machine learning | Breaking Cybersecurity News | The Hacker News

Generative AI is changing how businesses work, learn, and innovate. But beneath the surface, something dangerous is happening. AI agents and custom GenAI workflows are creating new, hidden ways for sensitive enterprise data to leak —and most teams don't even realize it. If you're building, deploying, or managing AI systems, now is the time to ask: Are your AI agents exposing confidential data without your knowledge? Most GenAI models don't intentionally leak data. But here's the problem: these agents are often plugged into corporate systems—pulling from SharePoint, Google Drive, S3 buckets, and internal tools to give smart answers. And that's where the risks begin. Without tight access controls, governance policies, and oversight, a well-meaning AI can accidentally expose sensitive information to the wrong users—or worse, to the internet. Imagine a chatbot revealing internal salary data. Or an assistant surfacing unreleased product designs during a casual query. This isn't hypot...

If you're evaluating AI-powered SOC platforms, you've likely seen bold claims: faster triage, smarter remediation, and less noise. But under the hood, not all AI is created equal. Many solutions rely on pre-trained AI models that are hardwired for a handful of specific use cases. While that might work for yesterday's SOC, today's reality is different. Modern security operations teams face a sprawling and ever-changing landscape of alerts. From cloud to endpoint, identity to OT, insider threats to phishing, network to DLP, and so many more, the list goes on and is continuously growing. CISOs and SOC managers are rightly skeptical. Can this AI actually handle all of my alerts, or is it just another rules engine in disguise? In this post, we'll examine the divide between two types of AI SOC platforms. Those built on adaptive AI, which learns to triage and respond to any alert type, and those that rely on pre-trained AI, limited to handling predefined use cases only. Understanding t...

With nearly 80% of cyber threats now mimicking legitimate user behavior, how are top SOCs determining what's legitimate traffic and what is potentially dangerous? Where do you turn when firewalls and endpoint detection and response (EDR) fall short at detecting the most important threats to your organization? Breaches at edge devices and VPN gateways have risen from 3% to 22%, according to Verizon's latest Data Breach Investigations report. EDR solutions are struggling to catch zero-day exploits, living-off-the-land techniques, and malware-free attacks. Nearly 80% of detected threats use malware-free techniques that mimic normal user behavior, as highlighted in CrowdStrike's 2025 Global Threat Report. The stark reality is that conventional detection methods are no longer sufficient as threat actors adapt their strategies, using clever techniques like credential theft or DLL hijacking to avoid discovery.  In response, security operations centers (SOCs) are turning to a multi-lay...

SaaS Adoption is Skyrocketing, Resilience Hasn't Kept Pace SaaS platforms have revolutionized how businesses operate. They simplify collaboration, accelerate deployment, and reduce the overhead of managing infrastructure. But with their rise comes a subtle, dangerous assumption: that the convenience of SaaS extends to resilience. It doesn't. These platforms weren't built with full-scale data protection in mind . Most follow a shared responsibility model — wherein the provider ensures uptime and application security, but the data inside is your responsibility. In a world of hybrid architectures, global teams, and relentless cyber threats, that responsibility is harder than ever to manage. Modern organizations are being stretched across: Hybrid and multi-cloud environments with decentralized data sprawl Complex integration layers between IaaS, SaaS, and legacy systems Expanding regulatory pressure with steeper penalties for noncompliance Escalating ransomware threats and inside...

Facebook, the social network platform owned by Meta, is asking for users to upload pictures from their phones to suggest collages, recaps, and other ideas using artificial intelligence (AI), including those that have not been directly uploaded to the service. According to TechCrunch, which first reported the feature, users are being served a new pop-up message asking for permission to "allow cloud processing" when they are attempting to create a new Story on Facebook. "To create ideas for you, we'll select media from your camera roll and upload it to our cloud on an ongoing basis, based on info like time, location or themes," the company notes in the pop-up. "Only you can see suggestions. Your media won't be used for ads targeting. We'll check it for safety and integrity purposes." Should users consent to their photos being processed on the cloud, Meta also states that they are agreeing to its AI terms , which allow it to analyze their med...

Popular messaging platform WhatsApp has added a new artificial intelligence (AI)-powered feature that leverages its in-house solution Meta AI to summarize unread messages in chats. The feature, called Message Summaries, is currently rolling out in the English language to users in the United States, with plans to bring it to other regions and languages later this year. It "uses Meta AI to privately and quickly summarize unread messages in a chat, so you can get an idea of what is happening, before reading the details in your unread messages," WhatsApp said in a post. Message Summaries is optional and is disabled by default. The Meta-owned service said users can also enable " Advanced Chat Privacy " to choose which chats can be shared for providing AI-related features. Most importantly, it's made possible by Private Processing , which WhatsApp launched back in April as a way to enable AI capabilities in a privacy-preserving manner. Private Processing is de...

Google has revealed the various safety measures that are being incorporated into its generative artificial intelligence (AI) systems to mitigate emerging attack vectors like indirect prompt injections and improve the overall security posture for agentic AI systems. "Unlike direct prompt injections, where an attacker directly inputs malicious commands into a prompt, indirect prompt injections involve hidden malicious instructions within external data sources," Google's GenAI security team said . These external sources can take the form of email messages, documents, or even calendar invites that trick the AI systems into exfiltrating sensitive data or performing other malicious actions. The tech giant said it has implemented what it described as a "layered" defense strategy that is designed to increase the difficulty, expense, and complexity required to pull off an attack against its systems. These efforts span model hardening, introducing purpose-built mac...

DALL-E for coders? That's the promise behind vibe coding, a term describing the use of natural language to create software. While this ushers in a new era of AI-generated code, it introduces "silent killer" vulnerabilities: exploitable flaws that evade traditional security tools despite perfect test performance. A detailed analysis of secure vibe coding practices is available here . TL;DR: Secure Vibe Coding Vibe coding, using natural language to generate software with AI, is revolutionizing development in 2025. But while it accelerates prototyping and democratizes coding, it also introduces "silent killer" vulnerabilities: exploitable flaws that pass tests but evade traditional security tools. This article explores: Real-world examples of AI-generated code in production Shocking stats: 40% higher secret exposure in AI-assisted repos Why LLMs omit security unless explicitly prompted Secure prompting techniques and tool comparisons (GPT-4, Claude, Cursor, etc.) Reg...

When generative AI tools became widely available in late 2022, it wasn't just technologists who paid attention. Employees across all industries immediately recognized the potential of generative AI to boost productivity, streamline communication and accelerate work. Like so many waves of consumer-first IT innovation before it—file sharing, cloud storage and collaboration platforms—AI landed in the enterprise not through official channels, but through the hands of employees eager to work smarter. Faced with the risk of sensitive data being fed into public AI interfaces, many organizations responded with urgency and force: They blocked access. While understandable as an initial defensive measure, blocking public AI apps is not a long-term strategy—it's a stopgap. And in most cases, it's not even effective. Shadow AI: The Unseen Risk The Zscaler ThreatLabz team has been tracking AI and machine learning (ML) traffic across enterprises, and the numbers tell a compelling story. In 2024 ...

AI is changing cybersecurity faster than many defenders realize. Attackers are already using AI to automate reconnaissance, generate sophisticated phishing lures, and exploit vulnerabilities before security teams can react. Meanwhile, defenders are overwhelmed by massive amounts of data and alerts, struggling to process information quickly enough to identify real threats. AI offers a way to level the playing field, but only if security professionals learn to apply it effectively. Organizations are beginning to integrate AI into security workflows, from digital forensics to vulnerability assessments and endpoint detection. AI allows security teams to ingest and analyze more data than ever before, transforming traditional security tools into powerful intelligence engines. AI has already demonstrated its ability to accelerate investigations and uncover unknown attack paths, but many companies are hesitant to fully embrace it. Many AI models are implemented with such velocity that they r...

AI agents have rapidly evolved from experimental technology to essential business tools. The OWASP framework explicitly recognizes that Non-Human Identities play a key role in agentic AI security. Their analysis highlights how these autonomous software entities can make decisions, chain complex actions together, and operate continuously without human intervention. They're no longer just tools, but an integral and significant part of your organization's workforce. Consider this reality: Today's AI agents can analyze customer data, generate reports, manage system resources, and even deploy code, all without a human clicking a single button. This shift represents both tremendous opportunity and unprecedented risk. AI Agents are only as secure as their NHIs Here's what security leaders are not necessarily considering: AI agents don't operate in isolation . To function, they need access to data, systems, and resources. This highly privileged, often overlooked acces...

A dataset used to train large language models (LLMs) has been found to contain nearly 12,000 live secrets, which allow for successful authentication. The findings once again highlight how hard-coded credentials pose a severe security risk to users and organizations alike, not to mention compounding the problem when LLMs end up suggesting insecure coding practices to their users. Truffle Security said it downloaded a December 2024 archive from Common Crawl , which maintains a free, open repository of web crawl data. The massive dataset contains over 250 billion pages spanning 18 years.  The archive specifically contains 400TB of compressed web data, 90,000 WARC files (Web ARChive format), and data from 47.5 million hosts across 38.3 million registered domains. The company's analysis found that there are 219 different secret types in the Common Crawl archive, including Amazon Web Services (AWS) root keys, Slack webhooks, and Mailchimp API keys. "'Live' secrets ar...

Organizations today face relentless cyber attacks, with high-profile breaches hitting the headlines almost daily. Reflecting on a long journey in the security field, it's clear this isn't just a human problem—it's a math problem. There are simply too many threats and security tasks for any SOC to manually handle in a reasonable timeframe. Yet, there is a solution. Many refer to it as SOC 3.0—an AI-augmented environment that finally lets analysts do more with less and shifts security operations from a reactive posture to a proactive force. The transformative power of SOC 3.0 will be detailed later in this article, showcasing how artificial intelligence can dramatically reduce workload and risk, delivering world-class security operations that every CISO dreams of. However, to appreciate this leap forward, it's important to understand how the SOC evolved over time and why the steps leading up to 3.0 set the stage for a new era of security operations. A brief history of the SOC For deca...