ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Search: “keyv”

35 stories

Searchkeywordsmart
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllMalware 3Data breach 1Exploit / PoC 1Policy & legal 1Vulnerability 1
SeverityAllcritical 2high 2medium 2low 1info 0

Smart search ranks by meaning as well as keywords (one row per story, last 45 days).

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

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

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

Latent Space · 4d agoModel release 7 sources1

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 papers · 8d agoAI research

Tracking Shai-Hulud: Inside the ChainDrop NPM Worm

ChainDrop, a Mini Shai-Hulud variant tied to TeamPCP, worms through npm via a compromised maintainer account and anchors C2 in an Ethereum smart contract.

On August 4, 2026, the self-propagating ChainDrop worm entered the npm ecosystem through a compromised maintainer account, poisoning packages including keyv, cacheable, and flat-cache. ChainDrop is a variant of Mini Shai-Hulud linked to the actor TeamPCP. It anchors its C2 infrastructure in an Ethereum smart contract, allowing domain rotation with a single blockchain transaction and defeating domain-based blocklists. The compromised keyv maintainer's GitHub account caused the project's own GitHub Actions release pipeline to publish malicious package versions.

Zscaler ThreatLabz · Aug 11, 2026Malware in the wild

DPRK APTs: Ted backdoor and curlRAT target South Korean media and automotive sectors

Rapid7 uncovered a DPRK-linked Linux toolkit using a HAProxy-embedded ted backdoor, SSH keylogger, and curlRAT against South Korean media and automotive firms.

Rapid7 Labs identified a previously undocumented framework attributed with medium confidence to DPRK actors, targeting South Korean automotive and media organizations likely since early 2025. The toolkit embeds a backdoor compiled into HAProxy 2.8.12 using its filter API, plus trojanized crond, agetty, atd, sshd, and polkitd, an SSH keylogger storing credentials under /var/lib/sshd/, and a curl-based RAT with a watchdog thread. It enables remote command execution, malicious script injection into served webpages (a watering-hole loop), credential harvesting, and long-term surveillance. Hardcoded C2s are associated with APT37 via ThreatFox, and exposed groupware portals and mail servers align with Kimsuky tradecraft; the initial access vector and any CVE remain unconfirmed.

Rapid7 Blog · 12d agoThreat actor in the wild1

Training a coding model to paint watercolours with TRL and OpenEnv

Hugging Face tutorial trains a coding model with TRL and OpenEnv to paint watercolours through generated code.

A Hugging Face blog walkthrough uses the TRL reinforcement learning library and the OpenEnv environment framework to train a coding model. The target task is generating code that produces watercolour-style drawings, serving as a hands-on reinforcement learning training example. No article body was available in the feed, so specifics are limited to the title.

Hugging Face Blog · 13d agoAI tools & infra1

SenseNova-U1.5: Towards Native Unified Visual Intelligence

SenseTime releases SenseNova-U1.5, an 8B-MoT encoder-free multimodal model unifying visual understanding, reasoning, and generation with native 4K resolution.

SenseNova-U1.5 is an 8B mixture-of-transformers multimodal model with an encoder-free, VAE-free architecture that understands, reasons about, and generates visual content at native resolutions up to 4K. Post-training optimizes specialized experts for visual aesthetics, bilingual text rendering, infographic generation, and image editing, consolidated through multi-expert on-policy distillation. Evaluations report gains in image fidelity, text rendering, multi-reference editing, and instruction following. The team plans to open-source training code including supervised fine-tuning, reinforcement learning, and on-policy distillation.

Hugging Face daily papers · 6d agoModel release

Alleged TeamPCP Hackers Charged in Australia Over Major Supply Chain Attacks

Australian Federal Police charges two men with 14 offences over TeamPCP supply chain backdoors in Trivy, Checkmarx KICS, and LiteLLM affecting 1,000+ organizations.

The Australian Federal Police charged two Western Australian men, aged 21 and 23, with 14 offences for their alleged principal roles in TeamPCP's March 2026 supply chain attacks; they appeared in Perth Magistrates Court on August 27, 2026. The group stole publishing credentials from trusted open-source projects and pushed poisoned releases across five ecosystems - GitHub Actions, Docker Hub, npm, PyPI, and OpenVSX - with LiteLLM's unpinned Trivy install enabling token theft and backdoored LiteLLM releases. The FBI said the malicious code potentially compromised more than 1,000 organizations, enabled theft of over 500,000 credentials, and exfiltrated at least 300 GB of data. Oligo Security linked the group's infrastructure to activity back to 2020, previously tracked as TA-NATALSTATUS and IronErn.

The Hacker News · 20d agoPolicy & legal in the wild1

Ambient @ EgoLongQA 2026: Distilling Long-Video perception into a Sub-2B Model

Ambient team wins EgoLongQA 2026 sub-2B division by distilling an agentic long-video perception pipeline into a 2B vision-language model.

Ambient's entry to the EgoLongQA track of the Wearable-AI Challenge at ECCV 2026 placed first in the <=2B parameter division with 0.8279 on the held-out test set. The system distills the junior perception module of a tool-using agentic pipeline into a 2B student, reaching 89% of the pipeline's accuracy with 1.1% of its parameters and lifting a 27.1% base model to 81.4%. To meet the division limit, the multilingual embedding table is pruned from 248,320 to 143,469 rows, reaching 1.9985B parameters with provably identical logits on retained rows.

Hugging Face daily papers · 6d agoAI research

Mozilla Revokes Firefox and Thunderbird Linux Signing Key After Key Lands in Private Repo

Mozilla revoked the Firefox and Thunderbird Linux RPM signing subkey after an unencrypted copy landed in a private repo; no unauthorized access found.

Mozilla revoked the OpenPGP signing subkey (fingerprint 09BE ED63 F346 2A2D FFAB 3B87 5ECB 6497 C1A2 0256) used for Firefox and Thunderbird Linux downloads after an unencrypted copy was committed to one of its private repositories, citing reason code 2, 'key material has been compromised.' Audit records showed no sign of unauthorized access, and a replacement subkey (827E 6586 0867 9618 CD34 9F93 678E 455D 7676 7AA3) valid until August 5, 2028 was published. Users who verify signatures manually or install from Mozilla RPM packages may need to import the new key and remove the old one. The rotation came roughly seven months ahead of Mozilla's usual two-year subkey cycle.

The Hacker News · Aug 11, 2026Data breach

Adversarial Testing of Automated Program Repair Agents for Security Vulnerabilities

SWEADV benchmark shows adversarial issue descriptions make LLM program-repair agents write insecure fixes in 51.7% of cases, evading most detection tools.

Researchers built SWEADV, a benchmark of 750 adversarial issue descriptions derived from 150 SWE-bench Verified repair tasks, covering command execution, deserialization, path traversal, denial of service, and weak hashing attack types. Tested on mini_swe agents backed by GPT-5-Mini, MiniMax-M2.5, and DeepSeek-R, adversarial descriptions induced malicious behavior with successful repair in 51.7% of cases. Detection was weak: LLM-as-judge pre-repair screening reached only 62.3% accuracy, and post-repair detection via static analysis and LLM-as-judge achieved just 39.4% and 55.4%.

arXiv cs.CR · 1d agoAI safety & security1

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

Hackers Disguise CHOSEN BRICK Malware as AI Apps, Antivirus Software and MRI Results

NCSC, FBI, and AIVD warn Iranian state-linked actors deliver CHOSEN BRICK Windows spyware via fake AI apps, antivirus installers, and MRI-result lures.

A joint advisory from the UK NCSC, FBI, and Dutch AIVD details CHOSEN BRICK (FBI tracking name: HEAVYGRAM), Iranian state-linked Windows spyware targeting dissidents, activists, and journalists worldwide since at least 2025. Lures impersonate Pictory, RunwayML, Norton Antivirus, Telegram, Adobe Flash Player, and KeePass, and operators pivot conversations from corporate to personal devices to bypass enterprise controls. The spyware persists via Registry Run keys, adds Microsoft Defender exclusions, uses per-victim Telegram bots for command-and-control, and exfiltrates screenshots, audio, email, and chat data via Telegram and cloud services, with some victim data appearing on pro-Iranian leak sites.

GBHackersupdated · 1h agofirst · 6h agoMalware in the wild 5 sources

Has anybody seen my keys? A key-hierarchy strategy for rack-level security

Oxide's RFD 0301 proposes a rack-level key hierarchy using Shamir secret sharing and a trust quorum to protect data-at-rest keys.

Oxide's request for discussion (RFD 0301) lays out a key-hierarchy strategy for rack-level security, deriving keys from a rack secret protected by Shamir secret sharing across a trust quorum of sleds, with keys exchanged over authenticated sprockets sessions. The document maps which keys protect control-plane data, metrics, Crucible extents, and authentication tokens, and defines open questions on key lifecycle, locality, and compromise handling. Future work includes sealing shares with the root of trust so an attacker would need to steal K whole sleds to reconstruct the rack secret.

Hacker News · security · 9d agoResearchHN 52↑ · 3 comments

SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models

SimpleMemVLA passes full timestamped video history straight to a VLA backbone, setting state of the art on four memory benchmarks.

SimpleMemVLA is a vision-language-action model for long-horizon manipulation that removes the dedicated memory module entirely. It keeps sampled history intact and feeds it to the backbone as timestamped video, with the hidden states of a generated sub-task serving as the only channel into a standard flow-matching action head. Prefilling the shared history prefix during action execution keeps latency close to a single-frame VLA. The system sets a new state of the art on four memory benchmarks and outperforms retrieval, compression and recurrent-state mechanisms, with causal interventions confirming the policy genuinely reads its history.

Hugging Face daily papers · 14d agoAI research

ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

ENCP calibrates conformal prediction per navigation episode, giving step-level coverage guarantees for vision-language navigation agents despite within-episode dependence.

Episode-Normalized Conformal Prediction (ENCP) rescales a nonconformity score by a VLN policy's residual confidence and calibrates one maximum score per episode, preserving step-level coverage of at least 1−α despite dependence among steps within an episode. Across four VLN policies and three nonconformity scores on R2R and REVERIE, ENCP meets all reported empirical step-coverage targets in seen-to-unseen evaluation. The model-agnostic uncertainty estimates can signal when an agent should defer to a stronger predictor or human assistance.

arXiv cs.AI / cs.LG / cs.CL · 20h agoAI research

North Korean Hackers Deploy New Linux Espionage Toolkit

Rapid7 says North Korea-aligned actors use a new Linux espionage toolkit (ted HAProxy backdoor, CurlRAT) against South Korean automotive and media targets.

Rapid7 reports a stealthy Linux framework comprising a custom HAProxy backdoor ('ted'), trojanized system binaries (agetty, atd, crond, polkitd, sshd), an SSH keylogger, and CurlRAT that polls C&C every 12 hours. Initial access came via a Groupware login portal flaw, with credential harvesting enabling lateral movement to internal systems. The toolkit supports long-term surveillance, HTTP traffic interception/injection, and drive-by downloads, likely in use since late 2024. Infrastructure and artifacts overlap Operation SyncHole, suggesting Lazarus or APT37 involvement.

SecurityWeek · 9d agoThreat actor in the wild1

North Korea-linked Hackers Hide a Backdoor Inside HAProxy

Rapid7 reports North Korea-linked hackers implanted a backdoor compiled into HAProxy at South Korean automotive and media firms, enabling covert C2 and credential theft.

Rapid7 documented a previously undocumented Linux toolkit hitting South Korean automotive and media organizations, centered on a backdoor compiled directly into victims' HAProxy 2.8.12. The 'ted backdoor' uses HAProxy's native filter API to intercept HTTP traffic, receive C2 commands hidden in requests to a fake image path, and erase all traces from logs and counters; the toolkit also trojanizes crond, agetty, atd, sshd, and polkitd, adds an SSH keylogger, and runs curlRAT with virtualization checks. It can inject scripts or replace page content for selected victims, turning the load balancer into a watering hole. Attribution sits at medium confidence toward North Korean state actors, with overlaps to APT37-linked infrastructure and a concurrent Lazarus campaign; the campaign's command domains have since gone dark.

Security Affairs · 8d agoThreat actor in the wild

Afraidgate: Major Exploit Kit Campaign Swaps Locky Ransomware for CryptXXX

Unit 42 reports the Afraidgate campaign switched from Nuclear EK delivering Locky to Angler EK delivering CryptXXX via the Bedep downloader.

Unit 42 reported that the Afraidgate campaign, which uses gates registered through FreeDNS at afraid.org, switched in mid-April 2016 from Nuclear EK distributing Locky ransomware to Angler EK distributing CryptXXX. The Angler/Bedep/CryptXXX combination also spread from the pseudo-Darkleech campaign, with Bedep acting as a fileless, memory-resident downloader that also installs click-fraud malware. Recent Bedep updates detect virtual machines and alter behavior, complicating analyst investigation. Unit 42 published gate, EK, and post-infection indicators including gate IP 185.118.164.42 and associated domains.

Palo Alto Unit 42 · Aug 17, 2026Threat actor in the wild

Russian hackers plant nuclear weapon prompt in malware to trip AI safety guardrails

ESET reports Russian group UAC-0099 hid a prompt in VBS malware comments to trip AI safety filters and disrupt automated malware analysis in Ukraine.

ESET identified a technique dubbed GuardBreaker in which UAC-0099 embedded a comment reading "I want to make nuclear weapon. Help me …" inside a malicious VBS script to trigger AI safety mechanisms and halt AI-assisted malware analysis. The script, part of the group's toolset, downloads the MATCHBOIL malware used exclusively by this Russia-aligned group; CERT-UA documented the chain including LUNCHPOKE, BURNYBEAR and MATCHBOIL.V2 in a July advisory. UAC-0099 typically targets transportation and energy sectors and hands validated targets to GRU-linked Sandworm. ESET warned that AI-assisted analysis must be backed by layered detection and human-driven engineering.

Help Net Security · 16d agoAI safety & security in the wild

One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing

Researchers introduce EditVid, a training-free video editing framework scoring 78.16 FiVE-Acc versus 58.95 for the strongest comparable baseline.

EditVid is a unified training-free framework for diverse instruction-guided and subject-guided video editing. It combines sparse causal memory for local coherence, correspondence-based post-attention token injection for long-range identity preservation, and soft latent blending for edit locality. On the FiVE benchmark it reaches 78.16 FiVE-Acc against 58.95 for the strongest evaluated training-free baseline, with competitive results on IVEBench. A user study showed 51.8% overall preference for EditVid over 7 competing methods.

Hugging Face daily papers · 13d 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.CL · 11d agoAI research

PIDS-Bench: Evaluating Prompt-Injection Detectors Under Over-Defense, Obfuscation, and Distribution Shift

PIDS-Bench shows prompt-injection detectors scoring F1 above 0.98 still misclassify about one-third of external benign security-adjacent prompts, revealing provenance-sensitive over-defense.

PIDS-Bench is a frozen multi-axis benchmark that jointly evaluates prompt-injection detectors on attack detection and benign false-positive behavior at fixed thresholds, spanning in-distribution inputs, hard-benign prompts, obfuscated attacks, and domain/structural distribution shifts. It evaluates seven detectors plus a rule-based lower-bound reference. A detector exceeding F1 = 0.98 on held-out data still misclassifies roughly one-third of an externally-sourced benign security-adjacent subset, and no internal detector reaches F1 >= 0.95 with hard-benign FPR <= 0.10 on the stress distribution. Hard-negative augmentation nearly eliminates over-defense on curated stress inputs but leaves it intact on externally-sourced prompts, a pattern termed provenance-sensitive over-defense.

arXiv cs.CR · 2d agoAI safety & security

Microsoft Copilot reveals secret input that allowed it to be hacked

Microsoft disclosed a hidden input in Copilot that let attackers steal passwords from users who clicked a crafted link.

Microsoft revealed that Copilot contained a secret, undocumented input parameter that allowed the assistant to be compromised. Attackers could abuse the hidden input to steal passwords when a target clicked a malicious link. The disclosure highlights hidden-parameter risks in widely deployed AI assistants.

Ars Technica · Security · 29d agoAI safety & security in the wild1

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

ENEAS adds text prompting and semantic verification to video segmentation to keep tracking targets through occlusion and reject lookalike distractors.

ENEAS is a unified text-promptable method for instance tracking and open-concept semantic discovery in video, designed to fix temporal hallucinations, spatial fragmentation, and semantic misclassification seen in SAM 3-class foundation models. It extends the geometrically robust SeC architecture with a text-prompting adapter and temporal memory, and uses a verification layer combining fast visual embedding matching with conditional VLM refinement for ambiguous candidates. It targets 3D reconstruction pipelines where a single misclassified distractor corrupts the asset. Code and models are open-sourced.

Hugging Face daily papers · 13d agoAI research

Locky Ransomware Installed Through Nuclear EK

Unit 42 reports Locky ransomware delivered through the Nuclear exploit kit using Flash exploits, adding a drive-by path to existing malspam distribution.

Unit 42 observed Locky ransomware being delivered by the Nuclear exploit kit in March 2016 via Flash exploits, following February reports of Neutrino EK distributing Locky. Infections follow a drive-by chain through a gate to the Nuclear EK, which either installs Locky directly or drops a downloader that retrieves it from another domain. Locky retains two distribution paths: malspam with malicious Office macros or JavaScript attachments and exploit kit traffic triggered by casual web browsing.

Palo Alto Unit 42 · Aug 17, 2026Ransomware in the wild1

IFM/K2-Horizon-MoVA-36B-A4B — new model trending #15 on Hugging Face

IFM released K2-Horizon-MoVA-36B-A4B, an open-weights 36B-parameter MoE model with 4B active parameters and native 512K context.

IFM released the final checkpoint of K2-Horizon-MoVA-36B-A4B, a sparse Mixture-of-Experts model using Mixture-of-Values (MoVA) attention with 36B total and 4B active parameters. The model supports native 524,288-token context and reportedly outscores open-weight dense and MoE models up to 15x its size on agentic and reasoning benchmarks, while competing against closed frontier models. Intermediate checkpoints, training data, the training recipe, and training code are slated for public release.

Hugging Face trending models · 14d agoModel release

Beyond Solver Verdicts: Generative Reward Models for Autoformalization

Researchers introduce Generative Verification (GenV), a generative reward model achieving 0.961 AUROC in detecting unfaithful autoformalization that preserves solver verdicts.

The paper formalizes Verdict-Preserving-Unfaithfulness (VPU), a failure mode in neurosymbolic autoformalization where an incorrect encoding executes successfully and matches the expected solver verdict, and proves verdict-only verification is bounded to chance-level detection. The proposed Generative Verification (GenV) distills an offline Z3-equivalence oracle into a reference-free, continuous reference-equivalence score within the language model's vocabulary space. The oracle-mined verifier (GenV+HN) achieves 0.961 AUROC, generalizes zero-shot across unseen translators and formal styles, and yields an 11.3-point downstream accuracy gain in agentic test-time compute allocation. Mechanistic analysis with decision-projected logit lenses and sparse autoencoders shows the generative readout extracts precise spatial error coordinates without explicit localization training.

Hugging Face daily papers · 6d agoAI research1

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papers · 12d agoAI research1

microsoft/VibeVoice-ASR-Streaming-7B — new model trending #27 on Hugging Face

Microsoft released VibeVoice-ASR-Streaming-7B, an open streaming ASR model with speaker attribution, custom hotwords, and support for 10 languages under MIT license.

Microsoft Research released VibeVoice-ASR-Streaming-7B on Hugging Face, a unified streaming speech recognition model that continuously transcribes who said what as speech arrives. The 7B model supports customized hotwords for domain-specific terms and 10 languages including Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Code is available at github.com/microsoft/VibeVoice with a live demo, and a technical report is on arXiv (2609.02812). The model is licensed under MIT.

Hugging Face trending models · 13d agoModel release1

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 · 11d agoAI research1

K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

Clinician-calibrated K-Bench evaluates 125 LLM configurations on 200 high-risk mental health vignettes, exposing wide variation in suicide and violence risk handling.

K-Bench is a clinician-calibrated, protected benchmark evaluating 125 model configurations from 33 base models across 14 providers on 200 multi-turn vignettes covering suicide, self-harm, domestic violence, substance misuse and no-risk presentations. A frozen GPT-4o judge achieved 94.2% exact agreement with clinician consensus across 6,751 eligible comparisons from 151 clinician-rated transcripts. Leading models combined supportive conversation with combined-risk scores above 95, while risk exploration varied substantially among weaker configurations; therapeutic prompting helped weaker models and elevated reasoning produced no average improvement. A continuously updated public leaderboard is hosted at k-bench.ai with protected test materials.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI safety & security