macOS Users Encounter Phishing and Scams More Often Than Windows Users but Adopt Fewer Protections, Kaspersky Study Reveals
A recent study conducted by Kaspersky Lab highlights a concerning trend among macOS users, who report encountering cyber threats more frequently than Windows users while simultaneously adopting fewer protective measures.
According to the findings, 12 percent of surveyed macOS users experienced phishing attacks in the past year, compared to only 9 percent of Windows users. Complaints about fraudulent investment schemes reached 16 percent among Mac owners versus 13 percent for Windows users.
Privacy-related incidents were also more common on macOS, with 11 percent reporting violations of confidentiality against 8 percent on Windows, and 12 percent noting theft of personal data compared to 7 percent.
Behavioral differences further illustrate the gap. Only 51 percent of macOS users refrain from opening suspicious emails and links, while 62 percent of Windows users do so. Additional security solutions are installed by 35 percent of Mac users versus 42 percent of Windows users.
Password hygiene shows similar disparities: 35 percent of macOS users create unique credentials for each account compared to 38 percent on Windows. Complex passwords are chosen by 45 percent versus 52 percent, and multi-factor authentication is enabled by 46 percent against 51 percent.
Kaspersky Lab emphasizes that built-in macOS protections provide solid defense against many threats but fall short against social engineering, supply-chain attacks, and malware specifically designed for Apple platforms. The perception of macOS as inherently secure has apparently led to complacency among users.
Related articles
Behavioral Anti-Fraud: How Systems Analyze User Actions Beyond Device and Browser Fingerprints
Anti-fraud systems are shifting from static device and browser fingerprinting toward continuous behavioral analysis powered by machine learning. The article explains why matching User-Agent strings with Canvas or font rendering is no longer sufficient, as bot developers can easily synchronize these static signals. Modern defenses now record dozens of micro-events during a session, including keystroke timing, mouse trajectories, scroll speed, and focus changes, to build a dynamic Trust Score. These models are trained on large clusters of real-user behavior and flag sessions whose patterns fall outside legitimate clusters even when fingerprints appear realistic. The text details dwell time, flight time, error-correction patterns, natural hand tremor, and acceleration curves governed by Fitts’s law as key biometric markers. It also covers browser-level signals such as Event.isTrusted, CDP artifacts, and navigator.webdriver flags that reveal automation frameworks. The discussion extends to mobile sensors and concludes that perfectly error-free, mathematically smooth input is itself a strong indicator of synthetic activity.
Free Online Panel Examines Rising Omnichannel Scams and Multichannel Fraud Tactics
The Brazilian human risk management firm Eskive is hosting its third free online panel on August 18 at 11 a.m. to address the growing threat of omnichannel cyber fraud. Experts will discuss how attackers combine multiple channels such as email, SMS, and other vectors to create more convincing social-engineering narratives that bypass traditional single-channel defenses. The event will feature CEO Priscila Meyer as moderator along with cyber threat intelligence specialist Thiago Bordini and Santa Catarina Civil Police investigator Elias Edenis. Participants will gain practical insights from real client simulations, live Q&A sessions, and interactive quizzes designed to improve organizational preparedness. The panel aims to highlight why users accustomed to recognizing basic phishing or smishing attempts remain vulnerable when fraudsters deploy coordinated, multi-channel campaigns.
OpenAI Disables Coordinated ChatGPT Network Used for Financial Scams and Identity Forgery
OpenAI has deactivated a coordinated network of ChatGPT accounts that supported financial fraud, romance scams, and identity forgery operations. Criminals leveraged the AI to generate fake personas, translate conversations, and craft targeted messages aimed at victims across multiple schemes. The investigation originated from reports of suspicious activity observed on WhatsApp. Scammers used the tool to produce forged documents including stock confirmations, legal notices, passports, and fake financial interfaces to increase credibility. Operations typically began on social media or messaging apps, building emotional trust or urgency before requesting deposits, activation fees, or nonexistent fines. Indicators of possible human trafficking and forced labor were also uncovered through job advertisements and internal discussions about worker control in Poipet. OpenAI has blocked the accounts and shared operational indicators with law enforcement and technology companies.
Positive Technologies Uncovers Disinformation Factory Linking 45 Domains and 74 Telegram Channels
Researchers at Positive Technologies have exposed an integrated disinformation operation that combined fake government emails with a network of pseudo-news websites and synchronized social media channels. The campaign began with emails sent from lookalike domains such as minpromtorg.digital and gosuslugi.digital, requesting employee lists and salary data to prepare targeted phishing attacks. Parallel to the email activity, operators maintained at least 45 domains including rulenta.live and crime24.live that mixed genuine stories with fabricated content and cited nonexistent sources. These sites were amplified through dozens of Telegram channels and accounts on VKontakte, Odnoklassniki, YouTube, Instagram, and TikTok, creating a self-reinforcing loop where fabricated claims were quoted back as credible reporting. Investigators noted a possible infrastructure overlap with the cybercriminal group Rare Werewolf, although direct attribution remains unconfirmed. The operation demonstrates a complete information pipeline from initial reconnaissance via email to wide distribution of disinformation across multiple platforms.