AI | Breaking Cybersecurity News | The Hacker News

A quiet tweak in a popular open-source tool opened the door to a supply chain breach—what started as a targeted attack quickly spiraled, exposing secrets across countless projects. That wasn't the only stealth move. A new all-in-one malware is silently stealing passwords, crypto, and control—while hiding in plain sight. And over 300 Android apps joined the chaos, running ad fraud at scale behind innocent-looking icons. Meanwhile, ransomware gangs are getting smarter—using stolen drivers to shut down defenses—and threat groups are quietly shifting from activism to profit. Even browser extensions are changing hands, turning trusted tools into silent threats. AI is adding fuel to the fire—used by both attackers and defenders—while critical bugs, cloud loopholes, and privacy shakeups are keeping teams on edge. Let's dive into the threats making noise behind the scenes. ⚡ Threat of the Week Coinbase the Initial Target of GitHub Action Supply Chain Breach — The supply chain compromise...

We've been hearing the same story for years: AI is coming for your job. In fact, in 2017, McKinsey printed a report, Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation , predicting that by 2030, 375 million workers would need to find new jobs or risk being displaced by AI and automation. Queue the anxiety.  There have been ongoing whispers about what roles would be impacted, and pentesting has recently come into question. With AI now able to automate tasks such as vulnerability scans and network scans—among other things—and with platforms like PlexTrac adding AI capabilities to cut back on the manual effort, will pentesters be out of a job? Let's start with some optimism. This year, McKinsey retracted its former prediction that 375 million workers would be displaced by AI, lowering the prediction to roughly 92 million workers. The article continued to ease concern stating that although some jobs may become obsolete, it's more likely that jobs will simply unde...

Google has stepped in to clarify that a newly introduced Android System SafetyCore app does not perform any client-side scanning of content. "Android provides many on-device protections that safeguard users against threats like malware, messaging spam and abuse protections, and phone scam protections, while preserving user privacy and keeping users in control of their data," a spokesperson for the company told The Hacker News when reached for comment. "SafetyCore is a new Google system service for Android 9+ devices that provides the on-device infrastructure for securely and privately performing classification to help users detect unwanted content. Users are in control over SafetyCore and SafetyCore only classifies specific content when an app requests it through an optionally enabled feature." SafetyCore (package name "com.google.android.safetycore") was first introduced by Google in October 2024, as part of a set of security measures designed to...

DeepSeek, the Chinese AI startup that has captured much of the artificial intelligence (AI) buzz in recent days, said it's restricting registrations on the service, citing malicious attacks. "Due to large-scale malicious attacks on DeepSeek's services, we are temporarily limiting registrations to ensure continued service," the company said in an incident report page. "Existing users can log in as usual. Thanks for your understanding and support." Users attempting to sign up for an account are being displayed a similar message, stating "registration may be busy" and that they should wait and try again. "With the popularity of DeepSeek growing, it's not a big surprise that they are being targeted by malicious web traffic," Erich Kron, security awareness advocate at KnowBe4, said in a statement shared with The Hacker News. "These sorts of attacks could be a way to extort an organization by promising to stop attacks and rest...

Cybersecurity researchers have found that it's possible to use large language models (LLMs) to generate new variants of malicious JavaScript code at scale in a manner that can better evade detection. "Although LLMs struggle to create malware from scratch, criminals can easily use them to rewrite or obfuscate existing malware, making it harder to detect," Palo Alto Networks Unit 42 researchers said in a new analysis. "Criminals can prompt LLMs to perform transformations that are much more natural-looking, which makes detecting this malware more challenging." With enough transformations over time, the approach could have the advantage of degrading the performance of malware classification systems, tricking them into believing that a piece of nefarious code is actually benign. While LLM providers have increasingly enforced security guardrails to prevent them from going off the rails and producing unintended output, bad actors have advertised tools like WormGPT...

The 2025 cybersecurity landscape is increasingly complex, driven by sophisticated cyber threats, increased regulation, and rapidly evolving technology. In 2025, organizations will be challenged with protecting sensitive information for their customers while continuing to provide seamless and easy user experiences. Here's a closer look at ten emerging challenges and threats set to shape the coming year. 1. AI as a weapon for attackers The dual-use nature of AI has created a great deal of risk to organizations as cybercriminals increasingly harness the power of AI to perpetrate highly sophisticated attacks. AI-powered malware can change its behavior in real-time. This means it can evade traditional methods of detection and find and exploit vulnerabilities with uncanny precision. Automated reconnaissance tools let attackers compile granular intelligence about systems, employees, and defenses of a target at unprecedented scale and speed. AI use also reduces the planning time for a...

Run by the team at orchestration, AI, and automation platform Tines, the Tines library contains pre-built workflows shared by real security practitioners from across the community, all of which are free to import and deploy via the Community Edition of the platform.  Their bi-annual "You Did What with Tines?!" competition highlights some of the most interesting workflows submitted by their users, many of which demonstrate practical applications of large language models (LLMs) to address complex challenges in security operations. One recent winner is a workflow designed to automate CrowdStrike RFM reporting. Developed by Tom Power, a security analyst at The University of British Columbia, it uses orchestration, AI and automation to reduce the time spent on manual reporting. Here, we'll share an overview of the workflow, plus a step-by-step guide for getting it up and running. The problem - time-consuming reporting The workflow's builder, Tom Power, explains, "The CrowdStrike ...

The lines between digital and physical realms increasingly blur. While this opens countless opportunities for businesses, it also brings numerous challenges. In our recent webinar, Shaping the Cyber-Physical Future: Trends, Challenges, and Opportunities for 2025 , we explored the different factors shaping the cyber-physical future. In an insightful conversation with industry experts, we discussed the most pressing security concerns of today and how to address them. Allison J. Taylor, the founder and CEO of Thought Marketing LLC, unveiled trends and recommended strategies businesses can employ to proactively bolster their security amidst evolving cyber challenges. Cesar Salazar, COO of Claro Enterprise Solutions, delved into innovative solutions that could propel business tech forward. He emphasized cyber-physical convergence, the use of emerging technologies, and responsive security operations. Below are the key takeaways from the webinar. These provide an overview of why businesses...

In recent years, artificial intelligence (AI) has begun revolutionizing Identity Access Management (IAM), reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that could signal a potential security breach. The focus has expanded beyond merely managing human identities — now, autonomous systems, APIs, and connected devices also fall within the realm of AI-driven IAM, creating a dynamic security ecosystem that adapts and evolves in response to sophisticated cyber threats. The Role of AI and Machine Learning in IAM AI and machine learning (ML) are creating a more robust, proactive IAM system that continuously learns from the environment to enhance security. Let's explore how AI impacts key IAM components: Intelligent Monitoring and Anomaly Detection AI enables continuous monitoring of both human and non-human identities , including APIs, service acc...