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CategoryAllMalware 911Ransomware 381Threat actor 367Vulnerability 355Phishing & fraud 318Exploit / PoC 189Data breach 150Industry 127Policy & legal 109AI safety & security 33AI research 19Advisory 19AI tools & infra 17Research 17
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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

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.

The Hacker News · 4d agoResearch2

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

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

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

Huntress · 9d agoResearch1

Nebulon Enterprise Simulated Threats for Phishing Research (NEST-Phish): A Synthetic Enterprise Phishing Email Dataset for Behavioral and Machine-Learning Research

Researchers release NEST-Phish, a synthetic enterprise phishing email dataset with matched legitimate and phishing emails and cue annotations for detection research.

Academic researchers introduce NEST-Phish, a publicly released synthetic enterprise phishing email dataset built around a fictitious organization named Nebulon. It contains matched synthetic legitimate and phishing emails across a broad set of workplace communication themes, each with interpretable phishing-cue annotations. Human-subject categorizations and supervised classifier evaluations indicate the dataset supports meaningful variation in phishing judgments and provides learnable signal for detection models. It is intended to support work on phishing detection, human susceptibility, explainability, and benchmark development.

arXiv cs.CR · 13d agoResearch