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Smart search ranks by meaning as well as keywords (one row per story, last 45 days).
Attackers impersonate popular AI brands to spread malware
Sophos documented 38 MDR cases where attackers impersonated AI brands like Claude and Perplexity to deliver infostealers and backdoors.
Sophos X-Ops analyzed 12 months of MDR cases and confirmed 38 incidents involving AI. Software impersonation accounted for 30 cases, with Claude impersonated in 26; fake installers used an 'InstallFix' technique delivering mshta commands, in-memory payloads, and process hollowing. Malicious browser extensions posing as AI assistants, including a fake Perplexity extension with 10,000 installs, acted as infostealers. In one case, attackers used a Claude coding agent to develop a Rust remote access trojan communicating over Slack after an SQL injection compromise.
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Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.
The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.
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ASCII smuggling crosses over from AI prompt injection to phishing evasion
Microsoft details high-volume phishing campaign using ASCII smuggling (Unicode tag chars) for filter evasion, peaking at 2.3M messages.
Microsoft researchers observed a high-volume finance-themed phishing campaign using invisible Unicode tag characters (U+E0000–U+E007F), a technique known from AI prompt injection research as ASCII smuggling, to split lure words like 'funding' and evade email filters. Telemetry from Microsoft Defender for Office 365 showed signature hits jump from roughly 21,000 messages on February 8, 2026 to more than 1.3 million on February 9, peaking above 2.3 million on February 11, with elevated weekday activity lasting approximately three months. The discovery emerged from prompt injection protection research, showing AI-era evasion techniques crossing into traditional phishing. Most messages were flagged by layered Defender protections rather than a single Unicode-specific signal.
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Recorded Future Launches Digital Risk Protection, Unifying Brand and Identity Monitoring
Recorded Future launched Digital Risk Protection, unifying brand and identity monitoring across five external threat surfaces in one workflow.
Recorded Future announced Digital Risk Protection, combining brand threat monitoring and identity exposure monitoring across five use cases: malicious site, impersonation, code repository, dark web brand, and identity exposure monitoring. The platform includes an AI Triage Agent that automates alert evaluation with explicit verdicts and context, expanding social media analysis, OCR, full Telegram coverage, and infostealer log ingestion. Gartner's 2026 Magic Quadrant folded digital risk protection into cyber threat intelligence technologies, and the launch cites $15.9 billion in 2025 US fraud/scam losses, up 28% year over year.
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DoppelCart fraud network uses 119,000 fake shops to steal credit cards
DoppelCart, the largest documented fake-shop network, runs 119,000 domains impersonating 44,182 brands to steal payment card details via WebSocket-connected checkout pages.
German cybersecurity startup Nebty discovered DoppelCart, a network of more than 119,000 fake e-commerce domains, mostly in the .SHOP TLD, that harvest payment card details through fraudulent checkout pages. Over 105,000 shops remain active, impersonating 44,182 brands with discounts of up to 65%, and 96% of confirmed shops share identical build files resolving to 27 commerce backends. Checkout code exfiltrates card numbers, expiration dates, CVVs, cardholder names, contact details, and even bank one-time codes to attacker C2 over WebSockets in real time, potentially bypassing bank security controls. The network surpasses BogusBazaar, the previously largest documented fake-shop cluster with 75,000 sites and an estimated 850,000 fraudulent transactions.
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Brand Impersonation Takedown: From Whack-a-Mole to Managed Response
Mandiant-tracked group UNC3753 impersonated US professional services firms' brands in 2026; Cyble urges managed takedowns over manual abuse reports.
Cyble describes how Google Mandiant-tracked group UNC3753 targeted US professional services firms between January and May 2026 using brand impersonation, spoofed domains, and fake executive profiles. Manual takedowns fail because phishing pages damage brands within hours while removal takes days. A managed takedown program with continuous monitoring and pre-authorized removal cuts the exposure window from days to hours.
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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.
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Teams calls are about to get a lot harder to fake
Microsoft will roll out Brand Impersonation Protection in Teams Calling from mid-May 2026, warning users about suspicious inbound VoIP calls impersonating trusted brands.
Microsoft Teams Calling is gaining Brand Impersonation Protection, which evaluates inbound VoIP calls from first-time external callers for signs of brand impersonation and displays warnings before users answer high-risk calls. The feature rolls out from mid-May 2026 with completion expected by late May 2026, is enabled by default, and requires no administrative action. Users can accept, block, or end flagged calls, and alerts may continue throughout a call if suspicious activity persists. Microsoft recommends preparing helpdesk teams and updating security awareness materials ahead of deployment.
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The New Face of Financial Fraud: AI-Powered Brand Abuse
Akamai reports AI-powered brand abuse is driving financial fraud against banks and promotes its Brand Guardian defense.
Akamai describes AI-powered brand abuse as a growing driver of financial fraud against banks. The post outlines the threats and the business impact for financial institutions. It also promotes Akamai Brand Guardian as a mitigation for financial institutions.
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When the Whole Company Adopts AI: What It Does to Your SOC
Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.
A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.
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Enabling Creative Exploration for Vibe Design Agents
Separating design-direction exploration from code generation via structured specifications broadens UI alternatives without destabilizing output.
The paper proposes an inference architecture for vibe design agents that makes design direction an explicit intermediate decision: a Verbalized Sampling-inspired pre-pass proposes structured design specifications with typicality scores, an external selector samples one, and a downstream generator realizes it under fixed settings. Across 168 prompts with 1,255 paired comparisons per temperature, theme sampling broadens selection coverage and screenshot variation, with LLM-judge preferences varying across interventions and prompt complexity. An online experiment with over 300,000 tasks found the code-export increase statistically uncertain, though negative feedback events decreased alongside modest operational costs.
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Details emerge on BlackFile's recent attacks on financial companies
BlackFile (UNC6671), a The Com-linked extortion crew, keeps hitting financial and med tech firms with voice-phishing IT-support scams and ~$3 million demands.
Google Threat Intelligence Group (tracking BlackFile as UNC6671, linked to The Com) reports the extortion group remains active, shifting focus to the financial sector and med tech organizations, with new Redact-brand extortion demands issued last week. The group impersonates IT support in voice-phishing attacks using hundreds of recruited callers, targets large firms in what researchers call big-game hunting, and processes an average of 1.5 new victims daily. Extortion demands start around $3 million and are typically negotiated below $1 million; Flashpoint observed infrastructure targeting Blackstone, Bain Capital, Moody's, CME, and Apollo, though compromise is unconfirmed. Mandiant has responded to more than two dozen BlackFile compromises since January, and victims face escalation tactics including swatting.
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Fake Apple Support AI Calls Target Stolen-Device Owners for Passcodes and 2FA Codes
SOCRadar details AnonyMousKIT, a phishing-as-a-service platform using AI voice agents posing as Apple Support to steal passcodes and 2FA codes.
SOCRadar's Threat Research Unit documented AnonyMousKIT, a credit-metered phishing-as-a-service platform that strips Activation Lock from stolen Apple devices across email, SMS, WhatsApp, recorded calls and AI voice agents. The 'Alice from Apple Support' personas request the device passcode, Apple ID credentials and a live 2FA code, with lures citing the handset's model identifier and live Find My status. Of 200 recovered AI calls made between August 31, 2025 and May 30, 2026, 179 targeted Brazil, and the calls cost $19.24 total via voice platform Vapi. Exposed log paths revealed 30 kit installations on 42 domains and 6,092 send attempts family-wide between March and July 2026.
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How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code
Hugging Face explains how Inference Endpoints, Jobs, and Buckets power semantic search on Papers with Code.
Hugging Face describes the infrastructure behind search on Papers with Code, built on its Inference Endpoints, Jobs, and Buckets services. The post is a product-focused engineering walkthrough with no security impact.
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Why the current tech backlash feels different
The Verge's Decoder mailbag discusses the current tech backlash, arguing AI hype overstates verifiability outside software engineering.
Nilay Patel's Decoder mailbag episode addresses listener feedback on the widely discussed 'software brain' essay. He argues AI hype is concentrated on software because code is verifiable through compilation, while domains like drug discovery, math and science lack equivalent verifiability. The episode also touches on AI backlash, surveillance, data centers and upcoming midterm coverage.
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Studying Image Tokenizers as Visual Languages in Unified Multimodal Models
A controlled autoregressive testbed shows validation losses must be analyzed per task, and image tokenizer choice affects joint multimodal text modeling.
Researchers built a pure-autoregressive testbed to study image tokenizers as the 'visual language' of unified multimodal models, tracking task-specific validation losses during multimodal continual pretraining across text, image, text-to-image (T2I), and image-to-text (I2T) prediction. They found that losses exhibit distinct scaling behavior per task and rank tokenizers differently, and that I2T loss over a shared text vocabulary gives a more consistent loss–performance signal than T2I loss. Better reconstruction does not necessarily yield lower task-specific losses or stronger downstream performance, and tokenizer choice can affect text modeling under joint optimization. Case studies examine the discriminator, semantic supervision, and vocabulary size design axes.
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Ransom Busters Claims It Hacked Ransomware Servers, Asks Victims for Up to $60,000
GuidePoint reports a ransomware affiliate posing as 'Ransom Busters' charges victims $20,000-$60,000 to delete stolen data, and details UNC6671's $8M AitM extortion wave.
GuidePoint's GRIT team reports that 'Ransom Busters', likely a ransomware affiliate active across multiple RaaS operations including DragonForce, Settra and Anubis, proactively emails victims claiming it deleted their stolen data and backups for a $20,000-$60,000 fee, citing claimed access to RaaS administrative panels for over three years. Two analyzed intrusions shared tooling: SoftPerfect Network Scanner for reconnaissance, s5cmd-based exfiltration to AWS cloud storage, an RMM tool installed via PowerShell, a backdoor account with password 'Numlock!123' and the same attacker hostname DESKTOP-BBETH6K. Separately, GRIT detailed UNC6671's (Cordial Spider) adversary-in-the-middle vishing operation running since April under five extortion brands, with more than $8 million across 15 Bitcoin wallets, an average of $600,000 per payment, and 78 phishing sub-domains across 76 organizations, 40% in financial services.
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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.
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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.
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From Reweighting to Rewriting: Unlocking the Intervention Effects of Influential Samples in Training Data Attribution
Study shows rewriting responses of influence-selected training examples shifts LLM behavior more strongly than reweighting the same samples.
The paper examines training data attribution, arguing that influence functions identify high-leverage examples whose value goes unrealized under conventional weight-based reweighting interventions. It introduces influence-guided response rewriting, which replaces the responses of influence-selected examples with behavior-aligned or behavior-opposed supervision while keeping instructions fixed, tested across four open-weight LLMs using epistemic abstention as the primary testbed. Rewriting produces stronger, more persistent, and bidirectional behavioral shifts, including on safety refusal, while reweighting the same examples yields weak, inconsistent effects. The results motivate intervention-aware evaluation of TDA methods.
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When will average people feel AI’s impact?
Interconnects essay argues AI's impact is still a rounding error for average people, comparing looming wage stagnation to Engels' pause.
An Interconnects essay argues that AI currently touches daily life far less than previous industrial revolutions, since its benefits are concentrated in knowledge work and lack tangible consumer goods. The author invokes Engels' pause (1790-1840), when British wages stagnated amid rapid GDP growth, as a warning that popular backlash could kneecap AI's development. He contends the current phase is about building compounding infrastructure, and predicts daily life may look similar even 50 years from now.
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AgenticGen: Reward-Guided Agentic Video Generation for Advertising
AgenticGen applies DPO and GRPO reward-guided reasoning to ad video generation, improving TikTok CTR 2.72%, CVR 2.63%, and Advv 9.61%.
AgenticGen decomposes advertising video generation into two trainable reasoning stages, strategy selection and draft generation, supervised by online business feedback. It learns a performance-based reward from accumulated online feedback plus a rubric-based reward aligned with human quality standards, then optimizes policies with DPO followed by GRPO using process and outcome rewards. Online A/B experiments in the TikTok advertising system show CTR up 2.72%, CVR up 2.63%, and Advv up 9.61% over an SFT baseline.
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Extortion crews have their eyes on high-value AI data, Google warns
Google's Mandiant warns extortion crews now steal proprietary AI models, prompts, and research for ransom, while threat actors automate attacks with agentic AI.
Google's AI Threat Tracker details intrusions in which extortion crews exfiltrated healthcare drug research and a proprietary AI model, and stole an AI media company's source code, prompts, skills, model scripts, and secrets, threatening leaks unless paid. TeamPCP (UNC6780), behind large open-source supply chain attacks on PyPI, npm, and Docker Hub since March, used a malicious GitHub Actions workflow to exfiltrate a company's proprietary AI repository. Mandiant also observed a fully autonomous multi-agent credential-harvesting cloud intrusion completed in under six hours, and a China-linked espionage group using Gemini to build a dynamic automated penetration-testing framework.
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Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers
Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.
Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.
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Amasty patches dozens of Magento extensions, 2 critical
Amasty patched dozens of Magento/Adobe Commerce extensions, including two critical flaws allowing unauthenticated web shell upload and remote code execution.
Extension vendor Amasty released fixes for a large batch of Magento and Adobe Commerce modules, with critical unauthenticated file upload flaws in Advanced Product Reviews and Gift Card that allow attackers to plant web shells and take full control of stores. Dozens of additional high-, medium- and low-severity extensions were also patched. The vendor says the release affects almost every Magento and Adobe Commerce store. A related Order Attributes flaw was previously exploited heavily, with Sansec Shield blocking over 12,000 attempts against 25% of Magento stores in three days.
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Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing
A study of 180 US workers found each LLM phishing personalization level raised click-intention odds by 28%, but credibility depends on context fit.
The arXiv paper evaluates how personalized pretexts in LLM-generated spear phishing affect perceived credibility, using 180 US working adults across 1,436 evaluations of emails with four cumulative personalization levels, from workplace context to shared-project details. Convincingness rose 2.40 points per level in sensitivity analysis and click-intention odds increased 28% per level, while non-clickers shifted toward deleting rather than reporting. Qualitative coding showed details matching the recipient's role and routines supported credibility, whereas incorrect, vague, or channel-inappropriate details raised suspicion. The authors argue personalization effectiveness depends on pretext fit, with implications for workplace security training.
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When the Attacker Wears Your Logo: Detecting and Taking Down Impersonation at AI Speed
Cyble details how attackers use lookalike domains and cloned sites for brand impersonation scams and how AI-speed detection enables rapid takedowns.
Cyble describes the growing risk of digital impersonation, where attackers register lookalike domains, clone websites, create fake executive profiles, publish fraudulent job ads, and imitate customer-support accounts without ever breaching the legitimate organization. The goal is to borrow a trusted brand's credibility to make scams look legitimate, with particular risk for professional services, financial, legal, and consulting firms. The piece outlines AI-assisted approaches for detecting and taking down impersonation infrastructure quickly.
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Claude Fable 5.1 made me a really nice animated pelican
Anthropic launched Claude Fable 5.1, claiming gains in coding and long-running tasks, with 52.6% on Terminal-Bench-Science 0.1.
Anthropic released Claude Fable 5.1 (alongside Mythos 5.1), positioning it as a new standard for coding, knowledge work, and long-running problem-solving. The model scores 52.6% on Terminal-Bench-Science 0.1, up from 24.7% for Fable 5, versus 29.0% for Opus 5 and 22.4% for GPT-5.6 Sol. Simon Willison's hands-on test found the model produced an impressive animated pelican, though he notes other benchmarks show only slightly improved scores.
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Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation
A distillation framework compresses LLM reasoning into a 15.5M-parameter trade-up recommendation model reaching AUC 0.941 with product-type test-time training.
The paper targets trade-up recommendation, which identifies higher-quality alternatives that preserve customer purchase intent. A retrieval-augmented few-shot LLM teacher generates labels and rationales that supervise a compact embedding-pair classifier; at inference the 15.5M-parameter student uses only two precomputed 768-dimensional embeddings with no LLM calls. On 8,352 annotated pairs, label-only training scored AUC 0.912, reasoning distillation reached 0.924, and product-type test-time training lifted it to 0.941 with average precision 0.940. The distilled student is roughly 5,000x faster and 10,000x cheaper than direct LLM inference on a 100K-pair proxy catalog.
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General Quantification of Covariate and Concept Shifts
Paper proposes γ*-concept shifts via entropic optimal transport, deriving estimable generalization bounds unifying covariate and concept shift under distribution shift.
The authors show existing definitions of concept shift break when source and target supports mismatch and propose γ*-concept shifts grounded in entropic optimal transport. They derive a general error bound covering broad loss functions, label spaces and stochastic labeling, plus estimators with concentration guarantees. The resulting DataShifts algorithm quantifies distribution shifts and estimates the error bound in most applications, addressing learning bounds that were previously non-estimable from samples.
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Apollo discloses data breach from ongoing wave of attacks hitting financial sector
Apollo Global Management confirmed a breach of cloud platforms by BlackFile-linked social engineering attackers, exposing personal data including Social Security numbers.
Apollo Global Management disclosed that attackers accessed some of its cloud platforms between July 6 and July 10, 2026. The company determined on August 12 that compromised data included names, dates of birth, contact information, home addresses, and Social Security numbers. Google attributed the broader campaign against financial sector organizations to BlackFile, a threat group affiliated with The Com that operates extortion brands Redact, Pink, Helix, and Falcon. Apollo, which manages $1.05 trillion in assets, is the first victim to formally confirm sensitive personal data was compromised in this wave, with Blackstone and Bain Capital also reportedly targeted.
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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.
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Grand Theft Auto VI hype leads to malware
Fake GTA6 ISO downloads spread via SEO poisoning, torrents, and forums deliver NJRAT, DCRAT, an infostealer, and wiper ransomware.
Huntress analyzed a malicious ISO masquerading as a leaked Grand Theft Auto VI build; there is no official GTA6 demo or leaked playable copy. The fake gta6installer.exe shows a Russian 'license' message asking victims to email the attacker if the crack fails, then drops GTA6-branded files into %TEMP%. It installs multiple repurposed NJRAT copies (2023-era files) connecting to AWS-hosted IPs 35.157.111.131, 3.68.56.232, 3.67.15.169 and an ngrok tunnel, plus DCRAT communicating with a0700877.xsph.ru (141.8.197.42). The bundle also includes an infostealer and ransomware used as a wiper, in what appears to be an opportunistic, everything-at-once campaign.
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Quoting Rick Brewster
Paint.NET added a clean-room Direct2D rewrite for WINE, largely written by Anthropic's Claude and described as unreviewed 'vibe coded' code.
Rick Brewster says Paint.NET now ships a from-scratch, reverse-engineered Direct2D implementation (PaintDotNet.Windows.Direct2D1.Managed.dll) used under WINE via a /wine flag, since Direct2D was never completed well enough there. He credits the Claude coding assistant with writing most of the code, calling it largely 'vibe coded' and not thoroughly reviewed. Simon Willison shared the quote as an example of shipping AI-assisted systems code in production software.
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