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Malicious Apache Modules Hijack Brazilian Government Site Traffic to Push Betting Pages
Check Point links Gambling Goblin, a Chinese-speaking cluster, to malicious Apache modules hijacking Brazilian government servers to promote betting sites.
Check Point Research tracks Gambling Goblin, a Chinese-speaking cluster, installing malicious Apache reverse-proxy modules on compromised Brazilian government and education web servers since mid-2025. The modules divert visitors to gambling and fake app-store pages while stripping the site's security headers, likely for large-scale SEO manipulation. The group's Linux arsenal includes DownPro, AlphaAgent, oRAT, a 3snake-based credential stealer, and SSH brute-forcing tools, and it is tied to Trend Micro's Earth Berberoka. Related SEO-fraud campaigns on .gov.br domains were documented by ESET (GhostRedirector), Palo Alto Networks Unit 42, and Hunt.io.
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Low-quality casino sites conceal highly dangerous threat actors
Infoblox reveals China-aligned APT groups hiding PeckBirdy malware C2 domains inside roughly 1.7 million Chinese-language illegal casino websites.
An Infoblox report says it tracks about 1.7 million Chinese-language casino sites enabling illegal gambling, some of which double as command-and-control infrastructure. China-aligned APT groups have hidden PeckBirdy framework C2 domains inside these low-quality casino sites since 2023, injecting scripts that display fake software update pages to deliver malware. Over 3 percent of Infoblox enterprise customers resolved at least one PeckBirdy C2 domain, and some sites rely on US cloud providers via 'infrastructure laundering.' Infoblox urges defenders not to dismiss casino-domain alerts as mere employee browsing violations.
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What must happen for AI’s trillion-dollar gamble to pay off
Hyperscalers need 2.7x productivity gains by 2030 to justify nearly $1.1 trillion in AI data center spending, or risk bankruptcy and capital misallocation.
Wharton finance professor Jessica Wachter estimates hyperscaler AI expenditure will reach nearly $1.1 trillion through 2027 and that a 2.7x productivity increase is needed to break even by 2030. AI revenues of roughly $150-200 billion this year fall far short of about $750 billion in annual spending, with total investment from Alphabet, Microsoft, Amazon, Meta, and Oracle potentially exceeding $5 trillion over four years. Alphabet reported its first free cash flow deficit (about $5.9 billion) since its 2004 IPO due to AI infrastructure costs. Researchers warn that failed demand could make the buildout the largest capital misallocation in history, with depreciating GPU chips risking stranded assets.
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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.
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The Fraud Ecosystem: A Transition From Known Marketplaces to a Fragmented Environment
Rapid7 analyzes how fraud marketplaces are fragmenting into specialized shops after larger marketplaces were dismantled, aided by new MITRE F3 framework
Rapid7 reports a shift from large known fraud marketplaces to a fragmented environment of smaller specialized storefronts such as Xleet, Blackpass, Infodig, and Styx, operating across dark web channels, Telegram, and P2P options. These Fraud-as-a-Service shops sell stolen accounts, PII, synthetic identity generation, infrastructure, and money laundering support, supporting schemes like business email compromise. MITRE's Fraud Fighting Framework (F3), introduced in early 2026, aims to help security teams prioritize monitoring of fraud TTPs, particularly account takeover techniques. Fraud damages are anticipated to approach hundreds of billions of USD.
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13 Malicious Packagist Packages Target Unpatched iPhones to Steal Crypto Wallet Seeds
Trojanized Packagist themes inject JavaScript into Vietnamese streaming sites, exploiting unpatched iPhone WebKit and kernel flaws to install spyware and steal crypto wallet seeds.
Socket researchers found 13 malicious Composer theme packages across five vendor namespaces (including vsmov, vsphim, and ophimcms) that inject JavaScript into Vietnamese movie and comic streaming sites. On iPhones running iOS 18.4-18.6.x, the injected code fires a WebKit-to-kernel exploit chain using CVE-2025-31277 and CVE-2025-43529, pivoting through the GPU process and the AppleM2ScalerCSCDriver IOKit user client to gain kernel read/write. Since around August 12, 2026 the payload also steals cryptocurrency wallet seeds and mnemonics from Bitget, BitKeep, Bitpie, Phantom, Tonkeeper, Trust Wallet, and OKX, alongside keychain databases, Wi-Fi passwords, SMS, photos, cookies, and location history, uploaded via HTTPS to rotating C2 domains. The group is believed to be Vietnamese-operated, hosts exploits on Funnull infrastructure, and Apple patched the kernel escape flaw in iOS and macOS 26.1.
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LLM-Based Social Engineering Scams
OpenAI disrupted a Cambodia-based ChatGPT-powered scam network running romance, crypto-investment, gambling, and fake law-enforcement fraud campaigns.
OpenAI disrupted a social engineering network operating from Cambodia that used ChatGPT to run multiple scam types simultaneously. Operators built trust with fake dating personas before pitching fraudulent cryptocurrency and spot gold investments, posed as gambling platforms offering fake bonuses, or impersonated law enforcement agencies demanding fine payments. The network also generated images of forged documents including passports, legal notices, stock-purchase confirmations, and gambling platform interfaces.
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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.
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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.
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