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Recent Trends in Internet Threats: Common Industries Impersonated in Phishing Attacks, Web Skimmer Analysis and More

Unit 42 analyzed 67 million malicious URLs and domains in H2 2022, a 52% increase, highlighting phishing impersonation and web skimmer trends.

Unit 42 observed more than 67 million unique malicious URLs, domains and IPs between July and December 2022, a 52% increase over the first half of the year. Malicious JavaScript detections grew 99.3%, with over 4 million malicious JS samples hosted on 4.8 million URLs. Over 85% of hosting infrastructure was concentrated in eight countries, led by the United States, Brazil and China. The report also analyzes industries spoofed in phishing pages and includes a web skimmer case study on a Tranco top 1 million website.

Palo Alto Unit 42 · Aug 17, 2026Research

Introducing Unit 42’s Attribution Framework

Unit 42 releases its Attribution Framework, a systematic method using Diamond Model and Admiralty scores to attribute activity clusters to named threat actors.

Palo Alto Networks' Unit 42 introduced a structured framework for threat actor attribution built on the Diamond Model of Intrusion Analysis and Admiralty reliability/credibility scoring. The framework tracks activity at three levels: activity clusters (named CL-STA, CL-CRI, CL-UNK, or CL-MIX), temporary threat groups, and named threat actors using the constellation naming schema. Analysts score evidence across TTPs, tooling, malware code, OPSEC, infrastructure, timelines, and victimology to decide when to merge or elevate clusters, avoiding premature group naming.

Palo Alto Unit 42 · Aug 17, 2026Research

The Year in Web Threats: Web Skimmers Take Advantage of Cloud Hosting and More

Unit 42 analyzed 2.24 million web threat incidents, finding web skimmers increasingly hosted on cloud infrastructure to steal payment card data.

Palo Alto Unit 42 analyzed 2,241,354 web threat incidents and 831,550 unique URLs detected via Advanced URL Filtering between October 2020 and September 2021. Threat activity peaked from October 2020 to January 2021, coinciding with the holiday shopping season, with most malicious domains geolocated to the United States, Russia, and Germany. Web skimmers ranked third among the top five threat classes and showed the most code diversity, making detection harder. Researchers observed more web skimmer families being hosted on cloud platforms to steal payment data and PII.

Palo Alto Unit 42 · Aug 17, 2026Research

Observational Indistinguishability and Integrity Blind Regions in Hybrid Quantum-Classical Workflows

Framework formalizes integrity blind regions in hybrid quantum-classical workflows, validated across 3,600 label interventions with conformal detection rules.

The paper presents a claim-relative evidence and reference framework for integrity of hybrid quantum-classical workflows, distinguishing structural blind regions caused by observational indistinguishability from finite-batch statistical misses. Experiments over 3,600 label interventions show exact label-path invariance for feature and prediction views. The geometry-aligned construction detects 343 of 2,700 conclusion-changing interventions using the conformal rule and 1,183 of 2,700 with the uncorrected union, with executed conformal clean false-action rates of 0.048-0.059.

arXiv cs.CR · 1d agoResearch

Almost Half of Malware Samples Communicate Direct to IP

Unit 42 analysis of 4 million malware reports finds 45% of C2-active samples connect directly to hard-coded IPs, bypassing DNS defenses.

Palo Alto Unit 42 analyzed over 4 million Advanced WildFire dynamic analysis reports and found that 45.32% of malware samples with C2 activity made at least one direct-to-IP connection, accounting for 23.17% of all C2 connection attempts. The firm proposes zero trust IP (ZT-IP), an enforcement approach that verifies whether outbound destinations were ever sanctioned by a DNS response. ZT-IP analysis surfaced Phorpiex ransomware droppers fetching payloads directly from C2 IPs, a persistent data exfiltration campaign using an obfuscated \GET protocol, and Mozi P2P botnet payloads delivered to IoT devices without DNS. Only 1% of benign samples connected directly to untrusted IP addresses.

Palo Alto Unit 42 · Aug 17, 2026Research

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future · 21d agoResearch

Trends in Web Threats: Attackers Were More Active During Holiday Season

Unit 42 tracked 533,000 malicious landing URL incidents from October-December 2021, showing web threats peaked during the holiday shopping season.

Unit 42 detected 533,452 malicious landing URL incidents (120,753 unique) and 2,906,875 malicious host URL incidents (165,255 unique) from October through December 2021. Threat activity peaked in November, likely tied to Black Friday in the United States, United Kingdom, and Germany. Most malicious domains appeared to originate in the United States, followed by Russia and Germany. Personal sites, blogs, business sites, and shopping sites were the most common apparently benign entry points for attacks.

Palo Alto Unit 42 · Aug 17, 2026Research

Trends in Web Threats in CY Q2 2022: Malicious JavaScript Downloaders Are Evolving

Unit 42 detected 751,000 landing URL incidents in Q2 2022 and documented malicious JavaScript downloaders evolving to evade detection.

Unit 42 detected 751,331 landing URL incidents (253,644 unique) and 1,744,629 malicious host URL incidents (256,844 unique) from April through June 2022. Total landing URL incidents rose compared with Q1 2022, and unique host URL incidents grew 42%, indicating attackers deploying more variants. The report includes a case study of a JavaScript downloader campaign demonstrating new evasion techniques. Personal sites, blogs, and business sites were the top apparently benign entry points.

Palo Alto Unit 42 · Aug 17, 2026Research

Autoencoder Is All You Need: Profiling and Detecting Malicious DNS Traffic

Palo Alto Unit 42 details an autoencoder-based method that profiles DNS traffic to detect C2 and malicious domains, blocking ~374,000 malicious DNS requests daily.

Unit 42 built an RNN-based autoencoder that compresses DNS traffic time series into fixed-dimensional 'DNS profiles' for each domain and device. Downstream classification, clustering, and anomaly detection modules flag suspicious domains, capturing 170 emerging suspicious domains in May 2024. Signatures block roughly 374,000 malicious DNS requests daily and run in the Advanced DNS Security service, with detections shared to Advanced URL Filtering. Case studies link DNS traffic patterns to C2 beaconing, dynamic DNS abuse, and DNS tunneling for data exfiltration.

Palo Alto Unit 42 · Aug 17, 2026Research

Automatically Detecting DNS Hijacking in Passive DNS

Unit 42's machine learning pipeline detected 6,729 DNS hijacking events between March and September 2024, hitting political parties, ISPs, and universities.

Unit 42 processes roughly 167 million new DNS records daily and applies a machine learning model using 74 features over 169 TB of passive DNS and geolocation data to flag hijacked domains. From March to September 2024 the pipeline screened over 29 billion records and classified 6,729 as DNS hijacking, averaging 38 detections per day; a new model detects hijacks in customer traffic within about 10 minutes. Notable cases include a Hungarian political party's hijacked domain, defacement of a large utility company and ISP, and university and research center domains repurposed for illicit gambling. DNS hijacking typically relies on stolen registrar or DNS provider credentials or cache poisoning, enabling MitM attacks, phishing, drive-by downloads, and scams.

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

Turn it off and on again, but for critical infrastructure

KTH researchers trained a reinforcement-learning intrusion response agent on an emulated segmented OT network that autonomously resets hosts and processes to disrupt intruders.

Researchers at KTH Royal Institute of Technology built a containerized replica of a segmented industrial network, attacked it across 14 days, and captured 40,000 30-second traffic intervals to train a defense agent under partial observability. The agent observes six packet-count numbers per interval, maintains 500 running state hypotheses, and can reset supervisory hosts, water tank processes, or entire subnets, with resets rebooting the target, renewing credentials, and changing its IP. The best agent approached a full-visibility baseline but depends on an assumed attacker behavior model; the testbed comprised three supervisory hosts, two PLCs, two tanks, weak credentials, and CVE-2017-7494 exposure. The team released its implementation and plans validation on a real industrial testbed with a partner.

Help Net Security · 2d agoResearchCVE-2017-74942· 1 read

Trends in Web Threats: Old Web Skimmer Still Active Today

Unit 42 detected 577,000 landing URL incidents in Q1 2022, with an old web skimmer family still actively stealing payment card data.

Palo Alto Unit 42 detected 577,275 landing URL incidents (116,643 unique) and 2,043,862 malicious host URL incidents (180,370 unique) between January and March 2022. Web threat volumes declined after the November 2021 holiday peak, but an old web skimmer family remained active. Business and economy sites overtook personal sites as the most common apparently benign entry points. Most malicious domains geolocated to the United States, Germany, and Russia, though proxy servers and VPNs obscure true locations.

Palo Alto Unit 42 · Aug 17, 2026Research

Beneath the Surface: Detecting and Blocking Hidden Malicious Traffic Distribution Systems

Unit 42 built an ML-based detector for malicious traffic distribution systems, finding malicious TDS chains average longer redirections and more URLs than legitimate ones.

Traffic distribution systems redirect victims through chains of intermediate domains to hide final destinations, serving phishing, malvertising, and online gambling operations. Unit 42's topological analysis of redirection graphs found malicious TDS traffic uses longer chains (about 25% exceed four hops vs 10% benign), more URLs (median 126 vs 80), and fewer isolated subgraphs with higher connectivity. These features power an ML detector integrated into Advanced DNS Security and Advanced URL Filtering to identify and block malicious TDS infrastructure in customer traffic.

Palo Alto Unit 42 · Aug 17, 2026Research

Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection

Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.

Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.

Palo Alto Unit 42 · 2d agoResearch

Hunting Vulnerabilities Using Frontier Models

Okta used frontier AI models GPT-5.5 Cyber and Mythos via OpenAI and Anthropic programs to scan millions of code lines for vulnerabilities.

Okta describes using frontier AI models, including GPT-5.5 Cyber Preview (TAC) and Mythos Preview, through OpenAI's Daybreak Cyber Partner Program and Anthropic's Project Glasswing to hunt vulnerabilities across its product codebase. The team built a custom Python orchestrator with strong isolation, vendor-agnostic model support, and four distinct scanning pipelines executed as isolated Codex or Claude Code sessions with progressive context loading to reduce context bloat. Human experts and AI agents worked both autonomously and in paired hunts, and Okta reports the best results when humans and agents taught each other.

Okta Security · 8d agoResearch

TLD Tracker: Exploring Newly Released Top

Unit 42 tracked 19 newly released top-level domains and found large-scale phishing, unwanted program distribution, and cybersquatting tied to TLD launch dates.

Researchers analyzed 19 new generic TLDs, including .zip, .bot, .ing, and .meme, released or approaching general availability over roughly 18 months. Data from passive DNS, registry zone files, newly registered domain feeds, and the Tranco top-1M list showed phishing campaigns, potentially unwanted program distribution, and domain squatting on these TLDs. Abuse correlated with each TLD's rollout phases, indicating attackers monitor general availability dates to register and weaponize domains. The IANA root database now lists over 1,000 generic TLDs.

Palo Alto Unit 42 · Aug 17, 2026Research

The modern attack chain: Rethinking Google Workspace security in the age of AI

Analysis of Vercel and Composio breaches shows stolen OAuth tokens, not phishing email, now open Google Workspace attacks — a path authorized AI agents follow.

The author analyzes the Vercel and Composio breaches as the same OAuth-first attack chain run twice: a stolen OAuth token, obtained via a compromised supplier, becomes the entry point rather than email. These tokens survive password resets, are hard to observe, and let attackers read Gmail and Drive data, take over accounts, and pivot laterally using stored credentials and password-reset magic links. The piece warns that authorized AI agents with overbroad OAuth grants can unintentionally traverse the same path — accessing inboxes, reading sensitive content, and exfiltrating data downstream — without any malicious actor or compromised credential.

Help Net Security · 15h agoResearch in the wild

1Password's AI patching benchmark is misleading

Trail of Bits reanalysis says 1Password's 26% AI clean-fix rate is misleading; 86% of eligible patches blocked exploits.

Trail of Bits critiques 1Password's FLAWED AI patching benchmark, arguing its 26% clean-fix headline mixes trials where agents were instructed to apply wrong fixes (22% of data) with trials that prohibited compiling or testing (36%). Restricting to reasonable conditions, 2,634 of 3,067 patches (86%) blocked the supplied exploit. Trail of Bits also reports 12.5% of 2,265 developer first fixes failed in its own 2024-2026 assessments, and released post-patch-validation and review-walkthrough agent skills.

Lobsters · security · 1d agoResearch

OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design

OptiPrime co-designs HE-MPC protocols with hardware acceleration to remove network communication bottlenecks in private DNN inference, beating Cheetah by up to 5.7x.

OptiPrime is a protocol-hardware co-optimization framework for private deep neural network inference based on hybrid homomorphic encryption (HE) and multi-party computation (MPC). It introduces a novel HE protocol for convolutions that reduces the number of transmitted output ciphertexts, addressing the network bottleneck that limits gains from commercial HE accelerators. A lightweight compression system reduces weight plaintext memory traffic by 10x, while a specialized dataflow maximizes on-chip reuse of intermediate ciphertexts. Experiments show up to 5.7x speedup over the Cheetah baseline on CPUs and 4.2x with an accelerator.

arXiv cs.CR · 1d agoResearch

6 Months on Alert: Get H1 2026 Cyber Risk Report for SOCs and MSSPs

ANY.RUN's H1 2026 report details 15 threat trends including 437% growth in fake CAPTCHA phishing and 90.7% rise in Adobe infrastructure abuse.

The report draws on interactive sandbox submissions from over 700,000 analysts and 16,000 SOC teams between January and June 2026. Attacks abusing Adobe infrastructure grew 90.7% versus H2 2025 while RMM-related attacks rose 26.5%, and custom fake CAPTCHA phishing grew 437% from Q1 to Q2 2026. ANY.RUN argues static IOCs are losing effectiveness as dead drop resolvers hide the final C2 until execution.

ANY.RUN · 1d agoResearch