders option group labels and radio button labels into HTML without escaping, which can enable cross-site scripting in applications using the rendered markup. The issue is addressed in version 0.410002.

oss-securitySep 8, 20:16 UTC · 7d agoVulnerability 2 sources CVE-2026-85484

Embedded Graph Flows for Categorical Graph Generation

Researchers propose Embedded Graph Flows, a generative model with learned categorical embeddings that beats DiGress and GruM on molecular graph benchmarks.

Embedded Graph Flows (EGF) learns continuous embeddings for node and unordered-edge categories and transports Gaussian noise toward these endpoints using a permutation-equivariant graph transformer. On QM9 it achieves the best result on all four reported metrics, with a Fréchet ChemNet Distance of 0.150 versus 0.717 for DiGress and 0.812 for GruM. On ZINC250k it retains the lowest NSPDK MMD, indicating close agreement with local substructures of reference molecules. Code is released on GitHub.

arXiv cs.AI / cs.LG / cs.CLSep 4, 16:26 UTC · 11d agoAI research1

CVE-2026-81578 + CVE-2026-82078 | PaperCut NG/MF Authentication Bypass and Unsafe Dynamic Class Loading Vulnerabilities

Two chained PaperCut NG/MF flaws, CVE-2026-81578 and CVE-2026-82078, enable pre-auth RCE, with active exploitation confirmed in customer environments.

PaperCut NG/MF is affected by CVE-2026-81578, an improper access control flaw (CVSS 4.0 8.8) allowing unauthenticated configuration changes, and CVE-2026-82078, an unsafe dynamic class loading flaw (CVSS 4.0 9.4) enabling arbitrary Java bytecode execution. Chained, they yield pre-authentication remote code execution on the PaperCut Application Server. PaperCut confirmed active exploitation and customer incidents, and Huntress observed exploitation starting August 26, 2026. Emergency Patch Release 2 is available for NG/MF v24-v26, with IOCs including suspicious pc-app.exe child processes, truncated server.log files, and AnyDesk installs.

Horizon3.aiSep 1, 15:31 UTC · 14d agoExploit / PoC in the wildCVE-2026-81578 CVE-2026-820781

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:43 UTC · 5d agoAI research

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:43 UTC · 19h agoAI research

PaperCut NG/MF Zero-day Vulnerability Exploited in the Attacks (CVE-2026-82078 & CVE-2026-81578)

PaperCut NG/MF zero-days CVE-2026-82078 and CVE-2026-81578 are actively exploited, chaining to pre-auth RCE on the Application Server.

PaperCut issued an urgent security advisory for two actively exploited vulnerabilities, CVE-2026-82078 and CVE-2026-81578, affecting all versions of PaperCut NG and PaperCut MF. When chained, the flaws enable pre-authentication remote code execution on the PaperCut Application Server, originating from a request-confusion and authorization gap. PaperCut is widely deployed for print management in enterprises and education, making unpatched instances a high-value target.

Qualys ThreatPROTECTAug 31, 12:07 UTC · 16d agoExploit / PoC in the wildCVE-2026-82078 CVE-2026-81578

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face BlogAug 18, 00:00 UTC · 29d agoAI tools & infra1

Adaptive Gated Deepfake Detection for Low-Resolution and Resource-Constrained Environments

AdaGate-DF routes deepfake detection by image quality through dual multi-exit gates, hitting 0.9370 AUC on Celeb-DF with low inference latency.

AdaGate-DF is an adaptive gated deepfake detection framework that uses image-quality cues to send high-quality images through earlier exits, saving compute in resource-constrained settings. On Celeb-DF it achieves an AUC of 0.9370, outperforming MaD-CoRN and DefakeHop++, and reaches 0.9708 at 384x384 resolution. On FaceForensics++ it remains effective under class imbalance while balancing uncertainty-aware prediction and computational efficiency.

arXiv cs.AI / cs.LG / cs.CLSep 4, 16:14 UTC · 11d agoAI research

iceener/files-stdio-mcp-server: sandbox escape in fs_search via a symlinked directory (recursive walker validates only the top level)

iceener/files-stdio-mcp-server allows a read-side sandbox escape: fs_search follows symlinked directories while the recursive walker validates confinement only at the top level.

A vulnerability report describes a read-side sandbox escape in iceener/files-stdio-mcp-server, an MCP server for text-based file access that explicitly promises 'Sandboxed filesystem access. Only these paths are available'. The fs_search tool can follow symlinked directories outside the allowed paths, and the recursive directory-listing walker used by fs_search (and by fs_read) validates confinement only at the top level. The same flaw affects fs_read's directory-listing walker. No CVE identifier was assigned in the provided report text.

oss-securitySep 10, 01:17 UTC · 6d agoVulnerability

Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps

Hugging Face guide fine-tunes a 350M-parameter model with 100 GRPO steps to improve structured output reliability.

A Hugging Face blog post demonstrates fine-tuning a 350M-parameter model using GRPO (Group Relative Policy Optimization) with TRL over 100 training steps. The stated goal is more reliable structured outputs from small language models. No article body was available, so details beyond the title are limited.

Hugging Face BlogSep 3, 00:00 UTC · 13d agoAI tools & infra

PaperCut NG/MF vulnerabilities exploited in zero-day attacks

PaperCut warns of active zero-day exploitation chaining CVE-2026-81578 and CVE-2026-82078 for pre-auth remote code execution in NG/MF print management.

PaperCut Software confirmed attackers are chaining two vulnerabilities in PaperCut NG and MF: CVE-2026-81578, an improper access control flaw in the web management interface allowing unauthenticated configuration changes, and CVE-2026-82078, unsafe dynamic class loading in database connection utilities enabling arbitrary Java bytecode execution. Huntress reproduced a pre-authentication remote configuration takeover and full RCE chain against PaperCut NG 25.0.11.75758 and observed limited exploitation at two customers, including post-exploitation whoami and ver commands. The vendor released Emergency Patch Release 2 with additional hardening and urged restricting Application Server web access to trusted IPs. In 2023, Clop and LockBit affiliates abused CVE-2023-27350 and CVE-2023-27351 in the same software.

Help Net SecurityAug 31, 14:39 UTC · 15d agoExploit / PoC in the wildCVE-2026-81578 CVE-2026-82078 CVE-2023-27350+1 CVEs1

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 papersSep 8, 20:00 UTC · 7d agoAI research1

PaperCut NG/MF Critical Zero-Day Exploited in the Wild

PaperCut confirms active exploitation of critical zero-days CVE-2026-81578 and CVE-2026-82078 in PaperCut NG/MF print management software, with confirmed customer incidents.

PaperCut Software issued an urgent advisory on August 27, 2026, confirming it is investigating active exploitation of flaws in PaperCut NG and PaperCut MF and treating the issue as a security emergency. On August 28 the vendor assigned CVE-2026-81578 and CVE-2026-82078 to the two vulnerabilities forming the exploit chain. At initial disclosure, no CVSS score, vulnerability class, authentication requirements, or exploit path details were public. Rapid7 is tracking the issue as an emerging threat.

Rapid7 BlogAug 28, 10:09 UTC · 19d agoExploit / PoC in the wildCVE-2026-81578 CVE-2026-82078

Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch

New work characterizes language generation in the limit via finite witnesses, proves a full separation-width hierarchy, and formalizes all results in Lean.

The paper fully characterizes when language generation in the limit is possible for arbitrary families over a countable universe: each target must admit a finite positive witness such that targets activated by any finite sample share an infinite common intersection. It defines positive separation width and proves every level of the resulting hierarchy occurs, with countable families admitting singleton witnesses and unions of families with infinite common cores requiring unbounded finite witnesses. The characterization, a universal normalization, and a diagonal capture lemma are machine-checked in the Lean proof assistant, with the development maintained on GitHub.

arXiv cs.AI / cs.LG / cs.CLSep 9, 17:54 UTC · 6d agoAI research1

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.CLSep 7, 17:00 UTC · 8d agoAI research

Attention Quantization for Tabular Foundation Models

FP8 quantization of attention queries, keys, and values speeds tabular foundation model inference up to 1.7x with no accuracy loss.

The paper develops an FP8 quantization strategy targeting attention calculations (queries, keys, values) in tabular foundation models, arguing attention matters more than weight or KV cache quantization given their differing size and serving patterns versus LLMs. Aligning quantization error between test rows and training rows proves crucial, since misalignment causes drastic accuracy drops. A Triton kernel using explicit FP8 matrix multiplication achieves up to 1.7x speedup over regular 16-bit kernels, with no relevant accuracy loss on TabPFN-v3 and TabICLv2 across TabArena and BeyondArena benchmarks.

arXiv cs.AI / cs.LG / cs.CLSep 11, 16:31 UTC · 4d agoAI research1

Beyond the Turing threshold: Productive grammars generate essentially undecidable languages

A theoretical paper designs formal grammars that emulate Post's productive sets, generating languages that are provably beyond Turing decidability.

The paper elaborates on Emil Post's productive sets, which are not even semi-computable, and builds formal grammars that emulate their construction over natural numbers. The resulting languages are shown to be essentially undecidable, placing them beyond Turing decidability. This is pure computability and formal language theory with limited direct security relevance.

arXiv cs.CRSep 10, 11:20 UTC · 6d agoResearch1

DF26: We Cannot Tell Fake From Real Anymore

DF26 benchmark shows humans and state-of-the-art deepfake detectors perform near chance on videos generated by seven modern text-to-video models.

Researchers introduce DF26, a benchmark of 271 real and 2,420 fully synthetic videos created by seven modern video generation models, all depicting single-person public-speaking scenarios such as direct-to-camera recordings, official statements, and studio interviews. Human viewers and state-of-the-art deepfake detectors scored close to random chance at distinguishing fakes from real footage. The authors argue current evaluation protocols are insufficient and call for benchmarks that explicitly measure robustness to modern generative model distribution shifts.

Hugging Face daily papersSep 6, 20:00 UTC · 9d agoAI research

Emacs arbitrary code execution: incomplete fix for CVE-2024-53920

Incomplete fix for Emacs CVE-2024-53920 allows arbitrary code execution when viewing or editing untrusted files in non-Lisp modes like Perl flymake.

Bas Alberts of GitHub Security Lab discovered that the patch for CVE-2024-53920, an arbitrary code execution flaw in Emacs, was incomplete. Code execution remains possible when viewing or editing untrusted text files in modes other than Emacs Lisp mode, for example Perl files with flymake mode enabled. All Emacs versions affected by the original CVE remain affected by the incomplete fix.

oss-securitySep 14, 14:36 UTC · 1d agoVulnerability CVE-2024-53920

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:43 UTC · 5d agoAI research

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.CLSep 4, 17:32 UTC · 11d agoAI research1

ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking in Full-Duplex Dialogue

ECHO benchmark pairs identical-overlap Chinese dialogue examples with contrasting contexts, revealing most full-duplex systems bias toward yielding the floor.

ECHO is a paired diagnostic benchmark for Chinese full-duplex turn-taking that matches examples with identical overlap transcripts but contrasting preceding multi-turn contexts, one requiring Yield and the other Keep. It also includes off-talk examples for diagnosing unnecessary yielding and introduces pair accuracy, which grants no credit to constant-action policies. Experiments across multiple full-duplex systems show most exhibit a pronounced Yield bias, performing substantially better on interruptions than backchannels. The benchmark and metadata will be publicly released.

arXiv cs.AI / cs.LG / cs.CLSep 15, 15:58 UTC · 20h agoAI research

USN-8736-1: Perl vulnerabilities

Ubuntu issued USN-8736-1 fixing two Perl regex flaws that could cause denial of service, code execution, or security-restriction bypass.

Ubuntu released a security notice addressing two Perl vulnerabilities in regular expression handling. CVE-2026-15534 involves mishandling of large inputs during regex matching, enabling out-of-bounds heap reads or writes that could lead to denial of service or arbitrary code execution. CVE-2026-19487 involves incorrect matching for regexes with alternative branches, allowing security restrictions to be bypassed. Users are advised to apply the updated packages.

Ubuntu Security NoticesSep 8, 14:25 UTC · 7d agoAdvisory CVE-2026-15534 CVE-2026-19487