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SloppyRAT: A New Tool For Ransomware Attacks

Zscaler details SloppyRAT, a new DLL backdoor delivered via ClickFix lures that stages CastleLoader and CastleRAT ahead of ransomware attacks.

Zscaler ThreatLabz analyzed SloppyRAT, a DLL-based backdoor distributed via ClickFix lures that abuses finger.exe over TCP port 79 to download a batch script. The malware copies curl.exe to download IronPython 3.4.2 from GitHub and executes zlib-compressed Base64-encoded Python to deploy CastleLoader and CastleRAT, then reflectively loads SloppyRAT in memory. It hinders analysis using XOR stack-string obfuscation, a modified affine cipher with modulus 127, and 13 runtime-decrypted code blocks, while communicating with C2 over a reverse SOCKS channel.

Zscaler ThreatLabzupdated · 5d agofirst · 6d agoMalware in the wild 3 sources

Red Heron Hackers Exploit Critical Gitea RCE to Steal Source Code and Deploy Linux Rootkit

PRC-linked Red Heron exploits critical Gitea RCE CVE-2026-60004 to steal source code and deploy JITTERLY implant with SIXZUT LD_PRELOAD rootkit; victims span five countries.

Acronis Threat Research Unit attributes a campaign to Chinese-speaking threat actor Red Heron, which weaponized CVE-2026-60004, a CVSS 9.8 RCE in Gitea versions 1.17 through 1.27.0, patched in 1.27.1 on July 27, 2026. The actor built an automated exploitation framework after a public PoC appeared, scanned 1,386 internet-exposed Gitea instances across seven countries, and separately listed 477 Taiwan-based systems across defense, energy, elections, and AI sectors. Confirmed victims include organizations in Canada, Argentina, Taiwan, the US, and Sri Lanka, with a Canadian renewable-energy firm hit in 22 sessions and a Taiwanese industrial automation firm losing hundreds of repositories including SCADA/HMI tools. Red Heron deploys the JITTERLY Linux implant (30+ commands, AES-128-GCM, Adaptix-like protocol) and the SIXZUT LD_PRELOAD rootkit disguised as libglthread.so.2, and moved laterally into a Synology/Proxmox environment to steal VM backups.

GBHackers · 1d agoThreat actor in the wild 3 sourcesCVE-2026-6000410

China-Linked Hackers Exploit Chrome-Windows Zero-Day Chain to Deploy GRIMWEDGE

Volexity attributes spear-phishing campaign exploiting Chrome-Windows zero-day chain to Chinese actors UTA0560 and APT31 deploying GRIMWEDGE and LONGTALE.

Volexity attributes a September 1, 2026 spear-phishing campaign targeting NGOs to China-linked UTA0560, which abused a reflected XSS flaw on a US university website to trigger a three-part exploit chain (CVE-2026-85046, CVE-2026-87491, CVE-2026-85880) escaping the Chrome V8 and browser sandboxes to deploy the GRIMWEDGE JavaScript backdoor with reconnaissance, file management, and command execution capabilities. The same chain was used near-simultaneously by JungleBamboo (APT31) to deploy SUPERSTOMP, installing the LONGTALE/GemStone credential-stealing Chrome extension masquerading as Google Gemini. The Chrome flaws were patched in Chromium but not yet in stable Chrome, creating an unusual patch-gap zero-day window attackers raced to exploit.

The Hacker Newsupdated · 46m agofirst · 1d agoThreat actor in the wild 19 sourcesCVE-2026-85046CVE-2026-87491CVE-2026-858801· 1 read

RANCOR: Targeted Attacks in South East Asia Using PLAINTEE and DDKONG Malware Families

Unit 42 names RANCOR, a previously unidentified espionage group targeting Southeast Asian political entities with newly discovered PLAINTEE and DDKONG malware families.

Unit 42 tracks a previously unidentified group it dubs RANCOR conducting highly targeted espionage attacks in Singapore and Cambodia using two custom malware families, DDKONG and PLAINTEE. Attacks appear to have begun with spear phishing, with decoy political news documents hosted on legitimate sites including a Cambodian government website and Facebook. Infrastructure links to IP 89.46.222[.]97 and KHRAT-associated domains such as facebook-apps[.]com, and the activity is grouped into two clusters tied together by PLAINTEE usage and similar targeting.

Palo Alto Unit 42 · Aug 17, 2026Threat actor1

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

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

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

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

Rare Not Random Using Token Efficiency for Secrets Scanning

Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.

The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.

Lobsters · security · 4d agoResearch

Bad Likert Judge: A Novel Multi-Turn Technique to Jailbreak LLMs by Misusing Their Evaluation Capability

Unit 42 details the Bad Likert Judge multi-turn jailbreak that abuses LLMs' evaluation capability, raising attack success rates over 60% across six frontier models.

Palo Alto Networks Unit 42 describes the Bad Likert Judge technique, a multi-turn jailbreak that asks a target LLM to act as a Likert-scale judge scoring the harmfulness of example responses. The highest-rated example in each scale can carry harmful content, bypassing the model's internal guardrails. Testing across six state-of-the-art text-generation LLMs showed an average attack success rate increase of more than 60% versus plain attack prompts, with tested models anonymized. The technique targets edge cases rather than typical use, and the article positions the work as guidance for defenders on potential jailbreak risks.

Palo Alto Unit 42 · Aug 17, 2026AI safety & security

I Am No One: Style-Aware Paraphrasing for Text Anonymization

Prompt-driven style-aware paraphrasing with LLMs cuts authorship attribution F1 by 60-70% while preserving content quality.

The paper proposes a style-aware, prompt-driven anonymization approach using pretrained LLMs to build compact stylistic profiles from minimal samples and rewrite text to suppress identifiable style markers while preserving meaning. It addresses stylometric re-identification risks in anonymized text, including ASR transcripts of meetings and call-center calls where leakage persists after acoustic anonymization. Across blog and review datasets, the approach reduces authorship attribution F1 by 60-70%, substantially outperforming both DP-based and non-DP baselines while maintaining readability.

arXiv cs.CR · 5d agoResearch

Hackers Disable Endpoint Protection and Deploy Sliver Across Compromised Windows Domain

The Hunter's Ledger tracked campaign UTA-2026-024 using Sliver C2, Domain Admin account creation, and Ethereum-based C2 rotation to compromise a US organization's Windows domain.

The Hunter's Ledger tracked an intrusion at one unnamed US organization as UTA-2026-024, staged from exposed server 193.233.202.17 with a Sliver beacon. Operators created a non-expiring Domain Admin account, enabled RDP with NLA disabled, dumped SAM, SYSTEM and SECURITY hives plus LSASS memory, and disabled eight endpoint protection services. A Node.js implant resolved its C2 server from an Ethereum smart contract that rotated domains five times in five months, while SYSTEM scheduled tasks with backdated dates and DNS allowlist manipulation provided persistence. The infrastructure ties to a confirmed ransomware incident, but no encryptor deployment was proven in this intrusion.

Cyber Security News · 8d agoThreat actor in the wild

Foul Language: WordlistLoader Disguises Malware as Ordinary Text

ClickFix-style campaigns deploy WordlistLoader, which disguises malware as ordinary text, to deliver the increasingly prevalent Amatera infostealer.

Researchers describe WordlistLoader, a new loader that disguises malicious payloads as ordinary text or wordlist files to evade detection. It is being used in ClickFix-style social engineering campaigns to deliver Amatera, an increasingly prevalent infostealer. The obfuscation technique helps the campaign slip past file-type-based inspections.

Dark Reading · 22d agoMalware in the wild

Enhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation

Study shows LLMs with Mixture-of-Agents and QLoRA finetuning effectively simplify medical texts into plain language while preserving content.

The paper evaluates Plain Language Adaptation (PLA) using GPT-4o-mini, Gemini-1.5-pro, and LLaMA in zero-shot and few-shot settings. It compares prompting strategies, QLoRA finetuning across models, and integrates Mixture-of-Agents (MoA) techniques for robustness. Results demonstrate LLM-driven PLA makes healthcare texts more comprehensible while retaining essential content.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

VectraRAT: An Undocumented Full-Stack MaaS Built From Scratch

SOCRadar's Threat Research Unit documents VectraRAT, a previously unreported full-stack Malware-as-a-Service platform built entirely from scratch.

SOCRadar's Threat Research Unit (STRU) documented VectraRAT, an undocumented Malware-as-a-Service platform. Unlike most MaaS offerings derived from leaked builders, VectraRAT was built entirely from scratch. The report details the platform's architecture and capabilities offered to affiliate customers.

SOCRadarupdated · 3h agofirst · 2d agoMalware 3 sources

Post-DEF CON Phishing Uses Malicious Google Doc to Deliver Malware

Huntress uncovered post-DEF CON phishing via X direct messages using a malicious Google Doc to deliver AMOS and NetSupport RAT malware.

Huntress uncovered a phishing campaign targeting attendees after Black Hat and DEF CON. Attackers used X direct messages pointing to a malicious Google Doc as the delivery vehicle. Payloads include AMOS, a macOS infostealer, and the NetSupport RAT, among other malware.

Huntress · 28d agoPhishing & fraud

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.

arXiv cs.CR · 12d agoResearch

Type Diversity Enables Transformers to Generalise Compositionally

Researchers show lexical-versus-structural compositional generalization gaps in Transformers stem from type diversity imbalance in datasets, not architectural limits.

The paper argues that Transformers' difficulty with structural compositional generalization is an artifact of low structural type diversity in prior benchmark datasets rather than an architectural limitation. Using Grammatical Framework, the authors create linguistically diverse variants of COGS and SLOG. They find type diversity correlates with compositional generalization equally in lexical and structural test cases, contradicting previous claims that compound divergence explains task difficulty.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

Google Doc Sidebar Sends Mac and Windows Users Down Different Paths to Malware

Huntress analysts trace one X direct message into separate Mac and Windows malware chains delivering AMOS infostealer and NetSupport Manager RAT.

Huntress SOC analysts dissected a malware campaign distributed via an X direct message styled as a Google Docs sidebar. macOS users were routed to the AMOS infostealer, while Windows users received NetSupport Manager remote access malware. The write-up details how a single message branched into two distinct delivery paths per operating system.

Huntress · 5d agoMalware in the wild

Akira Affiliate Crashes Ransomware After Attempting EDR Evasion

Huntress documented an Akira ransomware affiliate attack that failed after its anti-EDR tool crashed legitimate software and stopped encryption before completion.

Infosecurity Magazine reports on Huntress research into a failed Akira ransomware affiliate attack. The affiliate attempted EDR evasion using an anti-EDR tool, but the tool interfered with legitimate software on the client's system. The interference crashed the ransomware before encryption completed, sabotaging the attack; no completed encryption was reported.

Infosecurity Magazine · Aug 13, 2026Ransomware

GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

GraphProfiler links LLM attribute inferences to source posts via personal knowledge graphs, enabling targeted redaction of privacy-leaking content.

GraphProfiler represents a user's post history as a source-linked personal knowledge graph where nodes and edges trace back to originating posts, making LLM-based attribute inference auditable. It reaches 86.7% attack success rate on the eight-attribute SynthPAI benchmark and 84.6% on PANDORA, within two points of strong text-only baselines, while citing supporting evidence for over 98% of predictions. Ablation experiments show removing cited posts reduces attack success substantially more than removing random posts, supporting targeted privacy mitigation.

arXiv cs.CR · 5d agoResearch1

Hackers Are Hiding Espionage Infrastructure Inside Ordinary-Looking Casino Websites

Infoblox links China-aligned APT PeckBirdy C2 infrastructure hidden in casino and adult websites targeting Asian government, finance, IT, and education sectors.

Infoblox researchers report that China-aligned APT groups have used casino and adult websites as cover for PeckBirdy, a JavaScript command-and-control framework active since 2023. The sites embed C2 servers, register service workers for persistence, and serve fake browser-update prompts delivering backdoors capable of running commands, stealing credentials, and providing remote access. Targeted sectors across Asia include education, IT, banking, financial services, and government. Just over 3% of Infoblox enterprise customers resolved at least one PeckBirdy C2 domain, with detection coverage on VirusTotal ranging from 13 detections to none.

Cyber Security News · 6h agoThreat actor 2 sources

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

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

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.CL · 1d agoAI research

Structural Jailbreaks Generalize but Do Not Compound: A cross-provider and multilingual study of Involuntary In-Context Learning

Researchers show IICL structural jailbreaks generalize to Google Gemini, lifting attack success to 80-100% on harm and financial benchmarks; non-English prompts attenuate it.

The study red-teams two Google Gemini models with Involuntary In-Context Learning (IICL), a structural jailbreak reframing harmful requests as the final cell of a data-labeling task. IICL lifts attack success from at most 6.7% to 80-90% on HarmBench and 97-100% on financial abuse (FinProof), an order of magnitude above prior results on OpenAI's GPT-5.4. Against a compounding hypothesis, forcing IICL output into Spanish, Hindi, or Arabic attenuates the attack in 11 of 12 conditions, attributed to a 'relevance curse' producing lower-quality harmful content in lower-resource languages. Findings replicate under an independent non-Google judge (Cohen's kappa 0.86 over 377 paired verdicts).

arXiv cs.CR · 8d agoAI safety & security

Next-Gen Phishing Tactics Users Aren’t Ready For | Huntress

Huntress details modern phishing tactics including ClickFix, browser-in-the-browser, and OAuth consent phishing beyond basic credential harvesting.

Huntress describes a shift in phishing attacks beyond basic credential harvesting toward advanced tactics. Covered techniques include ClickFix social engineering, browser-in-the-browser (BitB) attacks, and OAuth consent phishing. The post recommends training users on these patterns through Huntress SAT simulations.

Huntress · 19d agoPhishing & fraud in the wild1

Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation

OPRD distillation enables weak-to-strong generalization by amplifying verifier-supported policy updates, outperforming existing RL and distillation methods with fewer student updates.

On-Policy Reverse Distillation (OPRD) evaluates a weak teacher's policy shift relative to its reference policy on student rollouts and amplifies the verifier-supported component of the student's policy gradient. This rescaling preserves the stationary points of policy optimization while letting the student learn beyond the teacher's capacity ceiling. In successive model transfer and multi-teacher distillation, OPRD achieves higher performance with fewer student updates than existing RL and distillation approaches, and response-style analysis shows students remain closer to verifier-RL-trained models than to their weak teachers.

Hugging Face daily papers · 8d agoAI research

PrivAudit: A Dual-Lens Auditing Framework for Website Privacy Practices under the CCPA

PrivAudit framework audits 998 websites for CCPA compliance, finding stronger disclosures but pervasive, weakly responsive third-party cookie tracking.

PrivAudit is an automated dual-lens auditing framework combining LLM-based analysis of privacy policies grounded in CCPA provisions with automated browser measurements of cookie writes under diverse privacy configurations. Applied to 998 websites, it finds CCPA-subject sites disclose opt-outs, data sharing, and user rights more frequently, yet tracking remains pervasive: 6,392 targeting cookies, 49% third-party writes. Cookies show limited-to-moderate responsiveness to privacy signals and consent choices even when sites claim to honor them. The framework is open-sourced and shared with regulators.

arXiv cs.CR · 7d agoResearch

PaperCut Zero-Day: Active Exploitation and Pre-Auth RCE

PaperCut NG/MF hit by a pre-auth RCE zero-day under active exploitation; Huntress reproduced the chain and urged immediate patching.

Huntress reports active exploitation of a zero-day in PaperCut NG and PaperCut MF, and says it reproduced a pre-authentication remote code execution chain. The flaw allows unauthenticated attackers to execute code on exposed PaperCut servers. Huntress published urgent patching, exposure-reduction, and detection guidance. No CVE identifier was provided in the announcement.

Huntress · 19d agoExploit / PoC in the wild

Hackers Use Cross-Platform Noodle RAT to Secretly Control Windows and Linux Systems

Check Point identifies Noodle RAT as a distinct cross-platform Windows/Linux backdoor used by Chinese-speaking actors against Asia-Pacific organizations since 2016.

Check Point assesses Noodle RAT, also known as ANGRYREBEL, as a distinct backdoor family rather than a variant of Gh0st RAT or Rekoobe, with separate Windows (Win.NOODLERAT) and Linux (Linux.NOODLERAT) variants sharing a common command-and-control design. The Windows implant runs filelessly via shellcode with loaders like MULTIDROP and MICROLOAD, while the Linux variant provides reverse shells, file management, and SOCKS tunneling after exploitation or web-shell placement on exposed servers. Groups including Iron Tiger, Calypso APT, Rocke, and Cloud Snooper have deployed it against organizations in Thailand, India, Japan, Malaysia, and Taiwan. Check Point released sample hashes and C2 IP indicators alongside the analysis.

Cyber Security News · 3h agoMalware in the wild 2 sources