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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 CenterAug 31, 20:00 UTC · 15d agoAI safety & security1

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 · AISep 7, 19:24 UTC · 8d agoAI industry

CVE-2026-82427: Apache Storm Nimbus: Path Traversal as the Supervisor User via Unsanitised Blobstore Map Local Name

Unsanitised topology.blobstore.map local names in Apache Storm enable path traversal writes on supervisors as the supervisor user.

CVE-2026-82427 affects Apache Storm Nimbus (org.apache.storm:storm-server) versions 3.0.0 before 3.1.0, rated important. Topology submitters can choose a local name for each blob in topology.blobstore.map, which AsyncLocalizer and Container.createBlobstoreLinks used to build paths under the topology's working directory without normalisation. Crafted names allow path traversal, letting a submitter create or overwrite files outside the intended directory on supervisors, with symlink handling also affected. Fixed in version 3.1.0.

oss-securitySep 13, 14:21 UTC · 3d agoVulnerability CVE-2026-82427

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.CLSep 4, 16:38 UTC · 11d agoAI research

UBoatRAT Navigates East Asia

Unit 42 discovers UBoatRAT, a new custom RAT targeting South Korean and video-game industry personnel, delivered via Google Drive with GitHub-based C2 and BITS persistence.

Unit 42 identified UBoatRAT, a new custom remote access trojan first found in May 2017, whose initial version used a public Hong Kong blog service and a compromised Japanese web server for command and control. The latest variants target personnel or organizations related to South Korea or the video games industry, are delivered through Google Drive, and masquerade as Microsoft Word, Excel, or folder icons. The RAT checks for virtualization software and domain join, retrieves its C2 address from a Base64-encoded string in a GitHub-hosted file, uses a custom XOR-encrypted C2 protocol, and maintains persistence via Windows Background Intelligent Transfer Service (BITS) jobs that survive reboots.

Palo Alto Unit 42Aug 17, 12:55 UTC · Aug 17, 2026Malware in the wild1

Do speech foundation models really learn words?

Researchers show via residualization that later layers of HuBERT and wav2vec 2.0 encode word identity and semantics independently of phonetic content.

The study argues that discriminative ability on words does not imply specialized word representations, since good word discrimination can be explained by phoneme encoding alone. By partialling out phoneme information using residualization, the authors show that later layers of HuBERT and wav2vec 2.0 encode words with reasonable fidelity independently of local phonetic content. Applying this disentanglement approach enhances higher-order linguistic information in word discovery tasks, informing analysis of speech foundation models used for recognition and speech tokens.

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:47 UTC · 6d agoAI research

Cyble Introduces Major Upgrade to its Executive Monitoring Module

Cyble upgraded Executive Monitoring in Cyble Vision, unifying impersonation, exposure, and mention findings with AI scoring and multi-channel alerting.

Cyble released a major upgrade to Executive Monitoring within its Cyble Vision platform, consolidating Mentions, Impersonations, Exposures, and a new Surface Mentions source (blog and news coverage) into a single findings stream. The release adds AI-generated verdicts and recommendations, per-executive Risk and Reputation scoring for board reporting, and richer onboarding with aliases, reference images, and addresses to cut same-name false positives. Alerting now supports data residency, bulk import, delivery via email, WhatsApp, and SMS, an Access API, and branded executive PDF reports; the upgrade is live with no customer action required.

CybleSep 10, 12:26 UTC · 6d agoTools

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

How to Spot and Stop Rogue Device Joins

Wiz details how adversaries use realistic device names in Entra ID registrations to evade detection and which behavioral signals still expose them.

Wiz researchers describe how adversaries generate realistic device names during Entra ID device registration instead of leaving recognizable fingerprints from public tooling, making rogue device joins blend into enterprise environments. The post explains how this trend changes Entra ID detection approaches. It also identifies behavioral signals that still expose these attacks. No specific CVE or victim was named.

Wiz BlogAug 18, 16:24 UTC · 28d agoResearch in the wild

Diffusion Models and Concept Formation

Paper argues diffusion models implicitly form Cobweb-like concept hierarchies, with a basic level emerging at intermediate noise levels.

The authors draw a formal correspondence between diffusion models and Cobweb, a classic incremental concept-hierarchy learner, noting both are hierarchical Bayesian density models with Gaussian prototypes. Modes of the diffusion model's noisy marginals form a hierarchy whose basic level sits at intermediate noise, where class identity commits. The correspondence is tested on MNIST and Fashion-MNIST via mode-finding. Diffusion is reframed as a cognitive model of concept formation.

arXiv cs.AI / cs.LG / cs.CLSep 11, 16:43 UTC · 4d agoAI research

Revolut Exposed KYC Data After Fraudulent Government Email Passed Security Checks

Revolut handed over KYC documents, selfies, and Bitcoin transaction histories to attackers after a fraudulent email from a genuine government domain passed authentication checks.

Revolut confirmed on September 12, 2026 that it disclosed sensitive customer KYC data to an unauthorized third party after a fraudulent information request was sent from an email account operating inside a real government agency's domain, carrying valid domain authentication credentials. The exposed data included identity documents (passports, driver's licenses), verification selfies, birth dates, contact details, IBANs, account statements, and full transaction histories including Bitcoin. Revolut discovered the fraud only after independently verifying with the agency, blocked the sender, and notified law enforcement and financial regulators, but did not disclose the number of affected customers or the agency involved. Researcher ZachXBT assessed the operation was targeted at high-net-worth users, useful for fraud, impersonation, or extortion.

Security AffairsSep 12, 21:05 UTC · 3d agoData breach

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 · 22h agoAI research

NASA AIT-GUI Flaws Could Let Unauthenticated Attackers Issue Spacecraft Commands

Researchers disclosed 9.4-CVSS flaws in NASA/JPL's AIT-GUI allowing unauthenticated attackers to issue arbitrary spacecraft commands via exposed command endpoints.

Cycode disclosed a flaw chain in AIT-GUI, the browser-based operator console for NASA/JPL's open-source AMMOS Instrument Toolkit, tracked as GHSA-p9r8-2q67-fp86 with CVSS 9.4, affecting versions 2.5.1 and earlier. The server binds to 0.0.0.0:8080, issues sessions without credential checks, and lets unauthenticated users issue spacecraft commands via POST /cmd and reach files outside intended directories via /script/run and /seq (CWE-306, CWE-352, CWE-22). Version 2.5.2 adds host binding and same-origin checks but does not add authentication, and a related missing-authentication flaw was published separately as CVE-2026-60112 with CVSS 9.3.

The Hacker NewsAug 20, 17:20 UTC · 26d agoVulnerability CVE-2026-601121

Can Edge-Deployable Vision-Language Models Identify Species?

Evaluation of 2-8B VLMs (Qwen3-VL, Gemma3) against BioCLIP on camera-trap species ID shows all models degrade sharply on field imagery.

The study tests whether edge-deployable 2-8B vision-language models carry genuine taxonomic knowledge, comparing Qwen3-VL 2B/4B/8B and Gemma3 4B against the 300M specialist BioCLIP on a 96-species task across clean iNaturalist photos and six LILA.science camera-trap collections. All models degrade 9.6-26.6 percentage points on field imagery, and BioCLIP outperforms every VLM by 33.2-59.2 points on an expanded 200-image sample, suggesting specialized data rather than scale drives the gap. Under open-set prompting, 5.9-9.6% of responses are syntactically valid but taxonomically nonexistent species names, with fabrication rankings replicating across evaluation sets.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:57 UTC · 5d agoAI research1

220 million traveler records exposed in Vietnam-linked APIS leak

Vietnam-linked APIS Elasticsearch leak exposed 220 million passenger and crew records with passport numbers and flight details spanning 2017 to 2026.

Kinryū Labs discovered an exposed Elasticsearch cluster named 'pax-info' holding 210,318,069 passenger records and 10,465,631 crew records (roughly 107 GB across 29 indices) hosted in Viettel-assigned IP space in Hanoi. The database, apparently operated by a Vietnamese organization, was reachable via a chain of two misconfigurations: a cloud-based path that bypassed an HTTP 401 block and acceptance of default credentials. Exposed data included names, dates of birth, nationalities, passport numbers, and detailed flight information for travelers of many nationalities from January 2017 to April 2026. Access was remediated on June 8 after Kinryū Labs notified Vietnamese authorities, airlines, and CERTs, with Singapore Airlines' security team helping coordinate the response; it remains unknown whether any data was copied by malicious actors.

BleepingComputerSep 8, 07:35 UTC · 8d agoData breach1

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.CLSep 10, 17:36 UTC · 5d agoAI research1

Agents Gone Wild: An AI-Orchestrated Global Campaign Against PaperCut NG/MF

AI-orchestrated campaign exploited PaperCut NG/MF RCE (CVE-2026-81578/82078), compromising 440+ instances at 395 organizations in 48 countries.

GreyNoise tracked a likely Russian-speaking actor using AI (OpenAI Codex harness plus a DeepSeek model) to develop, test, and deploy exploits for PaperCut NG/MF (CVE-2026-81578, CVE-2026-82078) starting 31 August 2026. The actor compromised at least 440 PaperCut instances across 395 organizations in 48 countries, achieving domain admin at 12 victims — fastest time to domain admin was five minutes and a US high school was fully compromised in seven minutes. Attack paths involved LSASS memory and registry secret harvesting, pass-the-hash to domain controllers, noPac attacks, account additions to Domain Admins, and DCSync to exfiltrate full NTDS.DIT credential dumps. Impact scope suggests access development potentially for handoff, with prior PaperCut intrusions historically leading to extortion.

GreyNoiseSep 9, 00:00 UTC · 7d agoThreat actor in the wildCVE-2026-81578 CVE-2026-82078 CVE-2021-42278+1 CVEs1

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

Hackers Target Claude, Cursor and Codex AI Agents to Steal Tokens and Prompt Histories

Gen Digital found infostealers like Amatera and Remus stealing AI coding agent tokens, prompt histories, and MCP configs from infected Windows and macOS machines.

Gen Digital analysts observed Amatera and Remus detections among tens of thousands of protected Windows users over three months, with Amatera targeting Cline and Continue data and Remus targeting Claude, Cursor, and OpenCode. CallbackBeaver added Cursor and Claude to its collection scope with more than 5,000 samples in 30 days, while macOS-focused Djinn Stealer has been associated with Claude, Codex, Gemini, Cline, OpenCode, and Kilo. The stealers harvest access and refresh tokens, prompt histories, and MCP configuration files that can expose source control, ticketing, databases, cloud resources, and sensitive project context for follow-on fraud. Many stealers add targets via remotely managed rules, meaning this is an adaptation of existing infostealers rather than a new vulnerability in the AI tools themselves.

Cyber Security NewsSep 9, 11:41 UTC · 7d agoMalware in the wild2

Fortunate Recall: Ontology-Driven Memory Lifecycle Management for Persistent Coherence in LLMs

Fortunate Recall introduces ontology-based lifecycle policies for LLM memory, cutting confabulation roughly in half (e.g., 45.1% to 22.4%) versus Mem0.

Fortunate Recall (FR) is a composable policy layer that classifies personal facts into a 10+1 behavioral ontology and applies category-specific lifecycle rules including differential temporal decay, slot-key supersession, event-time validity, and retrieval routing. FR-Bank scores 76.9% on the new 516-question LifecycleBench, ahead of Mem0, A-MEM, Memory-R1, and MemoryOS (61%-70.5%), and 75.2% on LongMemEval-S. End-to-end, confabulation drops from Mem0's 45.1% to 22.4% over answered queries, with the ranking replicating on open-weight Kimi K2.5 and transferring to the independent BEAM benchmark (46.8% vs 32.9%).

arXiv cs.AI / cs.LG / cs.CLSep 9, 16:31 UTC · 6d agoAI research

Kraken: LLM-based Speech-to-Speech Translation via Low-bitrate VQ and Dual-path Source Conditioning

Kraken speech-to-speech translation model builds on Qwen3-8B with low-bitrate vector quantization and source-conditioned vocoding.

Kraken augments a pre-trained Qwen3-8B LLM with speech feature inputs and low-bitrate single-layer vector-quantized tokens trained to reconstruct SSL features. A separate token-to-waveform decoder, Autowave-X, is conditioned on source speech to improve non-linguistic transfer. Training used 150k hours of multilingual and multitask speech data. The model reportedly beats SeamlessM4T-Large v2 and Qwen2.5-Omni in translation quality and speaker/prosody transfer.

arXiv cs.AI / cs.LG / cs.CLSep 11, 16:41 UTC · 4d agoAI research1

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

New KATARU IoT Malware Packs Linux Privilege Escalation Exploits and Mirai-Style DDoS Attacks

Nozomi Networks identified KATARU, a new Mirai-style IoT botnet delivered via Telnet brute force that uses Linux privilege-escalation exploits and encrypted C2 for DDoS floods.

Nozomi Networks identified KATARU in August after a Telnet password-guessing attack against a honeypot retrieved an ARM payload. The malware attempts exploits for CVE-2026-46300 (Fragnesia), CVE-2026-43284 (DirtyFrag), and CVE-2026-31431 (Copy Fail), plus a cgroup v1 release_agent escape, and persists via systemd services, cron tasks, rc scripts, OpenWrt hooks, and Android boot locations. Its C2 uses X25519 key exchange with ChaCha20-Poly1305 encryption and supports TCP, UDP, ICMP, HTTP, QUIC, and DNS floods, plus SSH brute forcing and command execution; embedded exploit shellcode in the ARM build targeted x86, suggesting untested copied code.

Cyber Security NewsSep 11, 14:17 UTC · 5d agoMalware in the wild 2 sources CVE-2026-46300 CVE-2026-43284 CVE-2026-31431

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

Training-free reasoning-plus-retrieval framework lifts multilingual multimodal entity linking accuracy by 6.9% overall and up to 23.3% on rare entities.

The paper broadens rarity measurement in multimodal entity linking using knowledge-graph structural metrics beyond popularity-based pageview metrics, identifying many rare entities that popularity metrics miss. Across these rare-entity slices, state-of-the-art accuracy drops by 15.4-39.9%, exposing distinct failure modes under different rarity definitions. The proposed training-free framework iteratively searches and reasons over Wikipedia with a reasoning-capable vision-language model; experiments show reasoning and retrieval are complementary. On the MERLIN benchmark covering Hindi, Indonesian, Japanese, Tamil, and Vietnamese, the system improves overall accuracy by 6.9% and up to 23.3% on rare entities, with MERLIN-Rare test slices released.

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

Berlin investigates new data leak after hackers publish stolen login credentials

Berlin investigates a fresh leak after Rhysida hackers published stolen login credentials; the city refuses to pay the ransom demand.

Berlin confirmed hackers published additional stolen data, including login credentials, from a mid-August cyberattack on two city ministries responsible for urban development/housing and transport/climate. The Rhysida ransomware group claimed the breach in late August, saying it stole 5.79 TB of data including contracts, emails, passwords and classified information; Berlin acknowledged an extortion demand but refused to pay. Berlin's data protection regulator said the leak includes personal data on public employees and possibly residents, such as names, addresses, dates of birth and bank information. Germany's BSI separately linked the campaign to the TerminalFix fake-CAPTCHA technique and the LoremIpsumLoader/AxolotLoader malware tied to financially motivated Rhysida-associated hackers, days before Berlin's Sept. 20 election.

The RecordSep 7, 11:50 UTC · 9d agoRansomware in the wild1

Thought without systematicity? Evaluating reasoning models on rule induction tasks

Study finds reasoning models often fail on structurally equivalent variants of tasks they solve, suggesting their reasoning lacks systematicity.

The paper extends rule induction tasks from cognitive science using task isomorphisms such as recombination and substitution to test systematicity in reasoning models. Despite solving tasks correctly, models frequently fail on structurally equivalent variants of the same task. The authors conclude many model behaviors lack systematicity, making it difficult to establish cognitive abilities beyond the specific evaluation contexts.

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

Arrested man allegedly impersonated NSA elite hacking unit, Supreme Court chief justice

Colorado man Joshua Culver indicted for impersonating NSA's Tailored Access Operations chief and Supreme Court Chief Justice John Roberts in Indiana court cases.

Joshua Culver, also known as Maverick Young, was arrested in Colorado after a July Indiana indictment on four counts of falsely impersonating an officer of the court and one count of using a forged judge's signature. He allegedly posed as an NSA officer in September to pressure the Tippecanoe County sheriff's office, and later presented a forged document purportedly from the head of the Tailored Access Operations unit demanding case dismissal and warrant quashing. The indictment also alleges he used a forged signature of Chief Justice John Roberts on a dismissal order in Grant County, Indiana.

CyberScoopAug 25, 18:43 UTC · 21d agoPolicy & legal2

AI models' written reasoning steps correspond to distinct internal patterns, a new study finds

KAIST and Naver AI Lab researchers show LLM reasoning steps like extraction and computation map to distinct activation patterns, strongest in middle layers.

Researchers at KAIST and Naver AI Lab defined eight recurring reasoning operations, including extraction, decomposition, formula recall, deduction, and computation, and showed they correspond to separable activation patterns in Qwen2.5-7B, Qwen3-8B, and Gemma4-31B on math tasks, with GPT-5 labeling solution segments. The separation peaks in middle layers, holds even when a computation step produces a wrong answer, and goes beyond surface-level token choice. Findings replicated on Llama-3-8B, and classifiers trained on Qwen3-8B transferred to GPQA-Diamond and MATH-500. The authors note that using internal states for error detection or mid-generation steering remains future work.

The DecoderSep 12, 13:39 UTC · 4d agoAI research2

When AI Agents Go Rogue: Agent Session Smuggling Attack in A2A Systems

Unit 42 unveils agent session smuggling, where a rogue AI agent hides covert instructions in established Agent2Agent (A2A) protocol sessions to manipulate victim agents.

Palo Alto Networks Unit 42 discovered agent session smuggling, a new attack technique in which a malicious AI agent exploits an established cross-agent session under the Agent2Agent (A2A) protocol to send covert instructions hidden among benign client requests and server responses. The technique leverages the implicit trust agents place in collaborating agents and the stateful, multi-turn nature of A2A sessions; the researchers stress it affects any stateful protocol, not an A2A flaw. Unlike one-shot data-based attacks, a rogue agent can converse, adapt and build false trust over multiple interactions. Proposed mitigations include human-in-the-loop enforcement, cryptographically signed AgentCards for remote agent verification, and context-grounding to detect injected instructions.

Palo Alto Unit 42Aug 17, 12:32 UTC · Aug 17, 2026AI safety & security2

MAxBench: A Multinomial Concept Recovery Benchmark

MAxBench evaluates multinomial concept recovery methods, finding affine subspaces steer most reliably but none consistently beats prompting.

MAxBench is a geometry-agnostic evaluation framework for multinomial concept representations in language models, based on sampling from recovered concept representations. It compares 10 localization methods covering 5 geometry types across 6 concepts and 4 models. Findings show affine subspaces steer more reliably than rank-one or linear subspaces due to better non-zero offsets, manifold steering is competitive where applicable, and no method consistently outperforms prompting.

arXiv cs.AI / cs.LG / cs.CLSep 11, 17:08 UTC · 4d agoAI research

Horizon3 Announces Integration with CrowdStrike Falcon® Next-Gen SIEM

Horizon3 announces NodeZero integration pushing validated exposure findings into CrowdStrike Falcon Next-Gen SIEM for correlated investigations.

Horizon3 announced an integration enabling validated NodeZero findings to flow into CrowdStrike Falcon Next-Gen SIEM, available now in the CrowdStrike Marketplace. Security teams can ingest and correlate exposure data with endpoint, identity, cloud, and other telemetry during investigations. CrowdStrike claims Falcon Next-Gen SIEM delivers up to 150x faster search than legacy SIEMs at up to 80% lower total cost of ownership.

Horizon3.aiSep 15, 13:10 UTC · 1d agoTools

Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

A controlled pure-autoregressive testbed shows task-specific validation losses rank image tokenizers differently, with I2T loss the most consistent signal.

Researchers built a controlled pure-autoregressive testbed and tracked task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They find losses should be analyzed per task because they exhibit distinct scaling behavior and rank tokenizers differently, and that the loss-performance relationship depends on the predicted token space. I2T loss, computed over a shared text vocabulary, correlates consistently with both generation and visual understanding performance after supervised finetuning. Case studies revisit the discriminator, semantic supervision, and vocabulary size as tokenizer design axes.

arXiv cs.AI / cs.LG / cs.CLSep 8, 17:57 UTC · 7d agoAI research1

Seattle Times and Newsday sue OpenAI and Microsoft for infringement

The Seattle Times and Newsday sued OpenAI and Microsoft for copyright infringement, seeking destruction of datasets and models trained on their journalism.

The Seattle Times and Newsday allege OpenAI used their journalism as training data without permission and that its chatbots reproduce passages of their reporting, seeking destruction of copies of their works, training datasets, and AI models that incorporate them. Microsoft is named as co-defendant because Copilot is built on OpenAI technology. The suit follows similar actions by The New York Times, Ziff Davis, Merriam-Webster, Encyclopedia Britannica, and nearly 400 local newspapers.

The Verge · AISep 6, 23:36 UTC · 9d agoAI policy1

Beneath the Surface of Chains-of-Thought: A Mechanistic Interpretation of Reasoning Operations in LLMs

Study shows LLM reasoning operations like planning and deduction are geometrically separable in hidden states, with separability peaking in middle layers.

Researchers investigate whether functional reasoning operations — problem formulation, goal decomposition, deduction — have corresponding geometric structure in LLM hidden representations. They find operations are separable in held-out representations with separability peaking in middle layers, ruling out lexical and positional confounds; token-wise operation alignment becomes more distributed across layers, and identical surface tokens are represented differently depending on their surrounding chunk. Attention-masking interventions show chunk-onset operation-aligned representations depend on preceding reasoning context; code is released on GitHub (naver-ai/beneath-cot).

Hugging Face daily papersSep 3, 20:00 UTC · 12d agoAI research1

Hackers Can Hide Malicious AI Commands Inside Normal English to Bypass Security Filters

Check Point's PuzzleMask technique hides malicious prompts in ordinary English that fast gatekeeper models miss but high-reasoning downstream models execute.

Check Point researchers disclosed PuzzleMask, a technique concealing policy-breaking instructions in natural-language prose without encodings or invisible characters. Fast screening models classified all 23 crafted wrappers as safe, while a high-reasoning model recovered and acted on the hidden instruction in 17 of 18 tests (94.4%). The gap stems from capability imbalance between gatekeeper and target models, with defenses including paraphrasing untrusted input, stricter self-referential wording rules, and output/tool-call monitoring.

Cyber Security NewsSep 11, 07:36 UTC · 5d agoAI safety & security1

Does Syntax Matter? A Graph-Augmented Variational Topic Model for Computational Social Sciences

SCPTM graph-augmented variational topic model shows syntax aids topic diversity and descriptor quality but gains stem mainly from the variational encoder.

The Structural Contextual Probabilistic Topic Model represents corpora as heterogeneous document-word graphs with lexical and syntactic edges processed by a Graph Attention Network inside a VAE for mixed-membership topic distributions. Across four corpora, neural gains in document-topic alignment are attributable to the variational encoder rather than syntax, while graph-augmented variants improve topic diversity everywhere. Dependency paths add value on argumentative deliberative texts but are redundant in technical and institutional registers.

arXiv cs.AI / cs.LG / cs.CLSep 7, 17:39 UTC · 8d agoAI research

Switching Password Managers in 2026

An Apple password-management engineer (writing personally) explains switching password managers via iOS direct app-to-app export, crediting FIDO Credential Exchange for passkey portability.

Ricky Mondello, an Apple engineer in password management and authentication (writing personally, not for Apple), demonstrates moving 100 items from 1Password to Apple Passwords via the iOS system export, which transfers passwords, passkeys, verification codes, and notes directly between apps with Face ID confirmation and no intermediate files. He credits the FIDO Alliance's Credential Exchange format (first draft May 2024, now an open spec) and iOS 26/macOS 26 for enabling phishing-resistant credential transfer between apps like 1Password, Bitwarden, Dashlane, DuckDuckGo, and Devolutions. The post is advice rather than news, recommending bulk transfer on the existing device, switching AutoFill to the new app, and treating the new manager as the source of truth.

Lobsters · securitySep 8, 13:55 UTC · 8d agoIndustry1

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.CLSep 7, 17:35 UTC · 8d agoAI research1

Delta investigates in-flight Wi-Fi spoofing on post

A passenger on Delta flight 591 allegedly spoofed the airline's in-flight Wi-Fi with a rogue access point, prompting an FBI and FAA investigation.

Delta Airlines is investigating an incident on flight 591 from Las Vegas to Atlanta in which a passenger reportedly created a rogue Wi-Fi network named 'Delta WiFi Fast' to steal sensitive passenger data. The cabin crew deactivated the aircraft's Wi-Fi for roughly 30 minutes, and Delta says flight safety and aircraft operating systems were never affected. The FBI's Atlanta office and the FAA acknowledged awareness of the incident, which bears hallmarks of an evil twin attack involving spoofed login portals and credential harvesting. DEF CON organizers said this year's conference in Las Vegas also suffered multiple similar deauthentication Wi-Fi attacks.

CyberScoopAug 11, 21:35 UTC · Aug 11, 2026Phishing & fraud in the wild

CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

Researchers introduce CausalArena, a unified benchmark revealing that causal discovery rankings shift substantially across structural causal model families and protocols.

The paper presents CausalArena, a unified and evolvable benchmark for causal discovery combining synthetic structural causal models, semantically grounded operational SCMs, formula-grounded scientific SCMs, and public real-world datasets. Experiments across classical, neural, and pretrained causal discovery foundation models show large ranking shifts between benchmark regimes. The authors identify pretraining-evaluation overlap and benchmark diversity as central evaluation challenges.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:53 UTC · 5d agoAI research