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Outage
AI technology AI tools ChatGPT ChatGPT Vulnerabilities Cyber Security Downdetector Generative AI OpenAI Outage

ChatGPT Outage in the UK: OpenAI Faces Reliability Concerns Amid Growing AI Dependence

 


ChatGPT Outage: OpenAI Faces Service Disruption in the UK

On Thursday, OpenAI’s ChatGPT experienced a significant outage in the UK, leaving thousands of users unable to access the popular AI chatbot. The disruption, which began around 11:00 GMT, saw users encountering a “bad gateway error” message when attempting to use the platform. According to Downdetector, a website that tracks service interruptions, over 10,000 users reported issues during the outage, which persisted for several hours and caused widespread frustration.

OpenAI acknowledged the issue on its official status page, confirming that a fix was implemented by 15:09 GMT. The company assured users that it was monitoring the situation closely, but no official explanation for the cause of the outage has been provided so far. This lack of transparency has fueled speculation among users, with theories ranging from server overload to unexpected technical failures.

User Reactions: From Frustration to Humor

As the outage unfolded, affected users turned to social media to voice their concerns and frustrations. On X (formerly Twitter), one user humorously remarked, “ChatGPT is down again? During the workday? So you’re telling me I have to… THINK?!” While some users managed to find humor in the situation, others raised serious concerns about the reliability of AI services, particularly those who depend on ChatGPT for professional tasks such as content creation, coding assistance, and research.

ChatGPT has become an indispensable tool for millions since its launch in November 2022. OpenAI CEO Sam Altman recently revealed that by December 2024, the platform had reached over 300 million weekly users, highlighting its rapid adoption as one of the most widely used AI tools globally. However, the incident has raised questions about service reliability, especially among paying customers. OpenAI’s premium plans, which offer enhanced features, cost up to $200 per month, prompting some users to question whether they are getting adequate value for their investment.

The outage comes at a time of rapid advancements in AI technology. OpenAI and other leading tech firms have pledged significant investments into AI infrastructure, with a commitment of $500 billion toward AI development in the United States. While these investments aim to bolster the technology’s capabilities, incidents like this serve as a reminder of the growing dependence on AI tools and the potential risks associated with their widespread adoption.

The disruption highlights the importance of robust technical systems to ensure uninterrupted service, particularly for users who rely heavily on AI for their daily tasks. Despite restoring services relatively quickly, OpenAI’s ability to maintain user trust and satisfaction may hinge on its efforts to improve its communication strategy and technical resilience. Paying customers, in particular, expect transparency and proactive measures to prevent such incidents in the future.

As artificial intelligence becomes more deeply integrated into everyday life, service disruptions like the ChatGPT outage underline both the potential and limitations of the technology. Users are encouraged to stay informed through OpenAI’s official channels for updates on any future service interruptions or maintenance activities.

Moving forward, OpenAI may need to implement backup systems and alternative solutions to minimize the impact of outages on its user base. Clearer communication during disruptions and ongoing efforts to enhance technical infrastructure will be key to ensuring the platform’s reliability and maintaining its position as a leader in the AI industry.

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Technology
AI Promt AI tools Generative AI Technology

Common AI Promt Mistakes And How To Avoid Them

 

If you are running a business in 2025, you're probably already using generative AI in some capacity. GenAI tools and chatbots, such as ChatGPT and Google Gemini, have become indispensable in a variety of cases, ranging from content production to business planning. 

It's no surprise that more than 60% of businesses believe GenAI to be one of their top goals over the next two years. Furthermore, 87 percent of businesses are piloting or have already implemented generative AI tools in some way. 

But there is a catch. The quality of your inputs determines how well generative AI tools perform. Effective prompting can deliver you accurate AI outputs that meet your requirements, whereas ineffective prompting can take you down the wrong path. 

If you've been struggling to maximise the potential of AI technologies, it's time to rethink the cues you're employing. In this article, we'll look at the most common mistakes people make when asking AI tools questions, as well as how to avoid them. 

What are AI prompts? 

Prompts are queries or commands you give to generative AI tools such as ChatGPT or Claude. They are the inputs you utilise to communicate with AI models and instruct them on what to perform (or generate). AI models develop content based on the prompts you give them. 

The more contextual and specific the questions, the more accurate the AI responds. For example, if you're looking for strategies to increase client loyalty, you can utilise the following generative AI prompt: "What are some cost-effective strategies to improve customer loyalty for a small business?” 

Common AI prompt mistakes 

Being too vague: Neither artificial intelligence nor humans can read minds. You may have a clear image of the problem you're attempting to solve, including limits, items you've explored or done, and potential objections. But, unless you ask a very specific inquiry, neither your human friends nor your AI assistance will be able to pull those images from your thoughts. When asking for assistance, be specific and complete. 

Not being clear about the format: Would you prefer a list, a discussion, or a table? Do you want a comparison of factors or a detailed dive into the issues? The mistake happens when you ask a question but do not instruct the AI on how you want the response to be presented. This mistake isn't just about style and punctuation; it's about how the information is digested and improved for your final consumption. As with the first item on this list, be specific. Tell the AI what you're looking for and what you'll need to receive an answer. 

Not knowing when to take a step back: Sometimes AI cannot solve the problem or give the level of quality required. Fundamentally, an AI is a tool, and one tool cannot accomplish everything. Know when to hold 'em and when to fold them. Know when it's time to go back to a search engine, check forums, or create your own answers. There is a point of diminishing returns, and identifying it will save you time and frustration. 

How to write prompts successfully 

  • Use prompts that are specific, clear, and thorough. 
  • Remember that the AI is simply a program, not a magical oracle. 
  • Iterate and refine your queries by asking increasingly better questions.
  • Keep the prompt on topic. Specify details that provide context for your enquiries.
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Malware attacks
AI generated Deepfake AI tools Cyber Attacks data security Data Theft Fake Apps Information Security Malware attacks

Meeten Malware Targets Web3 Workers with Crypto-Stealing Tactics

 


Cybercriminals have launched an advanced campaign targeting Web3 professionals by distributing fake video conferencing software. The malware, known as Meeten, infects both Windows and macOS systems, stealing sensitive data, including cryptocurrency, banking details, browser-stored information, and Keychain credentials. Active since September 2024, Meeten masquerades as legitimate software while compromising users' systems. 
 
The campaign, uncovered by Cado Security Labs, represents an evolving strategy among threat actors. Frequently rebranded to appear authentic, fake meeting platforms have been renamed as Clusee, Cuesee, and Meetone. These platforms are supported by highly convincing websites and AI-generated social media profiles. 
 
How Victims Are Targeted:
  • Phishing schemes and social engineering tactics are the primary methods.
  • Attackers impersonate trusted contacts on platforms like Telegram.
  • Victims are directed to download the fraudulent Meeten app, often accompanied by fake company-specific presentations.

Key behaviors include:
  • Escalates privileges by prompting users for their system password via legitimate macOS tools.
  • Displays a decoy error message while stealing sensitive data in the background.
  • Collects and exfiltrates data such as Telegram credentials, banking details, Keychain data, and browser-stored information.
The stolen data is compressed and sent to remote servers, giving attackers access to victims’ sensitive information. 
 
Technical Details: Malware Behavior on Windows 

On Windows, the malware is delivered as an NSIS file named MeetenApp.exe, featuring a stolen digital certificate for added legitimacy. Key behaviors include:
  • Employs an Electron app to connect to remote servers and download additional malware payloads.
  • Steals system information, browser data, and cryptocurrency wallet credentials, targeting hardware wallets like Ledger and Trezor.
  • Achieves persistence by modifying the Windows registry.
Impact on Web3 Professionals 
 
Web3 professionals are particularly vulnerable as the malware leverages social engineering tactics to exploit trust. By targeting those engaged in cryptocurrency and blockchain technologies, attackers aim to gain access to valuable digital assets. Protective Measures:
  1. Verify Software Legitimacy: Always confirm the authenticity of downloaded software.
  2. Use Malware Scanning Tools: Scan files with services like VirusTotal before installation.
  3. Avoid Untrusted Sources: Download software only from verified sources.
  4. Stay Vigilant: Be cautious of unsolicited meeting invitations or unexpected file-sharing requests.
As social engineering tactics grow increasingly sophisticated, vigilance and proactive security measures are critical in safeguarding sensitive data and cryptocurrency assets. The Meeten campaign underscores the importance of staying informed and adopting robust cybersecurity practices in the Web3 landscape.
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telecommunications
AI Scams AI tools Cyber Security CyberCrime Fake Documents financial scams Fraud Online fraud SE Asia SIM telecommunications

Tamil Nadu Police, DoT Target SIM Card Fraud in SE Asia with AI Tools

 

The Cyber Crime Wing of Tamil Nadu Police, in collaboration with the Department of Telecommunications (DoT), is intensifying efforts to combat online fraud by targeting thousands of pre-activated SIM cards used in South-East Asian countries, particularly Laos, Cambodia, and Thailand. These SIM cards have been linked to numerous cybercrimes involving fraudulent calls and scams targeting individuals in Tamil Nadu. 

According to police sources, investigators employed Artificial Intelligence (AI) tools to identify pre-activated SIM cards registered with fake documents in Tamil Nadu but active in international locations. These cards were commonly used by scammers to commit fraud by making calls to unsuspecting victims in the State. The scams ranged from fake online trading opportunities to fraudulent credit or debit card upgrades. A senior official in the Cyber Crime Wing explained that a significant discrepancy was observed between the number of subscribers who officially activated international roaming services and the actual number of SIM cards being used abroad. 

The department is now working closely with central agencies to detect and block suspicious SIM cards.  The use of AI has proven instrumental in identifying mobile numbers involved in a disproportionately high volume of calls into Tamil Nadu. Numbers flagged by AI analysis undergo further investigation, and if credible evidence links them to cybercrimes, the SIM cards are promptly deactivated. The crackdown follows a series of high-profile scams that have defrauded individuals of significant amounts of money. 

For example, in Madurai, an advocate lost ₹96.57 lakh in June after responding to a WhatsApp advertisement promoting international share market trading with high returns. In another case, a government doctor was defrauded of ₹76.5 lakh through a similar investment scam. Special investigation teams formed by the Cyber Crime Wing have been successful in arresting several individuals linked to these fraudulent activities. Recently, a team probing ₹38.28 lakh frozen in various bank accounts apprehended six suspects. 

Following their interrogation, two additional suspects, Abdul Rahman from Melur and Sulthan Abdul Kadar from Madurai, were arrested. Authorities are also collaborating with police in North Indian states to apprehend more suspects tied to accounts through which the defrauded money was transacted. Investigations are ongoing in multiple cases, and the police aim to dismantle the network of fraudsters operating both within India and abroad. 

These efforts underscore the importance of using advanced technology like AI to counter increasingly sophisticated cybercrime tactics. By addressing vulnerabilities such as fraudulent SIM cards, Tamil Nadu’s Cyber Crime Wing is taking significant steps to protect citizens and mitigate financial losses.
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Technology
AI technology AI tools Business AI Copilot data security LLM Microsoft Salesforce Technology

Microsoft and Salesforce Clash Over AI Autonomy as Competition Intensifies

 

The generative AI landscape is witnessing fierce competition, with tech giants Microsoft and Salesforce clashing over the best approach to AI-powered business tools. Microsoft, a significant player in AI due to its collaboration with OpenAI, recently unveiled “Copilot Studio” to create autonomous AI agents capable of automating tasks in IT, sales, marketing, and finance. These agents are meant to streamline business processes by performing routine operations and supporting decision-making. 

However, Salesforce CEO Marc Benioff has openly criticized Microsoft’s approach, likening Copilot to “Clippy 2.0,” referencing Microsoft’s old office assistant software that was often ridiculed for being intrusive. Benioff claims Microsoft lacks the data quality, enterprise security, and integration Salesforce offers. He highlighted Salesforce’s Agentforce, a tool designed to help enterprises build customized AI-driven agents within Salesforce’s Customer 360 platform. According to Benioff, Agentforce handles tasks autonomously across sales, service, marketing, and analytics, integrating large language models (LLMs) and secure workflows within one system. 

Benioff asserts that Salesforce’s infrastructure is uniquely positioned to manage AI securely, unlike Copilot, which he claims may leak sensitive corporate data. Microsoft, on the other hand, counters that Copilot Studio empowers users by allowing them to build custom agents that enhance productivity. The company argues that it meets corporate standards and prioritizes data protection. The stakes are high, as autonomous agents are projected to become essential for managing data, automating operations, and supporting decision-making in large-scale enterprises. 

As AI tools grow more sophisticated, both companies are vying to dominate the market, setting standards for security, efficiency, and integration. Microsoft’s focus on empowering users with flexible AI tools contrasts with Salesforce’s integrated approach, which centers on delivering a unified platform for AI-driven automation. Ultimately, this rivalry is more than just product competition; it reflects two different visions for how AI can transform business. While Salesforce focuses on integrated security and seamless data flows, Microsoft is emphasizing adaptability and user-driven AI customization. 

As companies assess the pros and cons of each approach, both platforms are poised to play a pivotal role in shaping AI’s impact on business. With enterprises demanding robust, secure AI solutions, the outcomes of this competition could influence AI’s role in business for years to come. As these AI leaders continue to innovate, their differing strategies may pave the way for advancements that redefine workplace automation and decision-making across the industry.
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Hacking Techniques
AI technology AI tools Cyber Attacks Cyber Hacking. Data Analytics data security Ethical Hacking Hacking Techniques

The Growing Role of AI in Ethical Hacking: Insights from Bugcrowd’s 2024 Report

Bugcrowd’s annual “Inside the Mind of a Hacker” report for 2024 reveals new trends shaping the ethical hacking landscape, with an emphasis on AI’s role in transforming hacking tactics. Compiled from feedback from over 1,300 ethical hackers, the report explores how AI is rapidly becoming an integral tool in cybersecurity, shifting from simple automation to advanced data analysis. 

This year, a remarkable 71% of hackers say AI enhances the value of hacking, up from just 21% last year, highlighting its growing significance. For ethical hackers, data analysis is now a primary AI use case, surpassing task automation. With 74% of participants agreeing that AI makes hacking more accessible, new entrants are increasingly using AI-powered tools to uncover vulnerabilities in systems and software. This is a positive shift, as these ethical hackers disclose security flaws, allowing companies to strengthen their defenses before malicious actors can exploit them. 

However, it also means that criminal hackers are adopting AI in similar ways, creating both opportunities and challenges for cybersecurity. Dave Gerry, Bugcrowd’s CEO, emphasizes that while AI-driven threats evolve rapidly, ethical hackers are equally using AI to refine their methods. This trend is reshaping traditional cybersecurity strategies as hackers move toward more sophisticated, AI-enhanced approaches. While AI offers undeniable benefits, the security risks are just as pressing, with 81% of respondents recognizing AI as a significant potential threat. The report also underscores a key insight: while AI can complement human capabilities, it cannot fully replicate them. 

For example, only a minority of hackers surveyed felt that AI could surpass their skills or creativity. These findings suggest that while AI contributes to hacking, human insight remains crucial, especially in complex problem-solving and adaptive thinking. Michael Skelton, Bugcrowd’s VP of security, further notes that AI’s role in hardware hacking, a specialized niche, has expanded as Internet of Things (IoT) devices proliferate. AI helps identify tiny vulnerabilities in hardware that human hackers might overlook, such as power fluctuations and unusual electromagnetic signals. As AI reshapes the ethical hacking landscape, Bugcrowd’s report concludes with both a call to action and a note of caution. 

While AI offers valuable tools for ethical hackers, it equally empowers cybercriminals, accelerating the development of sophisticated, AI-driven attacks. This dual use highlights the importance of responsible, proactive cybersecurity practices. By leveraging AI to protect systems while staying vigilant against AI-fueled cyber threats, the hacking community can help guide the broader industry toward safer, more secure digital environments.
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Trafficking
AI generated Deepfake AI tools China Cyber Security Generative AI Pig Butchering Scamming Trafficking

AI Tools Fueling Global Expansion of China-Linked Trafficking and Scamming Networks

 

A recent report highlights the alarming rise of China-linked human trafficking and scamming networks, now using AI tools to enhance their operations. Initially concentrated in Southeast Asia, these operations trafficked over 200,000 people into compounds in Myanmar, Cambodia, and Laos. Victims were forced into cybercrime activities, such as “pig butchering” scams, impersonating law enforcement, and sextortion. Criminals have now expanded globally, incorporating generative AI for multi-language scamming, creating fake profiles, and even using deepfake technology to deceive victims. 

The growing use of these tools allows scammers to target victims more efficiently and execute more sophisticated schemes. One of the most prominent types of scams is the “pig butchering” scheme, where scammers build intimate online relationships with their victims before tricking them into investing in fake opportunities. These scams have reportedly netted criminals around $75 billion. In addition to pig butchering, Southeast Asian criminal networks are involved in various illicit activities, including job scams, phishing attacks, and loan schemes. Their ability to evolve with AI technology, such as using ChatGPT to overcome language barriers, makes them more effective at deceiving victims. 

Generative AI also plays a role in automating phishing attacks, creating fake identities, and writing personalized scripts to target individuals in different regions. Deepfake technology, which allows real-time face-swapping during video calls, is another tool scammers are using to further convince their victims of their fabricated personas. Criminals now can engage with victims in highly realistic conversations and video interactions, making it much more difficult for victims to discern between real and fake identities. The UN report warns that these technological advancements are lowering the barrier to entry for criminal organizations that may lack advanced technical skills but are now able to participate in lucrative cyber-enabled fraud. 

As scamming compounds continue to operate globally, there has also been an uptick in law enforcement seizing Starlink satellite devices used by scammers to maintain stable internet connections for their operations. The introduction of “crypto drainers,” a type of malware designed to steal funds from cryptocurrency wallets, has also become a growing concern. These drainers mimic legitimate services to trick victims into connecting their wallets, allowing attackers to gain access to their funds.  

As global law enforcement struggles to keep pace with the rapid technological advances used by these networks, the UN has stressed the urgency of addressing this growing issue. Failure to contain these ecosystems could have far-reaching consequences, not only for Southeast Asia but for regions worldwide. AI tools and the expanding infrastructure of scamming operations are creating a perfect storm for criminals, making it increasingly difficult for authorities to combat these crimes effectively. The future of digital scamming will undoubtedly see more AI-powered innovations, raising the stakes for law enforcement globally.
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synthetic ID fraud
AI tools Cyber Security Financial Loss Identity Fraud KYC SSN synthetic ID fraud

How Synthetic Identity Fraud is Draining Businesses


 

Synthetic identity fraud is quickly becoming one of the most complex forms of identity theft, posing a serious challenge to businesses, particularly those in the banking and finance sectors. Unlike traditional identity theft, where an entire identity is stolen, synthetic identity fraud involves combining real and fake information to create a new identity. Fraudsters often use real details such as Social Security Numbers (SSNs), especially those belonging to children or the elderly, which are less likely to be monitored. This blend of authentic and fabricated data makes it difficult for organisations to detect the fraud early, leading to financial losses.

What Is Synthetic Identity Fraud?

At its core, synthetic identity fraud is the creation of a fake identity using both real and made-up information. Criminals often use a legitimate SSN paired with a fake name, address, and date of birth to construct an identity that doesn’t belong to any actual person. Once this new identity is formed, fraudsters use it to apply for credit or loans, gradually building a credible financial profile. Over time, they increase their credit limit or take out large loans before disappearing, leaving businesses to shoulder the debt. This type of fraud is difficult to detect because there is no direct victim monitoring or reporting the crime.

How Does Synthetic Identity Fraud Work?

The process of synthetic identity fraud typically begins with criminals obtaining real SSNs, often through data breaches or the dark web. Fraudsters then combine this information with fake personal details to create a new identity. Although their first attempts at opening credit accounts may be rejected, these applications help establish a credit file for the fake identity. Over time, the fraudster builds credit by making small purchases and timely payments to gain trust. Eventually, they max out their credit lines and disappear, causing major financial damage to lenders and businesses.

Comparing Traditional VS Synthetic Identity Theft

The primary distinction between traditional and synthetic identity theft lies in how the identity is used. Traditional identity theft involves using someone’s complete identity to make unauthorised purchases or take out loans. Victims usually notice this quickly and report it, helping prevent further fraud. In contrast, synthetic identity theft is harder to detect because the identity is partly or entirely fabricated, and no real person is actively monitoring it. This gives fraudsters more time to cause substantial financial damage before the fraud is identified.

The Financial Impact of Synthetic Identity Theft

Synthetic identity fraud is costly. According to the Federal Reserve, businesses lose an average of $15,000 per case, and losses from this type of fraud are projected to reach $23 billion by 2030. Beyond direct financial losses, businesses also face operational costs related to investigating fraud, potential reputational damage, and legal or regulatory consequences if they fail to prevent such incidents. These widespread effects calls for stronger security measures.

How Can Synthetic Identity Fraud Be Detected?

While synthetic identity fraud is complex, there are several ways businesses can identify potential fraud. Monitoring for unusual account behaviours, such as perfect payment histories followed by large transactions or sudden credit line increases, is essential. Document verification processes, along with cross-checking identity details such as SSNs, can also help catch inconsistencies. Implementing biometric verification and using advanced analytics and AI-driven tools can further improve fraud detection. Collaborating with credit bureaus and educating employees and customers about potential fraud risks are other important steps companies can take to safeguard their operations.

Preventing Synthetic Identity Theft

Preventing synthetic identity theft requires a multi-layered approach. First, businesses should implement strong data security practices like encrypting sensitive information (e.g., Social Security Numbers) and using tokenization or anonymization to protect customer data. 

Identity verification processes must be enhanced with multi-factor authentication (MFA) and Know Your Customer (KYC) protocols, including biometrics such as facial recognition. This ensures only legitimate customers gain access.

Monitoring customer behaviour through machine learning and behavioural analytics is key. Real-time alerts for suspicious activity, such as sudden credit line increases, can help detect fraud early.

Businesses should also adopt data minimisation— collecting only necessary data—and enforce data retention policies to securely delete outdated information. Additionally, regular employee training on data security, phishing, and fraud prevention is crucial for minimising human error.

Conducting security audits and assessments helps detect vulnerabilities, ensuring compliance with data protection laws like GDPR or CCPA. Furthermore, guarding against insider threats through background checks and separation of duties adds an extra layer of protection.

When working with third-party vendors businesses should vet them carefully to ensure they meet stringent security standards, and include strict security measures in contracts.

Lastly, a strong incident response plan should be in place to quickly address breaches, investigate fraud, and comply with legal reporting requirements.


Synthetic identity fraud poses a serious challenge to businesses and industries, particularly those reliant on accurate identity verification. As criminals become more sophisticated, companies must adopt advanced security measures, including AI-driven fraud detection tools and stronger identity verification protocols, to stay ahead of the evolving threat. By doing so, they can mitigate financial losses and protect both their business and customers from this increasingly prevalent form of fraud.


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