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614% Rise In ‘Scam-Yourself Attacks’

• Written by Kiara Fabbri Former Tech News Writer
• Fact-Checked by Sarah Frazier Former Content Manager

Gen’s Q3/2024 report reveals a rise in “Scam-Yourself Attacks,” with increases in data theft, ransomware, and mobile spyware.

In a Rush? Here are the Quick Facts!

• Data-theft malware increased by 39%, with Lumma Stealer rising by 1154%.
• Ransomware threats grew by 100%, with Magniber exploiting outdated Windows 7 software.
• Mobile spyware, including NGate, surged 166%, cloning bank card NFC data.

Gen Digital Inc., a global leader in consumer cybersecurity, released its Q3/2024 Threat Report on November 19, revealing a sharp rise in cybercriminal activities, including a staggering 614% increase in “Scam-Yourself Attacks.”

The report, based on data from millions of users worldwide, underscores how cybercriminals are rapidly adapting their tactics, using social engineering, AI, and deepfake technologies to make scams harder to spot.

Siggi Stefnisson, Cyber Safety CTO at Gen, said, “In July through September, scams continued to dominate the threat landscape, while data-theft abusing malware and ransomware also increased rapidly.”

Stefnisson continued, “Our consistent focus is to empower people with the tools they need, such as the Norton Genie scam detector, so they can protect their digital lives as threats evolve.”

“Scam-Yourself Attacks” are social engineering scams where cybercriminals trick individuals into installing malware on their own devices.

These attacks exploit people’s desire to learn new technologies or solve problems, like downloading software through fake tutorials or using ClickFix scams , where users are prompted to enter a command that gives cybercriminals control of their systems.

The report outlines several types of Scam-Yourself Attacks, including fake software updates, fake CAPTCHA prompts, and deceptive tutorials, all of which are designed to manipulate victims into allowing malware onto their devices.

Alongside the rise of scams, data-theft malware saw a significant increase in Q3/2024, with overall activity rising by 39%.

The Lumma Stealer malware, which targets sensitive information such as login credentials, cryptocurrency wallets, and browser data, increased its activity by a staggering 1154%.

Ransomware threats also escalated, with a 100% rise in risk ratio. The Magniber ransomware emerged as a leading threat, often exploiting outdated software like Windows 7 to gain access to systems.

Gen researchers continue to collaborate with governments worldwide to combat ransomware, offering free decryption tools for victims, including the recently released Avast Mallox Ransomware Decryptor.

On mobile devices, data-stealing malware also surged. Spyware increased by 166%, and a new strain, NGate, emerged, cloning bank card NFC data to make unauthorized withdrawals or payments.

Banking malware targeting credentials increased by 60%, with new strains like TrickMo and Octo2. These threats are often delivered through malicious SMS messages, reinforcing the need for strong mobile security.

Norton Genie, Gen’s AI-driven scam detector, adapts in real-time to detect AI-enhanced deception tactics.

Norton Genie’s 2024 telemetry data shows that after generic scams, smishing attempts—SMS messages impersonating banks, delivery services, or government agencies—are the most common (16.5%).

The report also showed that lottery scams and general phishing emails follow closely, emphasizing the growing complexity of digital threats.

image by Doug Belshaw, from Flickr

AI Revolution Puts Google Scholar’s Legacy To The Test

• Written by Kiara Fabbri Former Tech News Writer
• Fact-Checked by Sarah Frazier Former Content Manager

Google Scholar turns 20, but AI-powered competitors with advanced summarization, contextual searches, and open-access features increasingly challenge its dominance.

In a Rush? Here are the Quick Facts!

• Google Scholar celebrates 20 years as a leading scholarly search engine.
• AI-driven platforms challenge Google Scholar’s dominance with context-aware search algorithms.
• Google Scholar integrates AI but lacks AI-generated summaries for multi-paper queries.

As Google Scholar marks its 20th anniversary, it remains a cornerstone for millions of researchers globally. However, as noted in the scientific journal Nature , emerging AI-driven tools are reshaping how scientific literature is accessed, analyzed, and utilized .

Since its debut in 2004, the platform’s ranking system, which emphasizes relevance and citation counts, along with features that guide users to free versions of articles, has cemented its dominance in the academic community, notes Nature.

However, the rise of AI tools is challenging this supremacy. Platforms like Semantic Scholar and Consensus leverage large language models to summarize papers, highlight key citations, and even answer research-driven questions.

Semantic Scholar, for example, uses AI to extract readable summaries and identify critical references. Similarly, Consensus applies advanced search algorithms to refine results based on specific research questions.

These innovations cater to a growing demand for tools that not only locate information but also contextualize and synthesize it.

Aaron Tay, an academic librarian at Singapore Management University, highlights the shifting preference for AI-powered platforms, as reported by Nature.

While Google Scholar remains his primary tool, he acknowledges the growing appeal of alternatives like Undermind, which deploys agent-based searches that adapt dynamically to the content they process. These tools often deliver more refined results, albeit with a longer processing time.

In response, Nature reports that Google Scholar has integrated AI into its own offerings. Recent updates include AI-generated article outlines within its PDF reader and semantic search capabilities that interpret the intent and context behind queries.

Despite these advancements, the platform stops short of providing AI-generated overviews for complex searches, a feature now standard in Google’s general search engine, says Nature.

The entry of open-access databases like OpenAlex also underscores the push for transparency and accessibility in scholarly searches. Unlike Google Scholar, OpenAlex allows bulk data downloads, a crucial feature for bibliometric analyses, says Nature.

It must be noted that critics argue that while AI can summarize scientific literature, it falls short in conducting thorough, gold-standard reviews.

AI’s limitations spark concerns about accuracy and transparency, as large language models (LLMs) sometimes produce content lacking context or misrepresenting data. They often draw from unreliable sources without adequately evaluating information quality.

While Google Scholar’s entrenchment and scale make it difficult to dethrone, AI-driven competitors are reshaping expectations. As scholars navigate these evolving tools, the future of research may hinge on how well platforms balance scale, accuracy, and adaptability in the AI era.