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USN-8736-2: Perl vulnerabilities

Ubuntu issued USN-8736-2 fixing two Perl regex flaws that could cause out-of-bounds heap access, denial of service, or security bypass on 24.04 LTS.

USN-8736-2 backports the Perl fixes from USN-8736-1 to Ubuntu 24.04 LTS. CVE-2026-15534 involves out-of-bounds heap reads or writes when regular expressions handle large inputs, potentially causing denial of service or arbitrary code execution. CVE-2026-19487 causes incorrect regex matching with alternative branches, allowing security restrictions to be bypassed.

Ubuntu Security Notices14:37 UTC · 5h agoAdvisory 13 sources CVE-2026-15534 CVE-2026-19487

ZDI-26-636: Oracle Outside In Technology PostScript File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability

ZDI disclosed a heap-based buffer overflow in Oracle Outside In Technology's PostScript parsing (CVE-2026-60412) enabling user-triggered remote code execution.

Zero Day Initiative published ZDI-26-636, a CVSS 7.8 heap-based buffer overflow in PostScript file parsing within Oracle Outside In Technology. Remote attackers can execute arbitrary code when the target opens a malicious file or visits a malicious page, making user interaction a requirement. The vulnerability is tracked as CVE-2026-60412. The advisory reports no exploitation.

ZDI Published AdvisoriesSep 9, 05:00 UTC · 7d agoVulnerability 4 sources CVE-2026-604121

SpliTEE: Improving LLM Inference on Trusted Hardware with Differentially Private GPU Outsourcing

SpliTEE splits LLM inference between Intel TDX trusted execution and untrusted GPUs, using differential privacy instead of encryption to protect intermediate representations.

SpliTEE extends split inference to LLMs, running inference partly inside an Intel TDX TEE while masking intermediate inputs sent to untrusted GPUs with differential privacy rather than encryption. The authors show a prompt-reconstruction attack recovers nearly 80% of prompts from unmasked intermediate representations, motivating the masking. A global sensitivity analysis bounds the required DP noise scale, avoiding quantization and keeping models in floating point. The implementation is nearly twice as fast as full CPU-based TDX inference and 5-15 seconds faster than encryption-based Slalom with higher accuracy, evaluated on Llama-3.2-3B and Qwen3-4B.

arXiv cs.CRSep 14, 04:55 UTC · 2d agoResearch

Vulnerabilities fixed in libxml2-2.15.4

libxml2 2.15.4 fixes an out-of-bounds read in xmlregexp's NXT macro plus several integer overflow and parsing flaws.

libxml2 2.15.4 (released September 1, 2026) includes security fixes: an out-of-bounds read in the xmlregexp NXT macro, missing overflow checks in dict.c, uri.c, and valid.c, an integer overflow in xmlIO before the writecallback, and an overflow check in xmlXPtrEvalXPtrPart. The release also propagates parseFlags in xmlXIncludeProcess and xmlXIncludeProcessTree. No CVE identifiers, exploitation, or severity ratings are given in the announcement.

oss-securitySep 4, 21:23 UTC · 11d agoVulnerability

[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 SpaceAug 22, 07:36 UTC · 25d agoAI industry

The GNU C Library security advisories update for 2026-09-14

glibc advisory GLIBC-SA-2026-0017 discloses a buffer overflow in strfmon/strfmon_l affecting versions 2.38 through 2.44.

The GNU C Library published security advisories including GLIBC-SA-2026-0017, a buffer overflow in strfmon and strfmon_l. Calling these functions with right-justified width padding conversions can write past the end of the caller-supplied output buffer in glibc 2.38 to 2.44. Exploitation requires an application code path that calls strfmon with attacker-influenced parameters.

oss-securitySep 14, 19:54 UTC · 1d agoVulnerability 2 sources1

OPEN-1B: A Fully Auditable Training Run

Open-1B releases a 1B-parameter model with bitwise-reproducible training, letting independent auditors verify every step of the run on commodity hardware.

The paper introduces a 'fully auditable' tier of model transparency: every training operation is reproducible with bitwise certainty on heterogeneous commodity hardware by imposing definite ordering on GPU kernel reductions, data batch ordering, and collective communication. Because replaying a full run on one machine is infeasible, a collective verification scheme lets many independent auditors certify individual steps covering the whole run. The authors release Open-1B with its full pretraining dataset, every intermediate checkpoint, the training codebase, and an audit harness. This rules out undisclosed data, injected biases, or backdoors that proof-of-learning or proof-of-training-data techniques cannot exclude.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:23 UTC · 1d agoAI research

[dos] Nmap 7.99 - Extension Header Integer Underflow

A proof-of-concept denial-of-service exploit for Nmap 7.99 leverages an integer underflow in extension header parsing to crash the scanner.

Exploit-DB lists a denial-of-service proof of concept targeting Nmap version 7.99. The flaw is an integer underflow when handling extension headers, which can crash the scanner. No exploitation in the wild or patch details are mentioned in the listing.

Exploit-DBAug 17, 00:00 UTC · Aug 17, 2026Exploit / PoC1

Tables Decoded: DELTA for Structure, TARQA for Understanding

DELTA extracts tables into compact OTSL text and TARQA fine-tunes LLMs on it, beating VLM baselines on table QA.

DELTA separates physical structure recognition, logical structure recognition, and OCR to output tables in Optimised Table Structure Language (OTSL), a compact unified format encoding cell arrangements and content. It achieves TEDS-Structure scores comparable to state-of-the-art methods across FinTabNet, PubTabNet, and PubTables-1M, with robustness tested on a curated Hindi benchmark, TORQUE. TARQA, an LLM fine-tuned on OTSL sequences, gains 9.3 percentage points on WTQ TabQA and 9.2 points on FinTabNetQA TabVQA; code, models, and the benchmark are released on GitHub.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:59 UTC · 1d agoAI research

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

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 · 12d agoAI research1

USN-8737-1: GNU C Library vulnerabilities

Ubuntu patches GNU C Library flaws including a strfmon buffer overflow and tdelete out-of-bounds access that could enable code execution.

Ubuntu issued USN-8737-1 fixing multiple GNU C Library vulnerabilities. CVE-2026-19499 is a buffer overflow in the strfmon function when handling right-justification padding, affecting only Ubuntu 26.04 LTS. CVE-2026-19542 is an out-of-bounds stack array access in the tdelete function. An additional issue involves incorrect memory handling in wordexp with the WRDE_APPEND flag. All issues could potentially cause denial of service or arbitrary code execution.

Ubuntu Security NoticesSep 8, 15:17 UTC · 8d agoAdvisory CVE-2026-19499 CVE-2026-19542

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

E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning

E2A-Bench, a 969-query financial chart reasoning benchmark, finds VLMs fail evidence-to-action consistency, with fine-tuning amplifying BUY:SELL bias 4-6x.

E2A-Bench is a 969-query benchmark built from 323 HS300 constituents across three input modalities with deterministic OHLCV-derived evidence anchors, evaluating grounding, reasoning-action consistency, evidence-confidence calibration, and directional coverage via UCR, RCI, ECI, and NDR metrics. Testing 20 VLMs showed the lowest-hallucination model ranked near the bottom on coverage with only 6.4% directional coverage, and oracle-aided verification reduced unsupported claims but could collapse coverage. Financial fine-tuning amplified the BUY:SELL ratio by factors of 4.21 to 4.68 across base-fine-tuned pairs.

Hugging Face daily papersSep 12, 20:00 UTC · 3d agoAI research

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CLSep 4, 15:49 UTC · 12d agoAI research

Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning

Tiny Aya L2-Thinker, a 3.35B model, achieves over 93 percent in-language reasoning across 60 languages via optimized multilingual data mixing; weights released.

The paper studies L2 reasoning, the ability to reason consistently in the language of the user's prompt, approached through SFT data composition and scheduling. Tiny Aya L2-Thinker (3.35B) achieves an in-language reasoning rate above 93 percent across 60 languages on six benchmarks spanning math, commonsense, instruction following, open-ended generation, and cultural reasoning. Findings show generalization to held-out languages comes from broader language coverage, multilingual non-reasoning data, and a strong English reasoning backbone, suggesting reasoning is language-agnostic and transferable without per-language supervision. Model weights and multilingual reasoning data are publicly released.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:56 UTC · 7d agoAI research1

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

Re: rosbridge_library Protocol.incoming() quadratic CPU cost in JSON fallback

David Wheeler notes a rosbridge_library quadratic CPU cost flaw was publicly disclosed on oss-security without prior coordination.

In an oss-security reply, David A. Wheeler pointed out that a poster had just publicly disclosed details of a quadratic CPU cost issue in rosbridge_library's Protocol.incoming() JSON fallback path. Wheeler referenced the mailing list's stated norms encouraging public discussion of open-source security flaws. The reply itself contains no fix, CVE, or exploitation details.

oss-securitySep 14, 19:53 UTC · 1d agoVulnerability 3 sources

Steering Geometry: Validating Human Value Geometry in LLM Steering Space

Researchers show LLM activation steering vectors encode human value geometry predicted by Schwartz's theory, with fidelity improving at scale but degrading after instruction tuning.

The study tests whether latent geometry of activation steering vectors reflects theory-specified structure in human values, using Schwartz's Theory of Basic Human Values and a new 26K-sample benchmark spanning 20 values. Distribution-driven methods (CAA, SphericalSteer, ODESteer) recover predicted value topologies with Spearman correlation up to 0.51 (p < 10^-13), while behavior-centric methods (COLD-Steer, BiPO) steer comparably but show little geometric fidelity. Geometric alignment improves with model scale but drops after instruction tuning. Better geometric alignment also yields more human-consistent cross-value transfer, steering one value lifting compatible values and suppressing opposing ones.

Hugging Face daily papersSep 4, 20:00 UTC · 11d 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 · 5d agoAI research1

Re: Vulnerabilities fixed in libxml2-2.15.4

libxml2 2.15.4 patches two flaws including a heap buffer overflow in xmlDictAddQString tracked as CVE-2026-86137 and CVE-2026-86138.

libxml2 releases before 2.15.4 are affected by an integer overflow in xmlDictAddQString in dict.c that leads to a heap-based buffer overflow, tracked as CVE-2026-86137 and CVE-2026-86138. The oss-security post from Debian's Salvatore Bonaccorso flags the fixed release for downstream tracking. No exploitation is mentioned in the disclosure.

oss-securitySep 5, 12:16 UTC · 11d agoVulnerability CVE-2026-86137 CVE-2026-86138

USN-8765-1: python-sql vulnerability

Ubuntu patches python-sql SQL injection flaw where values passed to unary operators are incorrectly escaped.

Ubuntu Security Notice USN-8765-1 fixes a vulnerability in python-sql discovered by Cedric Krier. The library incorrectly escaped values passed to unary operators, allowing an attacker to potentially perform SQL injection attacks against applications using the library.

Ubuntu Security NoticesSep 15, 14:39 UTC · 1d agoAdvisory

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papersSep 7, 20:00 UTC · 8d agoAI research

ZDI-26-591: NVIDIA TensorRT ONNX File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability

ZDI disclosed a heap-based buffer overflow RCE (CVE-2026-24272, CVSS 7.8) in NVIDIA TensorRT ONNX parsing, requiring user interaction to exploit.

The Zero Day Initiative published advisory ZDI-26-591 covering a heap-based buffer overflow in NVIDIA TensorRT's ONNX file parsing. Successful exploitation allows remote code execution when a user opens a malicious ONNX file or visits a crafted page. ZDI rated the vulnerability CVSS 7.8 and assigned CVE-2026-24272.

ZDI Published AdvisoriesAug 24, 05:00 UTC · 23d agoAdvisory CVE-2026-24272

Atlas: Efficient Verifiable Semantic Search

Atlas delivers zero-knowledge proofs for HNSW semantic search, verifying RAG retrieval in under a second on SIFT1M and 2.0 seconds at 100M vectors.

Atlas lets a search provider prove that a query was answered correctly against a committed HNSW index without revealing the index, addressing provider deviations like truncation or bias. It combines offline preprocessing, a fixed-size-state restructuring of HNSW with a correctness proof, and timestep-tagged batching of per-step arguments. The system proves queries in under a second on SIFT1M and 2.0 seconds at 100 million vectors while preserving plaintext HNSW recall, and proven retrieval maintains end-to-end RAG answer quality at lower cost than prior verifiable retrieval systems.

arXiv cs.CRSep 10, 17:30 UTC · 6d agoResearch1

ZDI-26-592: NVIDIA TensorRT ONNX File Parsing Improper Validation of Array Index Remote Code Execution Vulnerability

NVIDIA TensorRT improper array index validation in ONNX parsing (CVE-2026-24238, CVSS 7.8) enables remote code execution.

ZDI-26-592 addresses improper validation of array index in NVIDIA TensorRT's ONNX file parsing, tracked as CVE-2026-24238 with CVSS 7.8. Exploitation permits remote code execution on affected installations and requires user interaction. The advisory was published by the Zero Day Initiative on August 24, 2026.

ZDI Published AdvisoriesAug 24, 05:00 UTC · 23d agoAdvisory CVE-2026-24238

Mathspace Data Breach Exposes Over 1 Million People

Mathspace breach exposed data of 1,079,819 Australian and New Zealand users via exploited Metabase zero-day CVE-2026-72898; ShinyHunters claimed responsibility.

Mathspace disclosed a breach affecting 1,079,819 students, teachers, staff, and parents in Australia and New Zealand. Attackers exploited the Metabase SQL injection zero-day CVE-2026-72898 (CVSS 10), patched August 6, and accessed Mathspace's self-hosted instance from August 10; ShinyHunters claimed the Metabase hacks. Exposed data includes names, usernames, emails, and login dates; no passwords, academic records, or credentials were taken.

SecurityWeekSep 8, 10:47 UTC · 8d agoData breach in the wildCVE-2026-72898

Show HN: Sunk Cost – How long until a local LLM rig pays for itself?

Show HN tool 'Sunk Cost' calculates when a local LLM rig breaks even versus falling API prices, factoring electricity cost and inference speed.

A Hacker News Show HN project called Sunk Cost models the payback period of buying local LLM hardware instead of paying API prices. Users can adjust assumptions like electricity cost ($/kWh) and API speed (tokens/second), and the model assumes API prices keep falling. Where local speed is unmeasured, it is estimated from memory bandwidth divided by bytes read per token, and labelled as an estimate.

Hacker News · securitySep 15, 01:37 UTC · 1d agoAI tools & infra HN 30↑ · 31 comments

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 · 8d agoAdvisory CVE-2026-15534 CVE-2026-19487

USN-8769-1: phpseclib vulnerability

Ubuntu patches phpseclib non-constant-time padding validation enabling remote padding oracle timing attacks against AES-CBC.

Ubuntu security notice USN-8769-1 addresses a vulnerability in phpseclib where padding validation was not performed in constant time when using AES in CBC mode. A remote attacker could leverage this timing side channel to conduct a padding oracle attack and decrypt sensitive information. Users are advised to update the phpseclib package.

Ubuntu Security NoticesSep 15, 15:59 UTC · 1d agoAdvisory

USN-8675-2: Perl vulnerabilities

Ubuntu issued USN-8675-2 fixing two Perl flaws (CVE-2026-12087, CVE-2026-13221) enabling information disclosure and regex-based security bypass on 26.04 LTS.

Ubuntu released USN-8675-2, extending the fixes from USN-8675-1 to Perl packages on Ubuntu 26.04 LTS. The update addresses CVE-2026-12087, an out-of-bounds heap read in the Socket module when handling short source addresses, which could lead to information disclosure. It also fixes CVE-2026-13221, where regular expressions containing many fixed string alternatives could produce incorrect matches and bypass security restrictions. No exploitation is reported in the notice.

Ubuntu Security NoticesSep 9, 14:10 UTC · 7d agoAdvisory CVE-2026-12087 CVE-2026-13221