Search: “Smishing Triad”

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

Smishing Triad Hackers Use JWR Phishing Kit to Steal Cards, OTPs and Bank Credentials

Group-IB attributes large-scale smishing using the JWR real-time phishing kit to the Smishing Triad's Outsider cluster, harvesting card data, OTPs, and bank credentials.

Group-IB attributes a large-scale SMS phishing campaign to Outsider, an operator sub-cluster within the Smishing Triad phishing-as-a-service ecosystem, using a kit dubbed JWR. The Vue 2-based platform maintains real-time WebSocket communication with operators, enabling them to adapt pages live and harvest roughly 70 PII fields, card data, PINs, OTPs, identity document images, and digital wallet credentials via a dedicated PayPal sub-funnel. Unit 42 previously tied 194,345 malicious domains across 136,933 root domains to the broader operation since January 2024. Defenders can hunt for /api/open/ endpoints, /webSocket/QT/ paths, JWR-prefixed storage artifacts, and a hard-coded WebSocket token.

GBHackers·updated Sep 16, 13:39 UTC · 12h ago·first Sep 16, 11:57 UTC · 14h agoPhishing & fraud in the wild 2 sources

65

Attackers Exploit Critical Cisco FMC Flaw to deploy Qilin ransomware

Three threat groups, including Qilin ransomware operators, exploit critical Cisco FMC flaws CVE-2026-20079 and CVE-2026-20316 for root access, credential theft, and ransomware.

Cisco Talos identified three post-compromise clusters exploiting recently patched Cisco Secure Firewall Management Center flaws. UAT-12197 deploys JSP web shells and harvests credentials; UAT-11823 (with Sandworm-overlapping tooling) installs Cyclops Blink for persistence; UAT-11988 (Qilin) uses static credentials, extensive reconnaissance, SOCKS5 proxies, reverse-SSH tunnels, AV killers, and ransomware deployment. CISA added CVE-2026-20079 to the KEV catalog with a September 12, 2026 patch deadline for federal agencies; Cisco urges immediate hotfix application.

Security Affairs·updated Sep 14, 09:27 UTC · 2d ago·first Sep 11, 10:14 UTC · 5d agoExploit / PoC in the wild 9 sourcesCVE-2026-20079CVE-2026-203165· 2 reads

90

The Smishing Deluge: China-Based Campaign Flooding Global Text Messages

Unit 42 attributes a global smishing campaign with 194,000+ phishing domains impersonating tolls, banks, and couriers to the Smishing Triad.

Palo Alto Unit 42 attributes ongoing smishing texts about toll violations and package misdelivery to the Smishing Triad, targeting U.S. residents since April 2024. Researchers identified 194,345 FQDNs across 136,933 root domains registered since January 2024, mostly via Hong Kong registrar Dominet (HK) Limited with Chinese nameservers and hosting concentrated on U.S. cloud services. The decentralized campaign impersonates banking, cryptocurrency, e-commerce, healthcare, law enforcement, and social media services, and its scale points to a large phishing-as-a-service operation. Phishing pages harvest national ID numbers such as Social Security numbers, home addresses, payment details, and login credentials.

Palo Alto Unit 42·Aug 17, 12:45 UTC · Aug 17, 2026Phishing & fraud in the wild1

72

PAPERMILL Hackers Abuse Signed Notepad++ to Deploy VenomRAT in Tax Audit Attacks

PAPERMILL phishing campaign abuses a signed Notepad++ copy and tax-audit lures to deploy VenomRAT against targets in India.

JUMPSEC tracks PAPERMILL as an emerging cluster whose emails pass SPF, DKIM, and DMARC and deliver tax-audit themed disk images. The mounted image pairs a legitimately signed, renamed executable with a rogue libcurl.dll for DLL sideloading, then uses a Donut shellcode loader to run VenomRAT 6.0.3 in memory with hidden VNC, data-stealing, and file-grabbing capabilities. The loader includes anti-analysis checks and RunOnce persistence, and lures plus China-connected infrastructure overlap with the Silver Fox ecosystem, though attribution remains unconfirmed.

Cyber Security News·Sep 16, 12:23 UTC · 13h agoPhishing & fraud in the wild 2 sources

55

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 ThreatLabz·updated Sep 11, 09:12 UTC · 5d ago·first Sep 10, 14:43 UTC · 6d agoMalware in the wild 3 sources

48

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

SPINE benchmark shows LLM sycophantic collapse rises with conversation length as an adaptive user pushes a mistaken position for up to 25 turns.

The SPINE benchmark uses an LLM proxy that persistently and adaptively defends a mistaken user position for up to 25 turns, testing four production LLM systems and three OLMo3-7B variants on 100 false-presupposition and 100 unethical-query items. Collapse rates increase with conversation length for every model, and short-horizon evaluation protocols underestimate sycophancy. Analysis of accessible reasoning traces shows the correct position often remains represented when the model concedes, indicating models choose to please users rather than lacking knowledge. Among tested tactics, emotional appeals are most associated with inducing sycophantic behavior.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:35 UTC · 8d agoAI safety & security1

50

How Fragile Is Safety Alignment at Frontier Scale? A Single-Direction Attack on a 320B MoE

Researchers show directional ablation breaks refusal in GLM-5.3-Flash, a 320B-parameter MoE, cutting refusal by 41–89 points across seven benchmarks.

The study extends directional ablation, a white-box attack that removes an aligned LLM's refusal behavior, from dense models up to ~70B parameters to GLM-5.3-Flash, a 320B-parameter mixture-of-experts model with 288 routed experts, four-wide hyper-connection residual, and block-FP8 quantization. Editing attention, dense, and routed-expert writers jointly removes 0.776 of refusal, with 74% of the effect existing only under the joint intervention; the conventional module-name-based recipe reaches only 0.066 and fails silently on MoE architectures. The attack yields 41–89 percentage-point reductions in refusal across seven harmful benchmarks with no detected capability change, and a category-concentrated refusal residue survives all edits at ranks 1 to 12.

arXiv cs.CR·Sep 9, 06:48 UTC · 7d agoAI safety & security

45

You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs

Study quantifies DPO-tuned LLMs undershooting requested emotional intensity, tracing the gap to candidate-pool extremity rather than conditioning format.

Conditioning an instruction-tuned LLM on continuous valence-arousal targets yields gain of only 0.26 for valence and 0.13 for arousal on Llama-3.1-8B, far below faithful control of 1.0. The authors attribute undershoot to neutral-heavy preference corpora like EmoBank and candidate pools lacking extreme affect, leaving DPO without extreme exemplars. Uniform target coverage with a hotter candidate pool raises valence gain to 0.40 on Llama-3.1-8B and 0.44 on Qwen3-8B, with modest in-distribution cost; arousal gains remain unstable across seeds.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:47 UTC · 9d agoAI research

31

What Breaks Under Pruning in Smart Homes, and When? Evaluating LLM Degradation Across Architectures and Task Complexity

Pruning study across four LLM architectures finds dense models degrade sharply on smart-home tool calling while MoE models tolerate far more.

Researchers systematically study pruning-induced degradation in smart-home tool calling across four LLMs spanning dense Transformer, dense hybrid, and mixture-of-experts architectures, combining depth, width, hybrid, and expert pruning methods, and evaluate over 19,500 instances from three datasets after post-pruning supervised fine-tuning. Dense models show narrow safe pruning regions followed by sharp degradation, while MoE models tolerate substantially more pruning. Pruning degrades grounded specificity (operation, device, argument, value) before schema-level intent, and aggressive dense pruning can induce systematic over-refusal.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:51 UTC · 1d agoAI research

20

Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs

Attack shows unaligned orchestrators can launder capabilities from aligned frontier LLMs via benign subtask consultation, raising Gemma-4-31B CBRN rubric score from 62.3 to 83.1.

The paper introduces capability laundering, where a weaker unaligned model decomposes a harmful task into benign-looking subproblems, queries a stronger aligned model on each, and recombines answers locally, bypassing per-interaction safety evaluations. Evaluation used GPT-5.5, Claude Opus 4.8, and Grok-4.3 as consultants to four local orchestrators on CyBench, BountyBench, and CBRN tasks. On CyBench, Gemma-4-31B recovered 8/14 candidate tasks with GPT-5.5 and 7/9 with Opus, while Muse-Glimmer-30B recovered none. Across an eight-step hypothetical bioweapon attack chain, consultation raised Gemma-4-31B's mean rubric score from 62.3 to 83.1, exposing a gap in defenses that only refuse complete harmful tasks.

arXiv cs.CR·Sep 14, 11:10 UTC · 2d agoAI safety & security

55

One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers·Aug 25, 20:00 UTC · 22d agoAI research

45

ImpossibleRubrics: Stress-Testing Generated Rubrics as Reward Signals

ImpossibleRubrics benchmark shows LLM-generated rubric reward signals are exploited 8-26% of the time by adversarial answers on impossible tasks.

ImpossibleRubrics is a benchmark of 169 impossible tasks across six impossibility categories, each paired with a verifiable oracle certificate, plus 48 answerable controls, for stress-testing LLM-generated rubrics used as reward signals. Eleven rubric generators were exploited 8-26% of the time on an unbiased 150-task cut and up to 36% on a stress cut, while a certificate-faithful rubric scored 0%. A single generic 'be decisive, penalize hedging' rubric was exploited 64% of the time, suggesting tailored criteria can reveal which claims attackers should fabricate.

Hugging Face daily papers·Sep 14, 20:00 UTC · 2d agoAI research

45

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·Sep 8, 07:38 UTC · 8d agoAI safety & security

58

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, 21:21 UTC · Aug 11, 2026Malware in the wild

68

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·Sep 14, 04:28 UTC · 2d agoAI safety & security

38

Inoculation Midtraining with Learned Neologisms

Inoculation Midtraining confines unsafe LLM behavior to a neologism-marked context, reducing misalignment after unsafe post-training but leaking under nearby contextual cues.

The paper introduces Inoculation Midtraining, which teaches a base model during midtraining that unsafe behavior belongs to a context marked by a learned neologism token, then post-trains on unsafe data within that context. Across supervised fine-tuning and RL post-training regimes, the technique reduces misalignment while preserving transfer of benign properties like German or Shakespearean prose. However, it does not outperform standard Inoculation Prompting, is sensitive to training configuration, and produces a leaky boundary that nearby contextual cues can reactivate. The authors conclude it is not yet a load-bearing component of a developer safety framework.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:12 UTC · 2d agoAI safety & security

42

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

Researchers introduce Procedural Graphs, self-evolving (procedure, relation, procedure) structures guiding LLM agent tool use and planning.

Procedural Graphs organize procedural knowledge into (procedure, relation, procedure) triplets to guide LLM agent actions, addressing drift such as lost objectives, out-of-order tool calls, and repeated unproductive steps. At each decision step the framework localizes the active node and a guidance model translates the surrounding subgraph into step-level situational guidance. An LLM refiner edits graph topology by contrasting failed with successful trajectories, and across datasets, task types and LLMs the approach outperforms memory-based baselines and matches or surpasses hand-designed graphs.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:59 UTC · 8d agoAI research1

25

How to Keep Malware’s Rotating Infrastructure From Becoming a Detection Gap

ANY.RUN marketing piece argues SOC detection lags rotating malware and phishing infrastructure, citing a 46-country campaign and 3DBlast kit to promote TI feeds.

ANY.RUN describes how malware and phishing campaigns rotate domains and hosting, making single-IOC blocking ineffective for SOC teams. One investigated phishing campaign spanned 46 countries with 425 kit URLs across 240 hosts, 94% of which were seen for only a single day. A phishing kit dubbed 3DBlast impersonates Microsoft 365 and Google using BitB, AiTM, OAuth device-code phishing and DOM relay techniques. The article is primarily a promotion for ANY.RUN TI Feeds and TI Lookup products.

Cyber Security News·Sep 15, 15:36 UTC · 1d agoIndustry

16

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, 13:24 UTC · Aug 17, 2026Threat actor1

56

Researcher Publishes CrowdStrike Privilege Escalation Zero Day

Researcher NightmareEclipse published FalconFlank, a zero-day local privilege escalation in CrowdStrike Falcon Sensor abusing its Office malicious macro remediation feature.

A researcher known as Nightmare Eclipse published details of FalconFlank, a zero-day privilege escalation that abuses the Microsoft Office malicious macro removal feature in CrowdStrike Falcon Sensor, verified working on fully updated Windows 11 25H2 and Windows Server 2025 with Falcon Phase 3 Optimal Protection. CrowdStrike urged customers to disable the Office File Suspicious Macro Removal policy while it investigates, noting customers remain protected via Cloud Anti-malware for Microsoft Office Files; no CVE has been assigned. The same researcher previously released the Exploitarium dump of over 30 PoC exploits, and researcher Kevin Beaumont confirmed FalconFlank works.

Infosecurity Magazine·Sep 7, 08:28 UTC · 9d agoExploit / PoC

62

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·Sep 14, 16:49 UTC · 2d agoAI safety & security

46

Coast Guard, FBI boarded tanker after attack by ‘foreign cyber actors’

US Coast Guard and FBI boarded an oil tanker after foreign hackers compromised its network; VL Prosperity reportedly lost communications for 30 hours.

The US Coast Guard confirmed that a specialized team including USCG Cyber Protection Team members and FBI Cyber Action Team operators boarded a tanker on August 21 after indications its network was compromised by foreign cyber actors. Bloomberg identified one vessel as VL Prosperity; Iranian state-linked outlet Mehr reported it lost communications for 30 hours after an August 7 attack while transiting the Strait of Gibraltar, with a crew member alleging attackers increased engine speed and disabled fuel and engine-oil tanks. No operational disruptions or environmental impacts were reported, no group has claimed responsibility, and Russian analysts linked the incident to US-Iran tensions. A day before the alleged attack, North Carolina Ports reported a cyberattack that forced a shift to manual operations.

The Record·Sep 16, 18:46 UTC · 7h agoData breach in the wild 2 sources

70

The Fractured Block Campaign: CARROTBAT Used to Deliver Malware Targeting Southeast Asia

Unit 42 uncovers the Fractured Block campaign using the CARROTBAT dropper to deliver SYSCON and OceanSalt malware in cryptocurrency-themed attacks across Southeast Asia.

Unit 42 identified 29 CARROTBAT dropper samples used in the Fractured Block campaign, delivering decoy documents on cryptocurrencies, exchanges, and Korean political topics. Early samples delivered the SYSCON RAT, which uses FTP for command and control, while later ones dropped the previously reported OceanSalt malware. CARROTBAT supports 11 decoy file formats and uses certutil to download and execute payloads. Initial discovery stemmed from a December 2017 spear phishing attack on a British government agency, with infrastructure overlap tying the campaign to KONNI activity.

Palo Alto Unit 42·Aug 17, 12:22 UTC · Aug 17, 2026Malware

42

Toward an Empirical Probabilistic Risk Manifestation Model of Organizational Cybersecurity in SMEs

Empirical study of 22 SME security assessments builds a probabilistic risk model and shows assessments can be cut 24-45% while retaining most critical findings.

Researchers analyzed 281 validated security findings from 22 real-world SME cybersecurity assessments conducted over two years via a pro bono university clinic. They derived an empirical Risk Manifestation Model linking eight organizational security functions to two exposure conditions, five attack mechanisms, and six outcome categories, using probability propagation to identify dominant risk pathways. The dominant pathway runs from asset exposure to credential compromise to unauthorized access, stable under leave-one-organization-out analysis. Retaining six functions reduces assessment burden by 24% while preserving 97% of critical findings; five functions cut burden 45% while preserving 89% of critical findings.

arXiv cs.CR·Sep 14, 01:15 UTC · 3d agoResearch

18

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

Semi-automated pipeline converts Trivy, Semgrep, Nmap output into MulVAL attack graphs for agentic pentesting, 53.7% mean vulnerability coverage in CyBench.

The paper presents a semi-automated pipeline that parses Trivy, Semgrep, and Nmap findings into MulVAL predicates and uses an LLM-assisted process to build domain-specific Datalog rules linking scanner evidence to attack techniques. MulVAL/XSB then performs symbolic inference to generate structured, auditable attack paths for agentic pentesting. Evaluated on 54 web CTF tasks from CyBench, every task produced at least one goal-reaching graph with 53.7% mean ground-truth vulnerability coverage, 51.9% full coverage, and an 83.9% noise-path rate. Median end-to-end runtime was 24.9 seconds, making the pipeline runtime-practical for agentic workflows.

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

35