Search: “remasc”

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Domain-Incremental Learning for Multi-Channel Replay Speech Detection

First continual learning benchmark for multi-channel replay speech detection shows task-specific beamforming cuts catastrophic forgetting across 24 acoustic environments.

Researchers frame replay-attack detection for voice-controlled systems as domain-incremental learning over acoustic environments, evaluating a beamformer-based detector across all 24 environment orderings of the ReMASC corpus with five seeds. Naive sequential fine-tuning raises error rates on previously learned environments by 18.8 points, while elastic weight consolidation halves forgetting but loses plasticity and gradient projection memory is statistically indistinguishable from naive fine-tuning. A task-specific beamformer keeping one spatial front-end per environment significantly improves final and incremental accuracy, and the last environment in a sequence dominates final performance.

arXiv cs.CR·Sep 10, 08:03 UTC · 6d agoResearch1

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Hackers Steal Active Directory Password Hashes Without Attacking Domain Controllers Directly

Attackers use the DCSync technique to impersonate domain controllers and harvest AD password hashes and Kerberos keys without directly compromising domain controllers, Trellix warns.

Per Trellix, threat actors increasingly abuse Active Directory replication via DCSync, using privileged credentials to invoke DRSGetNCChanges and retrieve NTLM password hashes and Kerberos key material without running code on domain controllers. Capturing the krbtgt account hash enables forging Golden Tickets for persistent, highly privileged domain access. Because malicious replication traffic mimics legitimate DRS/RPC activity, defenders should monitor Windows Security Event ID 4662, restrict replication permissions, and investigate replication requests from non-domain-controller systems.

GBHackers·Sep 10, 12:00 UTC · 6d agoResearch in the wild 2 sources2

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ReMoMask-2: Latent Retrieval-Augmented Masked Motion Generation

ReMoMask-2 rebuilds retrieval in the generator's latent space for text-to-motion generation, achieving lowest FID on KIT-ML and SnapMoGen.

ReMoMask-2 is a retrieval-augmented text-to-motion framework that constructs its retrieval database directly in the generator's pre-quantization latent space and aligns text queries through a distilled lightweight projector, eliminating the representation gap. The framework combines Hierarchical Bidirectional Momentum contrastive learning, Semantic Spatial-Temporal Attention, and Topology Structured Masking to handle hierarchical motion structure. The retriever achieves state-of-the-art accuracy, and ReMoMask-2 attains the lowest FID on KIT-ML and SnapMoGen, with a single mask-transformer stage outperforming the previous two-stage pipeline while delivering the fastest inference.

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

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RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting

RelightFormer is a feed-forward generative transformer for photorealistic single- and multi-view object relighting, trained on a 90K-object dataset.

Researchers introduce RelightFormer, a feed-forward generative transformer adapted from a video foundation model that performs direct image relighting without explicit intrinsic property estimation. The architecture injects target environment maps via a latent illumination module with cross-attention and uses permutation-invariant positional encodings for unordered multi-view inputs. Training relies on the newly constructed Laval Objaverse Dataset (LOD) with 90K objects and 39K unique illuminations, and the model shows state-of-the-art quality with strong zero-shot generalization across single-view, multi-view, and novel-view relighting.

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

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A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost·Sep 13, 17:02 UTC · 3d agoAI research1

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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 Research·updated Sep 11, 05:53 UTC · 5d ago·first Sep 10, 14:32 UTC · 6d agoAI safety & security 2 sources

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Rust Supply Chain Attack on arrayref: Significant Overlap with DPRK Campaigns

Malicious versions of the Rust crate arrayref executed a compile-time backdoor, with infrastructure overlapping recent DPRK supply chain attacks on Mastra and axios.

Wiz researchers report that malicious versions of the arrayref Rust crate ran a backdoor during compilation, compromising developer build pipelines. The campaign's command-and-control infrastructure significantly overlaps with infrastructure used in recent DPRK supply chain attacks, including campaigns against Mastra and axios. Developers using affected crate versions should audit their builds and review dependencies.

Wiz Blog·Aug 20, 15:56 UTC · 27d agoThreat actor in the wild1

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Domain-Specific Hallucination Detection in Large Language Models

A multi-signal pipeline detects LLM hallucinations, reaching F1 0.915 on HaluEval and cutting Qwen2.5-0.5B hallucination rates from 85.5% to 37.7% via DPO.

The paper presents a hallucination detection pipeline combining fine-tuned DeBERTa-v3 classification, Monte Carlo Dropout uncertainty, and temperature-scaled calibration. It achieves F1 0.915 and AUROC 0.977 on general-domain HaluEval tasks, with MC Dropout inference raising accuracy to 93.2%. Applying DPO to a Qwen2.5-0.5B generator reduces its hallucination rate from 85.5% to 37.7%, while cross-domain evaluation shows poor general-domain transfer to SciFact (F1 0.52) and PubMedBERT fine-tuning as the strongest adaptation (F1 0.63).

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:45 UTC · 6d agoAI research1

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xHunt Campaign: New PowerShell Backdoor Blocked Through DNS Tunnel Detection

xHunt's new CASHY200 PowerShell backdoor used DNS tunneling for C2; DNS security blocked beaconing at a Kuwait organization in September 2019.

Unit 42 describes CASHY200, a new PowerShell-based backdoor tied to the xHunt campaign that communicates with its C2 server windows64x[.]com via DNS tunneling, parsing commands from DNS answers. In September 2019, a Kuwait-based organization's DNS security service blocked the beaconing minutes after detection, cutting off adversary access. Samples dating to May and June 2018 and open source collection suggest the tool was used against Kuwait government organizations from spring 2018 through 2019, with malicious Word documents observed installing CASHY200 payloads configured with C2 domains such as firewallsupports[.]com and winx64-microsoft[.]com. The tool's name derives from identifiers stored under the registry key HKCU\Software\Microsoft\Cashe and the command value 200.

Palo Alto Unit 42·Aug 17, 13:19 UTC · Aug 17, 2026Threat actor

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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 News·Sep 11, 07:36 UTC · 5d agoAI safety & security1

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Feature Recovery for Object Understanding After Irreversible Fire Damage

TRACE benchmark with 21.4K scenes studies post-fire object understanding; a Feature Recovery Module improves degraded-image retrieval by 12.5% and material recovery by 20.1%.

The paper introduces TRACE, a transformation-aware benchmark with 21.4K real-image-grounded synthetic scenes, 499 object identities across 189 categories, and five tasks covering degraded-object detection, pristine-state recovery, material recovery, description generation, and functional reasoning. Existing models degrade sharply: RF-DETR mAP falls 71% relative from least to most severe level, and InternVL3.5 retrieval R@1 drops from 93.85 to 28.11. The proposed Feature Recovery Module maps degraded encoder features to pristine-aligned representations while keeping the host model frozen, averaging relative gains of 12.5% for retrieval and 20.1% for material recovery across VLM hosts and severity levels.

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

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BTR Reforged: Weaponizing Defender’s Remediation Driver as a Kernel Operation Primitive

Check Point shows attackers can abuse Microsoft Defender's signed remediation driver for arbitrary Ring 0 file and registry operations without exploiting any vulnerability.

Check Point Research presents BTR Reforged, a technique that repurposes Microsoft Defender's trusted remediation driver into an attacker-controlled kernel operation primitive. The signed driver can be instructed to execute arbitrary file and registry operations from Ring 0 without exploits, vulnerabilities, or memory corruption. The work demonstrates how trusted security components can be turned into attacker primitives, which is relevant for defenders assessing driver abuse risks.

Check Point Research·Aug 20, 13:07 UTC · 27d agoResearch

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Brinqa acquires PlexTrac to bring validated remediation to exposure management

Brinqa acquired PlexTrac to add pentest-driven validation of remediation, claiming the largest standalone unified exposure management vendor with 3,000+ customers.

Brinqa acquired PlexTrac to add offensive-security-driven validation that remediation actually worked, aiming to close the continuous threat exposure management loop from prioritization through verified fixes. Brinqa says the combination makes it the largest standalone vendor in unified exposure management, serving more than 3,000 customers across 57 countries, with PlexTrac continuing as a standalone product. Brinqa cited 164% year-over-year new-bookings growth in 2025 and inclusion in Gartner's inaugural Magic Quadrant for Exposure Assessment Platforms.

Help Net Security·Aug 19, 00:00 UTC · 28d agoIndustry

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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·Sep 15, 17:42 UTC · 1d agoAI research

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Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

Referee-Based Quality Estimation flags unreliable polyp segmentations at inference without ground truth, reaching ROC-AUC 0.960 with SegFormer-B0 referees.

RBQE measures agreement between a primary segmentation model and an independently trained referee on a 1,223-image external benchmark drawn from four public datasets. A cross-architecture SegFormer-B0 referee achieves the strongest signal (ROC-AUC 0.960), beating a Test-Time Augmentation baseline by 0.055 ROC-AUC under an identical protocol. Excluding trivially separable empty-mask cases, ROC-AUC falls to 0.876 (SegFormer-B0) and 0.783 (same-architecture control), but RBQE's margin over baselines widens. Progressive rejection of low-agreement predictions increases mean Dice of retained outputs, supporting selective prediction at the cost of one extra forward pass.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 17:32 UTC · 7d agoAI research

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HVNC Backdoor Targets LATAM Organizations with Fake Tax and DocuSign Lures

A custom HVNC backdoor is targeting Latin American financial organizations via fake DocuSign and NFe tax-document lures, giving attackers hidden persistent remote access.

ANY.RUN researchers analyzed a multi-stage phishing campaign delivering a custom HVNC backdoor to banking and financial organizations in Latin America. The chain starts with fake DocuSign and NFe tax-document pages that serve per-visitor ZIP archives, followed by an LNK dropper, an NSIS loader, and a 64-bit backdoor masquerading as Windows Update Assistant. The implant provides hidden remote desktop control, keystroke monitoring, Firefox data theft, Startup-folder persistence, and EDR-aware behavior, communicating over TCP/27015.

ANY.RUN·Sep 8, 10:24 UTC · 8d agoMalware in the wild

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Enoki: Efficient Multi-Level Hallucination Detection

Researchers introduce Enoki, an open information extraction framework unifying claim-level and span-level hallucination detection in LLMs at lower inference cost.

Enoki extracts text-anchored relational facts, verifies them against evidence, and projects unsupported facts back onto hallucinated spans, so claim-level verification and span-level localization share one representation without separate alignment. It supports LLM-based, encoder-based, and rule-based extraction regimes to balance accuracy against inference cost. Experiments show it stays competitive with strong claim-level systems while using fewer resources and outperforms them on fine-grained span- and entity-level localization. The authors also release EnokiQA, a dual-granularity dataset with aligned claim-level verification and span-level localization annotations.

Hugging Face daily papers·Aug 31, 22:21 UTC · 15d agoAI research

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Hackers Weaponize AI Safety Guardrails to Hide Malware From LLM-Powered Security Scanners

ESET says Russia-aligned actor UAC-0099 hid guardrail-triggering comments in VBScript to derail LLM-based malware scanners in Ukraine.

ESET researchers linked a technique named GuardBreaker to Russia-aligned threat actor UAC-0099 during an attack against an organization in Ukraine. The group embedded a safety-sensitive, weapon-related request in a VBScript comment so an LLM-powered analysis tool might interpret it as an instruction and refuse or truncate analysis before reaching the malicious code. The VBScript downloaded MATCHBOIL, a C#-based loader used by the group alongside MATCHWOK and DRAGSTARE. OWASP guidance recommends treating code comments and metadata as untrusted input, sanitizing it, and never treating an LLM refusal as a clean verdict.

GBHackers·updated Sep 11, 14:32 UTC · 5d ago·first Sep 11, 10:51 UTC · 5d agoThreat actor in the wild 3 sources1

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AD Rights Management Service (Part 1): Architecture, Deprecation, and Reconnaissance

Huntress maps AD RMS architecture and recon paths, setting up an offline key-extraction attack against its unrotatable 255-year root key.

Huntress's multi-part research examines Active Directory Rights Management Services, Microsoft's enterprise DRM role that still ships in Windows Server 2025 despite migration guidance favoring Azure Information Protection. Part 1 covers the trust model and how an ordinary domain account can locate RMS clusters and read rights-policy templates. Part 2 will detail four independent paths for extracting the Server Licensor Certificate (SLC) private key via service-group membership and the configuration database, enabling fully offline decryption of protected documents. The SLC certificate is valid from 2002 to 2258 and has no key-rotation mechanism, so a stolen key decrypts protected content indefinitely.

Huntress·Sep 8, 04:00 UTC · 8d agoResearch1

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Recursive Code World Models: Building Complex Worlds through Recursive Scene Programs

RCWM reconstructs complex 3D worlds as executable code from a single image using recursive scene programs with global-local-global solver recursion.

The paper introduces Recursive Code World Models, coupling a Recursive Scene Program representation with a recursive construction solver for image-to-3D-world reconstruction. Each solver call establishes the whole scene, recursively reconstructs unresolved parts, and revisits the whole to refine composition, while a vision-language coding agent compares reference images with scene renders to guide refinement. RCWM outperforms prior code-based image-to-scene reconstruction methods, and ablations show deeper recursive calls improve fine-scale reconstruction.

Hugging Face daily papers·Sep 9, 20:00 UTC · 6d agoAI research1

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AsyncRAT Malware Abuses AutoIt and PowerShell to Hide Inside Legitimate Windows Process

Point Wild details a five-stage AsyncRAT campaign using AutoIt abuse and process injection to hide a .NET RAT inside Microsoft's signed charmap.exe.

Researchers at Point Wild Threat Intelligence analyzed a campaign starting from a lure batch file ('Right-click to open Invoice Details.bat') that launches hidden PowerShell to reconstruct a Base64/XOR-obfuscated payload. The stage drops a renamed signed AutoIt interpreter and loader script into %LOCALAPPDATA%\Temp and achieves persistence via a batch file in the user's Startup folder (T1547.001). The loader decrypts the payload in memory with single-byte XOR key 0x36 and injects it into SysWOW64\charmap.exe using OpenProcess/VirtualAllocEx/WriteProcessMemory/CreateRemoteThread, with PE-sieve confirming an in-memory implanted PE and patched AMSI modules. The final AsyncRAT payload performs screen capture and data theft, with observed C2 at 158[.]51[.]122[.]136:4944 over raw TCP.

GBHackers·Sep 14, 05:24 UTC · 2d agoMalware3· 1 read

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Ncsc Raises Alarms Prompt

The UK NCSC raised alarms about prompt injection risks in LLM-integrated systems, urging organizations deploying AI to review exposure.

The UK National Cyber Security Centre (NCSC) has raised alarms about prompt injection attacks against systems using large language models. The warning highlights how attackers can manipulate model instructions to bypass safeguards, exfiltrate data, or trigger unintended agent actions. Organizations deploying LLM-based features are advised to assess and mitigate their exposure to this technique.

Infosecurity Magazine·Aug 19, 00:00 UTC · 28d agoAI safety & security

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Foundation Models for Generalizable Semantic and Goal-Oriented Communication

FMSGOC uses vision-language foundation model priors plus diffusion reconstruction to enable generalizable semantic communication at 0.039 bits per pixel for 6G.

FMSGOC targets generalization failures in semantic and goal-oriented communication for 6G by leveraging broad visual-linguistic foundation model priors. A vision-language model selects sparse, goal-aligned semantic anchors while a fine-tuned diffusion model performs masked completion to reconstruct images at the receiver, decoupling what to send from how to reconstruct. On CIFAR-10 it reaches 0.039 bits per pixel with cosine similarity 0.87-0.90 and 0.83-0.86 on unseen ImageNet inputs, outperforming end-to-end baselines at lower bit rates.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 18:12 UTC · 9d agoAI research

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How to secure hybrid meeting rooms without sacrificing user experience

Sponsored Barco piece, citing IDC data, says security is now the top videoconferencing purchase criterion as NIS2 and Cyber Resilience Act compliance pressures mount.

The sponsored article cites IDC research showing security (31%) now outranks price (26%) and quality (25%) as the top videoconferencing purchase criterion. It highlights concerns like malware propagation (47%), missed patches (39%), and risky user behavior (37%), and references NIS2, the Cyber Resilience Act, the Radio Equipment Delegated Act, and ISO/IEC 27001. Barco ClickShare marketing director Yannic Laleeuwe argues security is now a prerequisite for market access and resilience, but warns that usability tradeoffs drive risky workarounds.

The Register · Security·Sep 8, 15:00 UTC · 8d agoIndustry

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The Model Proposes, the Code Disposes: A Pre-Registered Ablation of a Verifier-and-Acceptance Stage in an LLM-Orchestrated Offensive-Security Agent

Pre-registered ablation finds a model verifier stage in an LLM offensive-security agent suppresses findings; removing it eliminated suppression with precision tradeoff.

The paper evaluates a verifier-and-acceptance stage in an LLM-orchestrated offensive-security agent via a pre-registered 20-run confirmatory ablation and a 2x2 factorial study with 40 runs on vulnerable lab targets. Removing the stage eliminated pre-report suppression (median 2 vs 0 findings, p = 0.00003) but reduced model-blinded shipped precision (0.471 vs 0.353, p = 0.0087). Suppression was attributed to the model verifier rather than deterministic acceptance rules, and an instrumented canary recorded zero external contacts in all 60 runs. The full design retained 93.8% of model-adjudicated true candidates but failed its pre-registered non-inferiority floor of 0.90.

arXiv cs.CR·Sep 14, 17:13 UTC · 2d agoResearch

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Not All Relations Are Equal: Relation-Balanced and Calibrated Graph Learning for Provenance-Based Intrusion Detection

RECAL improves provenance-based APT detection with relation-balanced masked graph learning and calibrated errors, reaching 99.99% F1 on DARPA E3 datasets.

RECAL is an unsupervised framework for provenance-based intrusion detection that uses relation-balanced masked graph learning to capture rare interaction patterns, addressing statistical heterogeneity where relation frequencies differ by roughly 140,000X in CADETS. It calibrates reconstruction errors against each relation's benign error distribution to produce comparable anomaly evidence and reduce false alarms. On three DARPA E3 datasets, RECAL achieves F1 scores of 99.99%, 99.93%, and 99.99%, outperforming the best baseline on each dataset, and reduces mean false positive rate by approximately 105X, 4X, and 41X versus the lowest-FPR baseline.

arXiv cs.CR·Sep 15, 00:31 UTC · 1d agoResearch

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The Router Within: Eliciting Native Skill Routing from a Frozen LLM

Gavel reads native skill-routing signals from a frozen LLM's forward passes with two linear maps, beating retrieve-and-rerank pipelines by up to 21.9 points on Qwen3-32B.

Gavel (Glance And Verdict from a frozen LLM) elicits skill routing from a frozen agent LLM using two trained linear maps that read mid-layer states, keeping all skill text out of context. A glance step scores the full library against compact per-skill banks built in one forward pass at installation; a verdict step resumes shortlisted skills' forward passes and fuses likelihood and yes/no judgments as a product of experts. It transfers zero-shot to three public benchmarks plus SkillTraj, a new benchmark of 372 simulated agent trajectories. On Qwen3-32B it beats progressive disclosure and retrieve-and-rerank pipelines adding 1.2B–16B external parameters by up to 13.4 points on written tasks and 21.9 when skills are needed mid-rollout.

Hugging Face daily papers·updated Sep 14, 17:58 UTC · 2d ago·first Sep 13, 20:00 UTC · 2d agoAI research 2 sources

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CISA Warns Hackers Exploit 17 Active Directory Techniques to Gain Control of Enterprise Networks

CISA and Five Eyes agencies issued joint guidance detailing 17 Active Directory attack techniques like Kerberoasting and DCSync, with hardening and detection advice.

CISA, the NSA, and cyber agencies from Australia, Canada, the UK, and New Zealand released joint guidance on September 15 covering 17 techniques attackers use to compromise Active Directory, including AD CS, Certificate Services, and Federation Services attacks. Named techniques include Kerberoasting, AS-REP roasting, password spraying, DCSync, NTDS.dit dumping, Golden and Silver Tickets, Golden SAML, and Skeleton Key. Recommendations include minimizing SPN accounts, enforcing AES encryption, disabling NTLM, account lockout thresholds of five attempts, phishing-resistant MFA, and Tier 0 prioritization. The guide also lists Windows event IDs 4769, 4768, 4625, 4771, and 2889 for detecting Kerberoasting and password spraying on domain controllers.

GBHackers·06:04 UTC · 13h agoAdvisory

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AD Rights Management Service (Part 2): Extraction, Offline Decryption, and the Unrotatable Key

Huntress research shows AD RMS SLC root key is unrotatable and never expires, so its compromise permanently exposes all RMS-protected documents.

Part 2 of Huntress's AD RMS series details server-side attacks: extracting the Server Licensor Certificate (SLC) private key and performing offline decryption of protected documents. The SLC key has no expiry or rotation mechanism, with a 255-year certificate validity (2002–2258), so whoever recovers it can decrypt every document the deployment ever protected, indefinitely. The author released SharpRMS, a unified tool combining the 2016 DisARMS client-side attacks with new server-side key extraction and decryption capabilities. The research frames the SLC as comparable to KRBTGT and the DPAPI domain backup key, though not equivalent to domain compromise.

Huntress·Sep 10, 04:00 UTC · 6d agoResearch

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