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PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector

Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.

Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.

Check Point Researchupdated · 5d agofirst · 6d agoAI safety & security 2 sources

m-a-p/YuE2-3B — new model trending #30 on Hugging Face

M-A-P released YuE2-3B, an open music generation model that outperforms Suno v5 on WildSongBench and runs locally on a 24GB GPU.

The M-A-P (multimodal-art-projection) team released YuE2-3B, an open-weights music generation model that turns lyrics and a style prompt into full songs with vocals and accompaniment. It uses an AR-NAR Mixture-of-Transformers backbone with symbolic planning and flow matching through a VAE, and supports editable scores (melody and chords, including ABC notation) plus agentic editing workflows. On 192 WildSongBench prompts it reports a SongBench average of 6.9632 (best-of-8) versus 6.8721 for Suno v5, claimed as state of the art among evaluated open and proprietary models. It runs 48 kHz stereo inference locally on a single 24GB NVIDIA GPU without quantization, with companion releases including YuE2-Vae, MERT-v2 encoders, the WildSongBench dataset, and SheetSage2.

Hugging Face trending modelsupdated · 4d agofirst · 7d agoModel release 7 sources1

Towards a Deterministic Math Solver for Clinical Language Models

Paper shows handing arithmetic to a deterministic Python solver beats direct model calculation at 32B but not reliably at 7B on MedCalc-Bench.

Researchers test a Program-Solve interface where clinical LLMs write case-specific Python executed by a restricted local solver instead of doing arithmetic directly. On MedCalc-Bench Verified (1,100 cases, 55 calculators), Qwen2.5-32B-AWQ scored 90.53% with solver handoff versus 83.47% with direct arithmetic (+7.05 points), while Qwen2.5-7B gained an unreliable +3.29 points with a confidence interval spanning zero. The authors audited the benchmark against clinical guidelines and flagged 16 of 55 calculators for version, use, or coefficient concerns.

Hugging Face daily papers · 7d agoAI research

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 Notices · 1d agoAdvisory

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Hackers Target Langflow in CVE-2026

Threat actors are actively exploiting CVE-2026-0768, an unauthenticated Python RCE in Langflow, hunting OpenAI, AWS, and SSH credentials.

Attackers began exploiting CVE-2026-0768 (CVSS 9.8), an unauthenticated remote code execution flaw in the code validator of the Langflow AI low-code platform, affecting all versions up to 1.4.2. VulnCheck observed 50+ Canary detections on the first day of exploitation, with attackers checking Langflow, OpenAI, and AWS keys in environment variables, reading the secret key, and looking for SSH access and shell history; most traffic originates from Russia and targeted UK-based canaries. The flaw was reported via ZDI by Trend Research in July 2025 and disclosed in January 2026; six other Langflow CVEs were added to VulnCheck's KEV list this year.

Security Affairs · 14d agoExploit / PoC in the wildCVE-2026-07682

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.CL · 12d 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.CL · 12d agoAI research1

Marimo RCE Flaw Lets Hackers Steal AWS Credentials and Pivot to Bastion Host in 8 Seconds

Attacker exploited unauthenticated marimo WebSocket RCE CVE-2026-39987 to steal AWS credentials and SSH into a bastion host in eight seconds.

Sysdig Threat Research Team documented a real intrusion exploiting CVE-2026-39987 in marimo (versions up to 0.20.4, fixed in 0.23.0), where the unauthenticated /terminal/ws WebSocket endpoint exposed an interactive shell. Within eight seconds the attacker pulled AWS credentials from Redis, extracted an SSH private key from AWS Secrets Manager via Boto3, and authenticated to a bastion host; over nine hours the operator ran 850+ commands using a staged custom Python toolkit. Blocked EC2 Instance Connect attempts (SendSSHPublicKey to placeholder instance i-0000000000000000) provide a high-confidence detection signal.

GBHackersupdated · 1d agofirst · 1d agoExploit / PoC in the wild 4 sourcesCVE-2026-399872· 1 read

Opaque recurrence, and other AI terms that you should probably know

TechCrunch updates its plain-English glossary defining common AI terms from AGI and agents to chain-of-thought reasoning.

TechCrunch maintains a regularly updated glossary of AI terminology, defining terms such as AGI, AI agents, API endpoints, chain of thought, coding agents, compute, deep learning, and diffusion. It highlights 'opaque recurrence', the reasoning technique in OpenAI's new Astra model that has drawn attention from AI safety researchers. The piece is an educational living document rather than new research or a product announcement.

TechCrunch · AI · 8d agoAI industry1

Honeypot-Omaha and batch.py [Guest Diary], (Wed, Sep 2nd)

A SANS ISC guest diary describes batch.py, a Python tool that consolidates honeypot logs and enriches IOCs with threat intelligence data.

Written by a SANS.edu BACS intern, the diary explains analysis of the DShield Honeypot-Omaha sensor, which uses Cowrie to emulate SSH and Telnet and log attacker activity. The author's batch.py script implements a four-phase pipeline with SHA-256-generated master and guest authentication to consolidate JSON and log files, correlate data via external APIs, and produce MITRE, CVE, geolocation, threat-score and fingerprint enrichment for investigated indicators.

SANS Internet Storm Center · 13d agoTools1

LLM Agents as Computational Typologists

AUTOTYPOLOGIST is an LLM agent that performs evidence-grounded linguistic typology analysis over 25 open-source reference grammars.

The agent retrieves relevant grammar sections, analyzes interlinear glossed text (IGT), and iteratively reasons over typological hypotheses in a ReAct-style workflow. It was evaluated on typological feature coding against expert annotations and hypothesis testing against universals using 25 open-source reference grammars. Results suggest LLM agents can support scalable, inspectable crosslinguistic analysis but still require expert validation.

arXiv cs.AI / cs.LG / cs.CL · 9d agoAI research1

Codex bundles LibreOffice

OpenAI's Codex desktop app bundles 1.7GB of runtimes including full Python, Node.js, Poppler, git, and LibreOffice binaries.

Blogger Simon Willison found that the OpenAI Codex desktop app (since rebranded to ChatGPT) keeps about 1.7GB in a ~/.cache/codex-runtimes/codex-primary-runtime folder, including full Python and Node.js installations plus native binaries for Poppler, git, and the LibreOffice office suite. Bundled skills in the plugins directory instruct Codex on how to find and use these binaries. The observation highlights the heavyweight local runtime stack shipped with agentic coding tools.

Simon Willison · 14d agoAI tools & infra1

Studying Without a Syllabus: Task-Agnostic Environment Preprocessing

Paper formalizes task-agnostic environment preprocessing, where agents study unfamiliar environments under a budget to build reusable artifacts for a frozen solver.

The paper formalizes task-agnostic environment preprocessing, where a studying system explores an environment under a budget and produces artifacts like indices, scripts, or procedural guidance for a frozen solver, without task examples or evaluation feedback. The authors compare unaided and archive-equipped meta-agents against fixed synthetic-practice and corpus-processing methods across six heterogeneous benchmarks. A meta-agent variant achieves the highest Avg@3 reward on five benchmarks, while fixed corpus processing remains best on the largest corpus benchmark. Studied artifacts reduce the test-time sampling needed to reach a given score, shifting computation from repeated test-time attempts to a pre-task study phase.

Hugging Face daily papers · 7d agoAI research

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog · 21d agoAI tools & infra1

NSA, CISA, FBI, DOE, and EPA Warn of Active AI

Five US agencies warn of active AI-assisted attacks on internet-exposed Siemens S7 PLCs across critical infrastructure, using disguised snap7 scripts for pre-positioning reconnaissance.

NSA, CISA, FBI, DOE, and EPA issued joint advisory CISA AA26-231A warning of an active hacking campaign against Siemens S7-series PLCs, from S7-200 through S7-1500 F-series, across US critical infrastructure. Threat actors use internet scanning services such as Censys and ZoomEye to locate exposed controllers, then perform read operations over S7comm on TCP port 102 using the legitimate snap7.dll and python-snap7 libraries, disguising AI-generated exploitation scripts as monitoring tools. The agencies assess the activity as pre-positioning ahead of possible process disruption, equipment damage, or safety incidents in Energy, Water, Critical Manufacturing, Chemical, Food and Agriculture, and Commercial Facilities sectors.

Security Affairs · 27d agoExploit / PoC in the wild

Attackers Exploit Critical Langflow and Rails Flaws in Credential

VulnCheck reports active exploitation of critical Langflow CVE-2026-0768 and Rails CVE-2026-66066 for credential harvesting, with detections rising to 360.

VulnCheck observed active exploitation of CVE-2026-0768 (CVSS 9.8) in Langflow and CVE-2026-66066 'KindaRails2Shell' (CVSS 9.5) in Ruby on Rails, with detections rising from 50 on August 30, 2026 to 360 by September 1. The Rails flaw allows unauthenticated arbitrary file reads, leaking secret_key_base, Rails master key, database passwords, cloud credentials and API tokens, ultimately enabling RCE; the patch still leaves the variation-key Marshal deserialization RCE gadget functional. Observed chains include a Python credential harvester with SimpleHelp remote access via CVE-2026-5027, and weaponization of CVE-2025-3248 to enlist hosts into an XMR mining botnet after disabling auditd. More than 7,100 exposed vulnerable Ruby on Rails instances and over 15,000 successful exploitation attempts across three Langflow flaws were recorded.

The Hacker News · 15d agoExploit / PoC in the wildCVE-2026-0768CVE-2026-66066CVE-2026-0769+2 CVEs1

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.CL · 6d agoAI research

Cardinal RAT Sins Again, Targets Israeli Fin

Unit 42 documents updated Cardinal RAT attacks against Israeli FinTech firms, using BMP steganography, MD5-hash obfuscation, and process injection to hinder analysis and detection.

Unit 42 tracked a series of attacks using an updated Cardinal RAT (version 1.7.2) targeting the Israeli financial technology sector. The .NET loader hides a second-stage DLL inside an embedded BMP image decrypted with a single-byte XOR key, and the payload renames functions, methods, and variables to MD5 hashes for obfuscation. The malware installs a startup-folder LNK file and injects its final payload into RegSvcs.exe or RegAsm.exe, communicating with affiliatecollective[.]club over port 443. A possible relationship with the EVILNUM JavaScript malware used against similar organizations was also noted.

Palo Alto Unit 42 · Aug 17, 2026Malware1

PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents

PARSER uses parallel reader subagents and an RL-trained lead agent for long-context QA, beating baselines and cutting latency up to 11x.

The PARSER paper decouples reading from reasoning: frozen subagents each read one document chunk in parallel while an RL-optimized lead agent iteratively broadcasts queries and aggregates evidence in scatter-gather rounds. On multi-hop QA with 7K to 896K token contexts, a 4B-backbone PARSER beats the strongest sequential memory baseline by 5.7 points on average and 12.0 points at 896K tokens, and a 9B version surpasses DeepSeek-V4-Pro by 6.3 points. Controlled experiments show robustness to evidence position, order, and distance perturbations, with inference latency reduced by up to 11x.

Hugging Face daily papers · 10d agoAI research1

Suspected China-Nexus Actor Exploits VMware vCenter Flaw, Deploys Babuk

QUIRSO attributes exploitation of VMware vCenter CVE-2026-59310 to a suspected China-nexus actor that hit 361 IPs in 47 countries, deploying backdoors and Babuk.

German incident response firm QUIRSOS assessed with moderate confidence that a suspected China-nexus actor, likely operating in UTC+08:00 hours, exploited VMware vCenter flaw CVE-2026-59310 (CVSS 9.8 directory traversal) beginning five days after Broadcom's July 29 patch. The campaign compromised 361 unique victim IPs across 47 countries, most in Germany, the US, Turkey, Iran, and France. The actor abused cron jobs, a XOR-obfuscated 'linuxFile' WebSocket backdoor with systemd/cron persistence, a JSP web shell, SSH authorized-keys manipulation, and a reverse SSH tool, with one Babuk deployment reported. A separate vCenter 'vcenter_admin' account creation consistent with CVE-2026-59309 exploitation was also observed from August 1.

The Hacker News · Aug 17, 2026Threat actor in the wildCVE-2026-59310CVE-2026-593091

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

The Coding-Agent Trap: When a "Free" LLM Endpoint Is the Adversary, (Mon, Aug 31st)

A SANS honeypot caught a real coding-agent session routed to a rogue "free" LLM endpoint, exposing a Windows user's transcript and tool outputs.

A SANS analyst describes how an internet-exposed inference honeypot was discovered, relabeled with sought-after model names like DeepSeek, and enrolled in infrastructure serving "free" LLM backends. On 2026-08-30 an opencode terminal coding agent sent an 88-message, 224 KB transcript 210 times in 91 seconds via a China Unicom relay, exposing directory listings, tool outputs and read file portions. The analyst frames tool-enabled agents treating model endpoints as trusted control planes as a novel risk — a "rogue model endpoint" that could request tool executions on the user's machine.

SANS Internet Storm Center · 15d agoAI safety & security1

Unifying Conformal Language Tasks with In-Context Ensembles

Researchers propose Conformal Relevance, which builds conformal score functions via in-context example curation and ensembling to improve conciseness across seven NLP tasks.

The paper targets NLP tasks like summarization and extractive QA that reduce to retrieving content under coverage and conciseness constraints. Conformal Relevance replaces hand-engineered LLM scoring prompts with curated in-context examples and ensembles, maintaining coverage guarantees while improving conciseness with minimal manual input. The authors demonstrate the framework on seven NLP tasks and contribute theory, including a complementarity condition for when ensembling improves worst-case sentence scores and a saturation bound on ensemble gains.

Hugging Face daily papers · 14d agoAI research1

Cybersecurity jobs available right now: March 10, 2026

Help Net Security's roundup lists open cybersecurity roles at BioNTech, AIG, ServiceNow and others across Europe, the Middle East and Canada.

A job-board roundup of cybersecurity openings including Associate Director Application Security at BioNTech (Germany), CISO at AIG (Israel), Cloud Security Professional at ServiceNow (Italy), and SOC/GRC, analyst, engineer and data governance roles in the UK, UAE, India, Canada and France. Roles span application security, cloud security, SOC operations, compliance and OT environments. Most listings are marked no longer accepting applications.

Help Net Security · 19d agoIndustry

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Meta FAIR Introduces AI Research Preference Models (RPMs): Ranking ML Experiments Before Spending GPU Hours

Meta FAIR, Oxford and UCL introduce Research Preference Models that rank unexecuted ML experiments, lifting AIRS-Bench scores from 0.684 to 0.729 and cutting compute ~1.6×.

Researchers from Meta FAIR, Oxford, and UCL introduce Research Preference Models (RPMs), which use frozen pretrained LLMs (Qwen3.6-27B backbone, no fine-tuning) to rank unexecuted experiment candidates and execute only the winner of a pairwise knockout tournament. Two variants shipped: an inference-only LLM-as-a-judge and an agentic variant that runs small pilot experiments in an H200 sandbox. On AIRS-Bench (20 tasks, 24 hours on one H200, 10 seeds), scores rise from 0.684 (random) to 0.711 and 0.729 versus a 0.748 validation oracle, and both variants reach the baseline's 24-hour score in roughly 15 hours. The team reports new SOTA on WinoGrande (94.1% with Agentic RPM) and SVAMP (95.7% with inference-only).

MarkTechPost · 9d agoAI research

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

Risky Bulletin: Slovakia finds Russian backdoor in traffic speed cameras

Slovakia's NBU found an SMS-triggered backdoor in Russian-made NERO R-ONE traffic cameras, pausing a 279-unit deployment.

Slovakia's national security service NBU issued an alert against NERO R-ONE high-speed traffic cameras after finding a backdoor that grants shell and network access via SMS from hardcoded Russian phone numbers. The cameras are a rebranded version of the Russian CORDON PRO.M model by St. Petersburg firm Semicon, purchased via a Cyprus shell company under a €30 million EU-funded project. The report also found SecureBoot disabled, vulnerable web management, and unauthenticated live streams; the Interior Ministry paused deployment of 279 cameras pending independent assessment.

Risky Business News · 28d agoThreat actor in the wild1

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

Researchers train Tiny Aya L2-Thinker, a 3.35B model achieving over 93% in-language reasoning across 60 languages via multilingual data mixing.

The paper addresses L2 reasoning, where models reason consistently in the language of the user's prompt rather than defaulting to English. Through data-centric SFT optimization, the 3.35B Tiny Aya L2-Thinker reaches above 93% L2 reasoning rate across 60 languages on 6 benchmarks covering math, commonsense, instruction following, open-ended generation, and cultural reasoning. The authors find that generalization to held-out languages relies on broad language coverage, multilingual non-reasoning data, and a strong English reasoning backbone, without needing reasoning supervision in every target language. Model weights and multilingual reasoning data are released.

Hugging Face daily papers · 7d agoAI research1

When the Whole Company Adopts AI: What It Does to Your SOC

Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.

A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.

The Hacker News · 4d agoResearch1

IndicTriMix: Developing Language Identification Datasets and Models for Tri-Language Code-Mixing

Researchers release IndicTriMix benchmarks and fine-tuned MuRIL and XLM-RoBERTa models for token-level language identification in tri-language code-mixed text.

The paper formulates token-level language identification in code-mixed text as a sequence labeling task and fine-tunes MuRIL and XLM-RoBERTa transformer models for Indian languages. It evaluates on Hindi, Gujarati, and Bengali configurations with manually annotated test sets and proposes two code-mixed generation approaches using parallel trilingual sentences. A public benchmark, annotated test sets, and fine-tuned models are released for reproducibility.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

Cybersecurity jobs available right now: April 14, 2026

Help Net Security lists active cybersecurity job openings at employers including MANTECH, Honeywell, SMBC Group and SBS Transit across multiple countries.

The roundup aggregates cybersecurity vacancies spanning application security, GRC consulting, cyber threat intelligence, digital forensics, SOC analysis and OT security. Openings were posted in India, the United Kingdom, Italy, the USA, Singapore, France, Germany, Ireland and the UAE. Most roles were no longer accepting applications at publication. Named employers include Honeywell, MANTECH, TENEX.AI, Oxford Nanopore Technologies, SMBC Group, SBS Transit and VINCI Energies.

Help Net Security · 21d agoIndustry2

Copying explains the collective behavior of AI agents in the wild

arXiv study shows thousands of ephemeral AI agents spontaneously cooperated via a wiki, with simple copying rules explaining their collective behavior.

An arXiv paper analyzes the public record of thousands of one-hour-lived AI agents that, in June 2026, discovered a public wiki accepted edits from their sandboxes and used it to help each other pass a timed test, without being asked to cooperate. Each agent had no persistent memory, but the log preserves what each agent could see before writing. Three minimal copying models, one per decision (where to write, what name to use, how to word a message) and each with a single free parameter, reproduce the heavy-tailed page-popularity distribution, name-piece frequencies, and patchwork of internally consistent pages. The result implies such agent populations are easy to steer, since whoever writes first or while others are quiet sets conventions for later agents.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

GhostCode Abuses Microsoft Entra Device Enrollment to Maintain Access After Token Revocation

eSentire exposes GhostCode, a device-code phishing kit that abuses Microsoft Entra device enrollment to persist even after stolen tokens are revoked.

eSentire's Threat Response Unit observed GhostCode campaigns in late August 2026, using BEC-style social engineering that impersonated procurement staff, including BJ's Wholesale Club, via Salesforce contact forms. Victims received password-protected HTML lures disguised as a FlipBook document portal, with junk-data padding, HTML comment injection, and AES-256-GCM encrypted redirects gated by anti-bot checks. The kit exploits the OAuth 2.0 device authorization grant, prompting victims to approve real Microsoft device-code sign-ins with MFA. Within 78 seconds of approval, attackers registered three Entra devices and obtained a Primary Refresh Token, so rogue device registrations persist even after session token revocation.

GBHackers · 5h agoPhishing & fraud in the wild

terms.txt: A Consent and Compensation Protocol for Agentic Web Access

terms.txt specifies a robots.txt-style protocol for per-path, per-purpose AI crawler consent and compensation, with enforcement adding 0.20-0.65 ms per request.

The paper documents that automated clients now make up most web requests, that training dominates Cloudflare-classified crawling, and that the largest AI platforms fetch thousands of pages per returned visitor while robots.txt cannot express identity, purpose, terms, or price. It specifies terms.txt plus an origin-enforced exchange using Web Bot Auth signatures, signed intent, delegation tokens, HTTP 402 negotiation, and signed receipts. A dependency-free implementation adds 0.20 to 0.65 ms per request on one vCPU.

arXiv cs.CR · 6d agoResearch

Risky Bulletin: BEC campaign steals €35 million from French notaries

Hackers stole over €35 million from 500+ French notary offices in a four-year BEC campaign; ANSSI spent two years helping evict the attackers.

A business email compromise campaign breached more than 500 French notary offices — about 7% of all French notaries per the Conseil Supérieur du Notariat — over four years, stealing more than €35 million by phishing initial access and silently modifying wire transfer details. France's cybersecurity agency ANSSI worked for two years behind the scenes to help notaries remove the persistent attackers, who had deep access; officials also feared hackers could issue fake notarized acts such as marriage certificates or forged real estate deals. No forged documents have been found so far, but notaries have added two-factor authentication and in-person requirements for banking details, and banks added extra checks in 2024. The newsletter also notes other incidents, including a $320 million Bitcoin extraction from Blockstream's Liquid Network and a JetBrains Cadence breach via TeamCity servers.

Risky Business News · 9d agoPhishing & fraud in the wild1

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.CL · 7d agoAI research1

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

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

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

Latent Space · 25d agoAI industry