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Taiwan has become the latest country to ban government agencies from using Chinese startup DeepSeek's Artificial Intelligence (AI) platform, citing security risks. "Government agencies and critical infrastructure should not use DeepSeek, because it endangers national information security," according to a statement released by Taiwan's Ministry of Digital Affairs, per Radio Free Asia . "DeepSeek AI service is a Chinese product. Its operation involves cross-border transmission, and information leakage and other information security concerns." DeepSeek's Chinese origins have prompted authorities from various countries to look into the service's use of personal data. Last week, it was blocked in Italy, citing a lack of information regarding its data handling practices. Several companies have also prohibited access to the chatbot over similar risks. The chatbot has captured much of the mainstream attention over the past few weeks for the fact tha...

Italy's data protection watchdog has blocked Chinese artificial intelligence (AI) firm DeepSeek's service within the country, citing a lack of information on its use of users' personal data. The development comes days after the authority, the Garante, sent a series of questions to DeepSeek, asking about its data handling practices and where it obtained its training data. In particular, it wanted to know what personal data is collected by its web platform and mobile app, from which sources, for what purposes, on what legal basis, and whether it is stored in China. In a statement issued January 30, 2025, the Garante said it arrived at the decision after DeepSeek provided information that it said was "completely insufficient." The entities behind the service, Hangzhou DeepSeek Artificial Intelligence and Beijing DeepSeek Artificial Intelligence, have "declared that they do not operate in Italy and that European legislation does not apply to them," it...

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...

This week, our news radar shows that every new tech idea comes with its own challenges. A hot AI tool is under close watch, law enforcement is shutting down online spots that help cybercriminals, and teams are busy fixing software bugs that could let attackers in. From better locks on our devices to stopping sneaky tricks online, simple steps are making a big difference.  Let's take a closer look at how these efforts are shaping a safer digital world. ⚡ Threat of the Week DeepSeek's Popularity Invites Scrutiny — The overnight popularity of DeepSeek, an artificial intelligence (AI) platform originating from China, has led to extensive scrutiny of its models, with several analyses finding ways to jailbreak its system and produce malicious or prohibited content. While jailbreaks and prompt injections are a persistent concern in mainstream AI products, the findings also show that the model lacks enough protections to prevent potential abuse by malicious actors . The AI chatbot ha...

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...

Lovable , a generative artificial intelligence (AI) powered platform that allows for creating full-stack web applications using text-based prompts, has been found to be the most susceptible to jailbreak attacks, allowing novice and aspiring cybercrooks to set up lookalike credential harvesting pages. "As a purpose-built tool for creating and deploying web apps, its capabilities line up perfectly with every scammer's wishlist," Guardio Labs' Nati Tal said in a report shared with The Hacker News. "From pixel-perfect scam pages to live hosting, evasion techniques, and even admin dashboards to track stolen data – Lovable didn't just participate, it performed. No guardrails, no hesitation." The technique has been codenamed VibeScamming – a play on the term vibe coding, which refers to an AI-dependent programming technique to produce software by describing the problem statement in a few sentences as a prompt to a large language model (LLM) tuned for codin...

Cybersecurity researchers have discovered a novel attack technique called TokenBreak that can be used to bypass a large language model's (LLM) safety and content moderation guardrails with just a single character change. "The TokenBreak attack targets a text classification model's tokenization strategy to induce false negatives, leaving end targets vulnerable to attacks that the implemented protection model was put in place to prevent," Kieran Evans, Kasimir Schulz, and Kenneth Yeung said in a report shared with The Hacker News. Tokenization is a fundamental step that LLMs use to break down raw text into their atomic units – i.e., tokens – which are common sequences of characters found in a set of text. To that end, the text input is converted into their numerical representation and fed to the model.  LLMs work by understanding the statistical relationships between these tokens, and produce the next token in a sequence of tokens. The output tokens are detokeni...