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Cybercriminals Exploit Psychological Vulnerabilities in Ransomware Campaigns

 


During the decade of 2025, the cybersecurity landscape has drastically changed, with ransomware from a once isolated incident to a full-sized global crisis. No longer confined to isolated incidents, these attacks are now posing a tremendous threat to economies, governments, and public services across the globe. There is a wide range of organizations across all sectors that find themselves exposed to increasingly sophisticated cyber threats, ranging from multinational corporations to hospitals to schools. It is reported in Cohesity’s Global Cyber Resilience Report that 69% of organizations have paid ransom demands to their suppliers in the past year, which indicates just how much pressure businesses have to deal with when such attacks happen. 

The staggering number of cybercrime cases highlights the need for stronger cybersecurity measures, proactive threat mitigation strategies and a heightened focus on digital resilience. With cybercriminals continuously improving their tactics, organizations need to develop innovative security frameworks, increase their threat intelligence capabilities, and foster a culture of cyber vigilance to be able to combat this growing threat. The cybersecurity landscape in 2025 has changed significantly, as ransomware has evolved into a global crisis of unprecedented proportions. 

The threat of these attacks is not just limited to isolated incidents but has become a significant threat to governments, industries, and essential public services. Across the board, companies of all sizes are increasingly vulnerable to cyber threats, from multinational corporations to hospitals and schools. In the last year, Cohesity released its Global Cyber Resilience Report, which revealed that 69% of organizations paid ransom demands, indicating the immense pressure that businesses face in the wake of such threats. 

This staggering figure underscores how urgent it is that we take more aggressive cybersecurity measures, develop proactive threat mitigation strategies, and increase our emphasis on digital resilience to prevent cyberattacks from taking place. Organizations must embrace new security frameworks, strengthen threat intelligence capabilities, and cultivate a culture of cyber vigilance to combat this growing threat as cybercriminals continue to refine their tactics. A persistent cybersecurity threat for decades, ransomware remains one of the biggest threats today. 

However, the first global ransom payment exceeded $1 billion in 2023, marking a milestone that hasn't been achieved in many years. Cyber extortion increased dramatically at this time, as cyber attackers constantly refined their tactics to maximize the financial gains that they could garner from their victims. The trend of cybercriminals developing increasingly sophisticated methods and exploiting vulnerabilities, as well as forcing organizations into compliance, has been on the rise for several years. However, recent data indicates a significant shift in this direction. It is believed that in 2024, ransomware payments will decrease by a substantial 35%, mainly due to successful law enforcement operations and the improvement of cyber hygiene globally.

As a result of enhanced security measures, increased awareness, and a stronger collective resistance, victims of ransom attacks have become increasingly confident they can refuse ransom demands. However, cybercriminals are quick to adapt, altering their strategies quickly to counteract these evolving defences to stay on top of the game. A response from them has been to increase their negotiation tactics, negotiating more quickly with victims, while simultaneously developing stealthier and more evasive ransomware strains to be more stealthy and evasive. 

Organizations are striving to strengthen their resilience, but the ongoing battle between cybersecurity professionals and cybercriminals continues to shape the future of digital security. There has been a new era in ransomware attacks, characterized by cybercriminals leveraging artificial intelligence in increasingly sophisticated manners to carry out these attacks. Using freely available AI-powered chatbots, malicious code is being generated, convincing phishing emails are being sent, and even deepfake videos are being created to entice individuals to divulge sensitive information or transfer funds by manipulating them into divulging sensitive information. 

By making the barriers to entry much lower for cyber-attacking, even the least experienced threat actors are more likely to be able to launch highly effective cyber-attacks. Nevertheless, artificial intelligence is not being used only by attackers to commit crimes. There have been several cases where victims have attempted to craft the perfect response to a ransom negotiation using artificial intelligence-driven tools like ChatGPT, according to Sygnia's ransomware negotiation teams. 

The limitations of AI become evident in high-stakes interactions with cybercriminals, even though they can be useful in many areas. According to Cristal, Sygnia’s CEO, artificial intelligence lacks the emotional intelligence and nuance needed to successfully navigate these sensitive conversations. It has been observed that sometimes artificial intelligence-generated responses may unintentionally escalate a dispute by violating critical negotiation principles, such as not using negative language or refusing to pay outright.

It is clear from this that human expertise is crucial when it comes to managing cyber extortion scenarios, where psychological insight and strategic communication play a vital role in reducing the potential for damage. Earlier this year, the United Kingdom proposed banning ransomware payments, a move aimed at deterring cybercriminals by making critical industries less appealing targets for cybercriminals. This proposed legislation would affect all public sector agencies, schools, local councils, and data centres, as well as critical national infrastructure. 

By reducing the financial incentive for attackers, officials hope to decrease both the frequency and severity of ransomware incidents across the country to curb the number of ransomware incidents. However, the problem extends beyond the UK. In addition to the sanctions issued by the Office of Foreign Assets Control, several ransomware groups that have links to Russia and North Korea have already been sanctioned. This has made it illegal for American businesses and individuals to pay ransoms to these organizations. 

Even though ransomware is restricted in this manner, experts warn that outright bans are not a simple or universal solution to the problem. As cybersecurity specialists Segal and Cristal point out, such bans remain uncertain in their effectiveness, since it has been shown that attacks fluctuate in response to policy changes, according to the experts. Even though some cybercriminals may be deterred by such policies, other cybercriminals may escalate their tactics, reverting to more aggressive threats or increasing their personal extortion tactics. 

The Sygnia negotiation team continues to support the notion that ransom payments should be banned within government sectors because some ransomware groups are driven by geopolitical agendas, and these goals will be unaffected by payment restrictions. Even so, the Sygnia negotiation team believes that government institutions should not be able to make ransom payments because they are better able to handle financial losses than private companies. 

Governments can afford a strong stance against paying ransoms, as Segal pointed out, however for businesses, especially small and micro-sized businesses, the consequences can be devastating if they fail to do so. It was noted in its policy proposal that the Home Office acknowledges this disparity, noting that smaller companies, often lacking ransomware insurance or access to recovery services, can have difficulty recovering from operational disruptions and reputational damage when they suffer from ransomware attacks. 

Some companies could find it more difficult to resolve ransomware demands if they experience a prolonged cyberattack. This might lead to them opting for alternative, less transparent methods of doing so. This can include covert payment of ransoms through third parties or cryptocurrencies, allowing hackers to receive money anonymously and avoid legal consequences. The risks associated with such actions, however, are considerable. If they are discovered, businesses can be subjected to government fines on top of the ransom, which can further worsen their financial situation. 

Additionally, full compliance with the ban requires reporting incidents to authorities, which can pose a significant administrative burden to small businesses, especially those that are less accustomed to dealing with technology. Businesses are facing many challenges in the wake of a ransomware ban, which is why experts believe a comprehensive approach is needed to support them in the aftermath of this ban.

Sygnia's Senior Vice President of Global Cyber Services, Amir Becker, stressed the importance of implementing strategic measures to mitigate the unintended consequences of any ransom payment ban. It has been suggested that exemptions for critical infrastructure and the healthcare industries should be granted, since refusing to pay a ransom may lead to dire consequences, such as loss of life. Further, the government should offer incentives for organizations to strengthen their cybersecurity frameworks and response strategies by creating incentives like these.

A comprehensive financial and technical assistance program would be required to assist affected businesses in recovering without resorting to ransom payments. To address the growing ransomware threat effectively without disproportionately damaging small businesses and the broader economy, governments must adopt a balanced approach that entails enforcing stricter regulations while at the same time providing businesses with the resources they need to withstand cyberattacks.

How Web Browsers Have Become a Major Data Security Risk

 




For years, companies protected sensitive data by securing emails, devices, and internal networks. But work habits have changed. Now, most of the data moves through web browsers.  

Employees often copy, paste, upload, or transfer information online without realizing the risks. Web apps, personal accounts, AI tools, and browser extensions have made it harder to track where the data goes. Old security methods can no longer catch these new risks.  


How Data Slips Out Through Browsers  

Data leaks no longer happen only through obvious channels like USB drives or emails. Today, normal work tasks done inside browsers cause unintentional leaks.  

For example, a developer might paste secret codes into an AI chatbot. A salesperson could move customer details into their personal cloud account. A manager might give an online tool access to company data without knowing it.  

Because these activities happen inside approved apps, companies often miss the risks. Different platforms also store data differently, making it harder to apply the same safety rules everywhere.  

Simple actions like copying text, using extensions, or uploading files now create new ways for data to leak. Cloud services like AWS or Microsoft add another layer of confusion, as it becomes unclear where the data is stored.  

The use of multiple browsers, Chrome, Safari, Firefox — makes it even harder for security teams to keep an eye on everything.  


Personal Accounts Add to the Risk  

Switching between work and personal accounts during the same browser session is very common. People use services like Gmail, Google Drive, ChatGPT, and others without separating personal and office work.  

As a result, important company data often ends up in personal cloud drives, emails, or messaging apps without any bad intention from employees.  

Studies show that nearly 40% of web use in Google apps involves personal accounts. Blocking personal uploads is not a solution. Instead, companies need smart browser rules to separate work from personal use without affecting productivity.  


Moving Data Is the Most Dangerous Moment  

Data is most vulnerable when it is being shared or transferred — what experts call "data in motion." Even though companies try to label sensitive information, most protections work only when data is stored, not when it moves.  

Popular apps like Google Drive, Slack, and ChatGPT make sharing easy but also increase the risk of leaks. Old security systems fail because the biggest threats now come from tools employees use every day.  


Extensions and Unknown Apps — The Hidden Threat  

Browser extensions and third-party apps are another weak spot. Employees often install them without knowing how much access they give away.  

Some of these tools can record keystrokes, collect login details, or keep pulling data even after use. Since these risks often stay hidden, security teams struggle to control them.  

Today, browsers are the biggest weak spot in protecting company data. Businesses need better tools that control data flow inside the browser, keeping information safe without slowing down work.  


Finance Ministry Bans Use of AI Tools Like ChatGPT and DeepSeek in Government Work

 


The Ministry of Finance, under Nirmala Sitharaman’s leadership, has issued a directive prohibiting employees from using artificial intelligence (AI) tools such as ChatGPT and DeepSeek for official work. The decision comes over concerns about data security as these AI-powered platforms process and store information externally, potentially putting confidential government data at risk.  


Why Has the Finance Ministry Banned AI Tools?  

AI chatbots and virtual assistants have gained popularity for their ability to generate text, answer questions, and assist with tasks. However, since these tools rely on cloud-based processing, there is a risk that sensitive government information could be exposed or accessed by unauthorized parties.  

The ministry’s concern is that official documents, financial records, and policy decisions could unintentionally be shared with external AI systems, making them vulnerable to cyber threats or misuse. By restricting their use, the government aims to safeguard national data and prevent potential security breaches.  


Public Reactions and Social Media Buzz

The announcement quickly sparked discussions online, with many users sharing humorous takes on the decision. Some questioned how government employees would manage their workload without AI assistance, while others speculated whether Indian AI tools like Ola Krutrim might be an approved alternative.  

A few of the popular reactions included:  

1. "How will they complete work on time now?" 

2. "So, only Ola Krutrim is allowed?"  

3. "The Finance Ministry is switching back to traditional methods."  

4. "India should develop its own AI instead of relying on foreign tools."  


India’s Position in the Global AI Race

With AI development accelerating worldwide, several countries are striving to build their own advanced models. China’s DeepSeek has emerged as a major competitor to OpenAI’s ChatGPT and Google’s Gemini, increasing the competition in the field.  

The U.S. has imposed trade restrictions on Chinese AI technology, leading to growing tensions in the tech industry. Meanwhile, India has yet to launch an AI model capable of competing globally, but the government’s interest in regulating AI suggests that future developments could be on the horizon.  

While the Finance Ministry’s move prioritizes data security, it also raises questions about efficiency. AI tools help streamline work processes, and their restriction could lead to slower operations in certain departments.  

Experts suggest that India should focus on developing AI models that are secure and optimized for government use, ensuring that innovation continues without compromising confidential information.  

For now, the Finance Ministry’s stance reinforces the need for careful regulation of AI technologies, ensuring that security remains a top priority in government operations.



Dangers of AI Phishing Scam and How to Spot Them

Dangers of AI Phishing Scam and How to Spot Them

Supercharged AI phishing campaigns are extremely challenging to notice. Attackers use AI phishing scams with better grammar, structure, and spelling, to appear legit and trick the user. In this blog, we learn how to spot AI scams and avoid becoming victims

Checking email language

Earlier, it was easier to spot irregularities in an e-mail, all it took was one glance. As Gen AI models use flawless grammar,  it is almost impossible to find errors in your mail copy, 

Analyze the Language of the Email Carefully

In the past, one quick skim was enough to recognize something is off with an email, typically the incorrect grammar and laughable typos being the giveaways. Since scammers now use generative AI language models, most phishing messages have flawless grammar.

But there is hope. It is easier to identify Gen AI text, and keep an eye out for an unnatural flow of sentences, if everything seems to be too perfect, chances are it’s AI.

Red flags are everywhere, even mails

Though AI has made it difficult for users to find phishing scams, they show some classic behavior. The same tips apply to detect phishing emails.

In most cases, scammers mimic businesses and wish you won’t notice. For instance, instead of an official “info@members.hotstar.com” email ID, you may notice something like “info@members.hotstar-support.com.” You may also get unrequested links or attachments, which are a huge tell. URLs (mismatched) having subtle typos or extra words/letters are comparatively difficult to notice but a huge ti-off that you are on a malicious website or interacting with a fake business.

Beware of Deepfake video scams

The biggest issue these days is combating deepfakes, which are also difficult to spot. 

The attacker makes realistic video clips using photo and video prompts and uses video calling like Zoom or FaceTime to trap potential victims (especially elders and senior citizens) to give away sensitive data. 

One may think that only old people may fall for deepfakes, but due to their sophistication, even experts fall prey to them. One famous incident happened in Hong Kong, where scammers deepfake a company CFO and looted HK$200 million (roughly $25 million).

AI is advancing, and becoming stronger every day. It is a double-edged sword, both a blessing and a curse. One should tread the ethical lines carefully and hope they don’t fall to the dark side of AI.

Cyberattackers Exploit GhostGPT for Low-Cost Malware Development

 


The landscape of cybersecurity has been greatly transformed by artificial intelligence, which has provided both transformative opportunities as well as emerging challenges. Moreover, AI-powered security tools have made it possible for organizations to detect and respond to threats much more quickly and accurately than ever before, thereby enhancing the effectiveness of their cybersecurity defenses. 

These technologies allow for the analysis of large amounts of data in real-time, the identification of anomalies, and the prediction of potential vulnerabilities, strengthening a company's overall security. Cyberattackers have also begun using artificial intelligence technologies like GhostGPT to develop low-cost malware. 

By utilizing this technology, cyberattackers can create sophisticated, evasive malware, posing a serious threat to the security of the Internet. Therefore, organizations must remain vigilant and adapt their defenses to counter these evolving tactics. However, cybercriminals also use AI technology, such as GhostGPT, to develop low-cost malware, which presents a significant threat to organizations as they evolve. By exploiting this exploitation, they can devise sophisticated attacks that can overcome traditional security measures, thus emphasizing the dual-edged nature of artificial intelligence. 

Conversely, the advent of generative artificial intelligence has brought unprecedented risks along with it. Cybercriminals and threat actors are increasingly using artificial intelligence to craft sophisticated, highly targeted attacks. AI tools that use generative algorithms can automate phishing schemes, develop deceptive content, or even build alarmingly effective malicious code. Because of its dual nature, AI plays both a shield and a weapon in cybersecurity. 

There is an increased risk associated with the use of AI tools, as bad actors can harness these technologies with a relatively low level of technical competence and financial investment, which exacerbates these risks. The current trend highlights the need for robust cybersecurity strategies, ethical AI governance, and constant vigilance to protect against misuse of AI while at the same time maximizing its defense capabilities. It is therefore apparent that the intersection between artificial intelligence and cybersecurity remains a critical concern for the industry, policymakers, and security professionals alike. 

Recently introduced AI chatbot GhostGPT has emerged as a powerful tool for cybercriminals, enabling them to develop malicious software, business email compromise scams, and other types of illegal activities through the use of this chatbot. It is GhostGPT's uniqueness that sets it apart from mainstream artificial intelligence platforms such as ChatGPT, Claude, Google Gemini, and Microsoft Copilot in that it operates in an uncensored manner, intentionally designed to circumvent standard security protocols as well as ethical requirements. 

Because of its uncensored capability, it can create malicious content easily, providing threat actors with the resources to carry out sophisticated cyberattacks with ease. It is evident from the release of GhostGPT that generative AI poses a growing threat when it is weaponized, a concern that is being heightened within the cybersecurity community. 

A tool called GhostGPT is a type of artificial intelligence that enables the development and implementation of illicit activities such as phishing, malware development, and social engineering attacks by automating these activities. A reputable AI model like ChatGPT, which integrates security protocols to prevent abuse, does not have any ethical safeguards to protect against abuse. GhostGPT operates without ethical safeguards, which allows it to generate harmful content unrestrictedly. GhostGPT is marketed as an efficient tool for carrying out many malicious activities. 

A malware development kit helps developers generate foundational code, identify and exploit software vulnerabilities, and create polymorphic malware that can bypass detection mechanisms. In addition to enhancing the sophistication and scale of email-based attacks, GhostGPT also provides the ability to create highly customized phishing emails, business email compromise templates, and fraudulent website designs that are designed to fool users. 

By utilizing advanced natural language processing, it allows you to craft persuasive malicious messages that are resistant to traditional detection mechanisms. GhostGPT offers a highly reliable and efficient method for executing sophisticated social engineering attacks that raise significant concerns regarding security and privacy. GhostGPT uses an effective jailbreak or open-source configuration to execute such attacks. ASeveralkey features are included, such as the ability to produce malicious outputs instantly by cybercriminals, as well as a no-logging policy, which prevents the storage of interaction data and ensures user anonymity. 

The fact that GhostGPT is distributed through Telegram lowers entry barriers so that even people who do not possess the necessary technical skills can use it. Consequently, this raises serious concerns about its ability to escalate cybercrime. According to Abnormal Security, a screenshot of an advertisement for GhostGPT was revealed, highlighting GhostGPT's speed, ease of use, uncensored responses, strict no-log policy, and a commitment to protecting user privacy. 

According to the advertisement, the AI chatbot can be used for tasks such as coding, malware creation, and exploit creation, while also being referred to as a scam involving business email compromise (BEC). Furthermore, GhostGPT is referred to in the advertisement as a valuable cybersecurity tool and has been used for a wide range of other purposes. However, Abnormal has criticized these claims, pointing out that GhostGPT can be found on cybercrime forums and focuses on BEC scams, which undermines its supposed cybersecurity capabilities. 

It was discovered during the testing of the chatbot by abnormal researchers that the bot had the capability of generating malicious or maliciously deceptive emails, as well as phishing emails that would fool victims into believing that the emails were genuine. They claimed that the promotional disclaimer was a superficial attempt to deflect legal accountability, which is a tactic common within the cybercrime ecosystem. In light of GhostGPT's misuse, there is a growing concern that uncensored AI tools are becoming more and more dangerous. 

The threat of rogue AI chatbots such as GhostGPT is becoming increasingly severe for security organizations because they drastically lower the entry barrier for cybercriminals. Through simple prompts, anyone, regardless of whether they possess any coding skills or not, can quickly create malicious code. Aside from this, GhostGPT improves the capabilities of individuals with existing coding experience so that they can improve malware or exploits and optimize their development. 

GhostGPT eliminates the need for time-consuming efforts to jailbreak generative AI models by providing a straightforward and efficient method of creating harmful outcomes from them. Because of this accessibility and ease of use, the potential for malicious activities increases significantly, and this has led to a growing number of cybersecurity concerns. After the disappearance of ChatGPT in July 2023, WormGPT emerged as the first one of the first AI model that was specifically built for malicious purposes. 

It was developed just a few months after ChatGPT's rise and became one of the most feared AI models. There have been several similar models available on cybercrime marketplaces since then, like WolfGPT, EscapeGPT, and FraudGPT. However, many have not gained much traction due to unmet promises or simply being jailbroken versions of ChatGPT that have been wrapped up. According to security researchers, GhostGPT may also busea wrapper to connect to jailbroken versions of ChatGPT or other open-source language models. 

While GhostGPT has some similarities with models like WormGPT and EscapeGPT, researchers from Abnormal have yet to pinpoint its exact nature. As opposed to EscapeGPT, whose design is entirely based on jailbreak prompts, or WormGPT, which is entirely customized, GhostGPT's transparent origins complicate direct comparison, leaving a lot of uncertainty about whether it is a custom large language model or a modification of an existing model.

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.

The Rise of Agentic AI: How Autonomous Intelligence Is Redefining the Future

 


The Evolution of AI: From Generative Models to Agentic Intelligence

Artificial intelligence is rapidly advancing beyond its current capabilities, transitioning from tools that generate content to systems capable of making autonomous decisions and pursuing long-term objectives. This next frontier, known as Agentic AI, has the potential to revolutionize how machines interact with the world by functioning independently and adapting to complex environments.

Generative AI vs. Agentic AI: A Fundamental Shift

Generative AI models, such as ChatGPT and Google Gemini, analyze patterns in vast datasets to generate responses based on user prompts. These systems are highly versatile and assist with a wide range of tasks but remain fundamentally reactive, requiring human input to function. In contrast, agentic AI introduces autonomy, allowing machines to take initiative, set objectives, and perform tasks without continuous human oversight.

The key distinction lies in their problem-solving approaches. Generative AI acts as a responsive assistant, while agentic AI serves as an independent collaborator, capable of analyzing its environment, recognizing priorities, and making proactive decisions. By enabling machines to work autonomously, agentic AI offers the potential to optimize workflows, adapt to dynamic situations, and manage complex objectives over time.

Agentic AI systems leverage advanced planning modules, memory retention, and sophisticated decision-making frameworks to achieve their goals. These capabilities allow them to:

  • Break down complex objectives into manageable tasks
  • Monitor progress and maintain context over time
  • Adjust strategies dynamically based on changing circumstances

By incorporating these features, agentic AI ensures continuity and efficiency in executing long-term projects, distinguishing it from its generative counterparts.

Applications of Agentic AI

The potential impact of agentic AI spans multiple industries and applications. For example:

  • Business: Automating routine tasks, identifying inefficiencies, and optimizing workflows without human intervention.
  • Manufacturing: Overseeing production processes, responding to disruptions, and optimizing resource allocation autonomously.
  • Healthcare: Managing patient care plans, identifying early warning signs, and recommending proactive interventions.

Major AI companies are already exploring agentic capabilities. Reports suggest that OpenAI is working on projects aimed at enhancing AI autonomy, potentially enabling systems to control digital environments with minimal human input. These advancements highlight the growing importance of autonomous systems in shaping the future of technology.

Challenges and Ethical Considerations

Despite its transformative potential, agentic AI raises several challenges that must be addressed:

  • Transparency: Ensuring users understand how decisions are made.
  • Ethical Boundaries: Defining the level of autonomy granted to these systems.
  • Alignment: Maintaining alignment with human values and objectives to foster trust and widespread adoption.

Thoughtful development and robust regulation will be essential to ensure that agentic AI operates ethically and responsibly, mitigating potential risks while unlocking its full benefits.

The transition from generative to agentic AI represents a significant leap in artificial intelligence. By integrating autonomous capabilities, these systems can transform industries, enhance productivity, and redefine human-machine relationships. However, achieving this vision requires a careful balance between innovation and regulation. As AI continues to evolve, agentic intelligence stands poised to usher in a new era of technological progress, fundamentally reshaping how we interact with the world.

Ensuring Governance and Control Over Shadow AI

 


AI has become almost ubiquitous in software development, as a GitHub survey shows, 92 per cent of developers in the United States use artificial intelligence as part of their everyday coding. This has led many individuals to participate in what is termed “shadow AI,” which involves leveraging the technology without the knowledge or approval of their organization’s Information Technology department and/or Chief Information Security Officer (CISO). 

This has increased their productivity. In light of this, it should not come as a surprise to learn that motivated employees will seek out the technology that can maximize their value potential as well as minimize repetitive tasks that interfere with more creative, challenging endeavours. It is not uncommon for companies to be curious about new technologies, especially those that can be used to make work easier and more efficient, such as artificial intelligence (AI) and automation tools. 

Despite the increasing amount of ingenuity, some companies remain reluctant to adopt technology at their first, or even second, glances. Nevertheless, resisting change does not necessarily mean employees will stop secretly using AI in a non-technical way, especially since tools such as Microsoft Copilot, ChatGPT, and Claude make these technologies more accessible to non-technical employees.

Known as shadow AI, shadow AI is a growing phenomenon that has gained popularity across many different sectors. There is a concept known as shadow AI, which is the use of artificial intelligence tools or systems without the official approval or oversight of the organization's information technology or security department. These tools are often adopted to solve immediate problems or boost efficiency within an organization. 

If these tools are not properly governed, they can lead to data breaches, legal violations, or regulatory non-compliance, which could pose significant risks to businesses. When Shadow AI is not properly managed, it can introduce vulnerabilities into users' infrastructure that can lead to unauthorized access to sensitive data. In a world where artificial intelligence is becoming increasingly ubiquitous, organizations should take proactive measures to make sure their operations are protected. 

Shadow generative AI poses specific and substantial risks to an organization's integrity and security, and poses significant threats to both of them. A non-regulated use of artificial intelligence can lead to decisions and actions that could undermine regulatory and corporate compliance. Particularly in industries with very strict data handling protocols, such as finance and healthcare, where strict data handling protocols are essential. 

As a result of the bias inherent in the training data, generative AI models can perpetuate these biases, generate outputs that breach copyrights, or generate code that violates licensing agreements. The untested code may cause the software to become unstable or error-prone, which can increase maintenance costs and cause operational disruptions. In addition, such code may contain undetected malicious elements, which increases the risk of data breach and system downtime, as well.

It is important to recognize that the mismanagement of Artificial Intelligence interactions in customer-facing applications can result in regulatory non-compliance, reputational damage, as well as ethical concerns, particularly when the outputs adversely impact the customer experience. Consequently, organization leaders must ensure that their organizations are protected from unintended and adverse consequences when utilizing generative AI by implementing robust governance measures to mitigate these risks. 

In recent years, AI technology, including generative and conversational AI, has seen incredible growth in popularity, leading to widespread grassroots adoption of these technologies. The accessibility of consumer-facing AI tools, which require little to no technical expertise, combined with a lack of formal AI governance, has enabled employees to utilize unvetted AI solutions, The 2025 CX Trends Report highlights a 250% year-over-year increase in shadow AI usage in some industries, exposing organizations to heightened risks related to data security, compliance, and business ethics. 

There are many reasons why employees turn to shadow AI for personal or team productivity enhancement because they are dissatisfied with their existing tools, because of the ease of access, and because they want to enhance the ability to accomplish specific tasks. In the future, this gap will grow as CX Traditionalists delay the development of AI solutions due to limitations in budget, a lack of knowledge, or an inability to get internal support from their teams. 

As a result, CX Trendsetters are taking steps to address this challenge by adopting approved artificial intelligence solutions like AI agents and customer experience automation, as well as ensuring the appropriate oversight and governance are in place. Identifying AI Implementations: CISOs and security teams, must determine who will be introducing AI throughout the software development lifecycle (SDLC), assess their security expertise, and evaluate the steps taken to minimize risks associated with AI deployment. 

In training programs, it is important to raise awareness among developers of the importance and potential of AI-assisted code as well as develop their skills to address these vulnerabilities. To identify vulnerable phases of the software development life cycle, the security team needs to analyze each phase of the SDLC and identify if any are vulnerable to unauthorized uses of AI. 

Fostering a Security-First Culture: By promoting a proactive protection mindset, organizations can reduce the need for reactive fixes by emphasizing the importance of securing their systems from the onset, thereby saving time and money. In addition to encouraging developers to prioritize safety and transparency over convenience, a robust security-first culture, backed by regular training, encourages a commitment to security. 

CISOs are responsible for identifying and managing risks associated with new tools and respecting decisions made based on thorough evaluations. This approach builds trust, ensures tools are properly vetted before deployment, and safeguards the company's reputation. Incentivizing Success: There is great value in having developers who contribute to bringing AI usage into compliance with their organizations. 

For this reason, these individuals should be promoted, challenged, and given measurable benchmarks to demonstrate their security skills and practices. As organizations reward these efforts, they create a culture in which AI deployment is considered a critical, marketable skill that can be acquired and maintained. If these strategies are implemented effectively, a CISO and development teams can collaborate to manage AI risks the right way, ensuring faster, safer, and more effective software production while avoiding the pitfalls caused by shadow AI. 

As an alternative to setting up sensitive alerts to make sure that confidential data isn't accidentally leaked, it is also possible to set up tools using artificial intelligence, for example, to help detect when a model of artificial intelligence incorrectly inputs or processes personal data, financial information, or other proprietary information. 

It is possible to identify and mitigate security breaches in real-time by providing real-time alerts in real-time, and by enabling management to reduce these breaches before they escalate into a full-blown security incident, adding a layer of security protection, in this way. 

When an API strategy is executed well, it is possible to give employees the freedom to use GenAI tools productively while safeguarding the company's data, ensuring that AI usage is aligned with internal policies, and protecting the company from fraud. To increase innovation and productivity, one must strike a balance between securing control and ensuring that security is not compromised.

Dutch Authority Flags Concerns Over AI Standardization Delays

 


As the Dutch privacy watchdog DPA announced on Wednesday, it was concerned that software developers developing artificial intelligence (AI) might use personal data. To get more information about this, DPA sent a letter to Microsoft-backed OpenAI. The Dutch Data Protection Authority (Dutch DPA) imposed a fine of 30.5 million euros on Clearview AI and ordered that they be subject to a penalty of up to 5 million euros if they fail to comply. 

As a result of the company's illegal database of billions of photographs of faces, including Dutch people, Clearview is an American company that offers facial recognition services. They have built an illegal database. According to their website, the Dutch DPA warns that Clearview's services are also prohibited. In light of the rapid growth of OpenAI's ChatGPT consumer app, governments, including those of the European Union, are considering how to regulate the technology. 

There is a senior official from the Dutch privacy watchdog Autoriteit Persoonsgegevens (AP), who told Euronews that the process of developing artificial intelligence standards will need to take place faster, in light of the AI Act. Introducing the EU AI Act, which is the first comprehensive AI law in the world. The regulation aims to address health and safety risks, as well as fundamental human rights issues, as well as democracy, the rule of law, and environmental protection. 

By adopting artificial intelligence systems, there is a strong possibility to benefit society, contribute to economic growth, enhance EU innovation and competitiveness as well as enhance EU innovation and global leadership. However, in some cases, the specific characteristics of certain AI systems may pose new risks relating to user safety, including physical safety and fundamental rights. 

There have even been instances where some of these powerful AI models could pose systemic risks if they are widely used. Since there is a lack of trust, this creates legal uncertainty and may result in a slower adoption of AI technologies by businesses, citizens, and public authorities due to legal uncertainties. Regulatory responses by national governments that are disparate could fragment the internal market. 

To address these challenges, legislative action was required to ensure that both the benefits and risks of AI systems were adequately addressed to ensure that the internal market functioned well. As for the standards, they are a way for companies to be reassured, and to demonstrate that they are complying with the regulations, but there is still a great deal of work to be done before they are available, and of course, time is running out,” said Sven Stevenson, who is the agency's director of coordination and supervision for algorithms. 

CEN-CELENEC and ETSI were tasked by the European Commission in May last year to compile the underlying standards for the industry, which are still being developed and this process continues to be carried out. This data protection authority, which also oversees the General Data Protection Regulation (GDPR), is likely to have the shared responsibility of checking the compliance of companies with the AI Act with other authorities, such as the Dutch regulator for digital infrastructure, the RDI, with which they will likely share this responsibility. 

By August next year, all EU member states will have to select their AI regulatory agency, and it appears that in most EU countries, national data protection authorities will be an excellent choice. The AP has already dealt with cases in which companies' artificial intelligence tools were found to be in breach of GDPR in its capacity as a data regulator. 

A US facial recognition company known as Clearview AI was fined €30.5 million in September for building an illegal database of photos and unique biometric codes linked to Europeans in September, which included photos, unique biometric codes, and other information. The AI Act will be complementary to GDPR, since it focuses primarily on data processing, and would have an impact in the sense that it pertains to product safety in future cases. Increasingly, the Dutch government is promoting the development of new technologies, including artificial intelligence, to promote the adoption of these technologies. 

The deployment of such technologies could have a major impact on public values like privacy, equality in the law, and autonomy. This became painfully evident when the scandal over childcare benefits in the Netherlands was brought to public attention in September 2018. The scandal in question concerns thousands of parents who were falsely accused of fraud by the Dutch tax authorities because of discriminatory self-learning algorithms that were applied while attempting to regulate the distribution of childcare benefits while being faced with discriminatory self-learning algorithms. 

It has been over a year since the Amsterdam scandal raised a great deal of controversy in the Netherlands, and there has been an increased emphasis on the supervision of new technologies, and in particular artificial intelligence, as a result, the Netherlands intentionally emphasizes and supports a "human-centred approach" to artificial intelligence. Taking this approach means that AI should be designed and used in a manner that respects human rights as the basis of its purpose, design, and use. AI should not weaken or undermine public values and human rights but rather reinforce them rather than weaken them. 

During the last few months, the Commission has established the so-called AI Pact, which provides workshops and joint commitments to assist businesses in getting ready for the upcoming AI Act. On a national level, the AP has also been organizing pilot projects and sandboxes with the Ministry of RDI and Economic Affairs so that companies can become familiar with the rules as they become more aware of them. 

Further, the Dutch government has also published an algorithm register as of December 2022, which is a public record of algorithms used by the government, which is intended to ensure transparency and explain the results of algorithms, and the administration wants these algorithms to be legally checked for discrimination and arbitrariness.

The Privacy Risks of ChatGPT and AI Chatbots

 


AI chatbots like ChatGPT have captured widespread attention for their remarkable conversational abilities, allowing users to engage on diverse topics with ease. However, while these tools offer convenience and creativity, they also pose significant privacy risks. The very technology that powers lifelike interactions can also store, analyze, and potentially resurface user data, raising critical concerns about data security and ethical use.

The Data Behind AI's Conversational Skills

Chatbots like ChatGPT rely on Large Language Models (LLMs) trained on vast datasets to generate human-like responses. This training often includes learning from user interactions. Much like how John Connor taught the Terminator quirky catchphrases in Terminator 2: Judgment Day, these systems refine their capabilities through real-world inputs. However, this improvement process comes at a cost: personal data shared during conversations may be stored and analyzed, often without users fully understanding the implications.

For instance, OpenAI’s terms and conditions explicitly state that data shared with ChatGPT may be used to improve its models. Unless users actively opt-out through privacy settings, all shared information—from casual remarks to sensitive details like financial data—can be logged and analyzed. Although OpenAI claims to anonymize and aggregate user data for further study, the risk of unintended exposure remains.

Real-World Privacy Breaches

Despite assurances of data security, breaches have occurred. In May 2023, hackers exploited a vulnerability in ChatGPT’s Redis library, compromising the personal data of around 101,000 users. This breach underscored the risks associated with storing chat histories, even when companies emphasize their commitment to privacy. Similarly, companies like Samsung faced internal crises when employees inadvertently uploaded confidential information to chatbots, prompting some organizations to ban generative AI tools altogether.

Governments and industries are starting to address these risks. For instance, in October 2023, President Joe Biden signed an executive order focusing on privacy and data protection in AI systems. While this marks a step in the right direction, legal frameworks remain unclear, particularly around the use of user data for training AI models without explicit consent. Current practices are often classified as “fair use,” leaving consumers exposed to potential misuse.

Protecting Yourself in the Absence of Clear Regulations

Until stricter regulations are implemented, users must take proactive steps to safeguard their privacy while interacting with AI chatbots. Here are some key practices to consider:

  1. Avoid Sharing Sensitive Information
    Treat chatbots as advanced algorithms, not confidants. Avoid disclosing personal, financial, or proprietary information, no matter how personable the AI seems.
  2. Review Privacy Settings
    Many platforms offer options to opt out of data collection. Regularly review and adjust these settings to limit the data shared with AI

Generative AI Fuels Financial Fraud

 


According to the FBI, criminals are increasingly using generative artificial intelligence (AI) to make their fraudulent schemes more convincing. This technology enables fraudsters to produce large amounts of realistic content with minimal time and effort, increasing the scale and sophistication of their operations.

Generative AI systems work by synthesizing new content based on patterns learned from existing data. While creating or distributing synthetic content is not inherently illegal, such tools can be misused for activities like fraud, extortion, and misinformation. The accessibility of generative AI raises concerns about its potential for exploitation.

AI offers significant benefits across industries, including enhanced operational efficiency, regulatory compliance, and advanced analytics. In the financial sector, it has been instrumental in improving product customization and streamlining processes. However, alongside these benefits, vulnerabilities have emerged, including third-party dependencies, market correlations, cyber risks, and concerns about data quality and governance.

The misuse of generative AI poses additional risks to financial markets, such as facilitating financial fraud and spreading false information. Misaligned or poorly calibrated AI models may result in unintended consequences, potentially impacting financial stability. Long-term implications, including shifts in market structures, macroeconomic conditions, and energy consumption, further underscore the importance of responsible AI deployment.

Fraudsters have increasingly turned to generative AI to enhance their schemes, using AI-generated text and media to craft convincing narratives. These include social engineering tactics, spear-phishing, romance scams, and investment frauds. Additionally, AI can generate large volumes of fake social media profiles or deepfake videos, which are used to manipulate victims into divulging sensitive information or transferring funds. Criminals have even employed AI-generated audio to mimic voices, misleading individuals into believing they are interacting with trusted contacts.

In one notable incident reported by the FBI, a North Korean cybercriminal used a deepfake video to secure employment with an AI-focused company, exploiting the position to access sensitive information. Similarly, Russian threat actors have been linked to fake videos aimed at influencing elections. These cases highlight the broad potential for misuse of generative AI across various domains.

To address these challenges, the FBI advises individuals to take several precautions. These include establishing secret codes with trusted contacts to verify identities, minimizing the sharing of personal images or voice data online, and scrutinizing suspicious content. The agency also cautions against transferring funds, purchasing gift cards, or sending cryptocurrency to unknown parties, as these are common tactics employed in scams.

Generative AI tools have been used to improve the quality of phishing messages by reducing grammatical errors and refining language, making scams more convincing. Fraudulent websites have also employed AI-powered chatbots to lure victims into clicking harmful links. To reduce exposure to such threats, individuals are advised to avoid sharing sensitive personal information online or over the phone with unverified sources.

By remaining vigilant and adopting these protective measures, individuals can mitigate their risk of falling victim to fraud schemes enabled by emerging AI technologies.

Malicious Python Packages Target Developers Using AI Tools





The rise of generative AI (GenAI) tools like OpenAI’s ChatGPT and Anthropic’s Claude has created opportunities for attackers to exploit unsuspecting developers. Recently, two Python packages falsely claiming to provide free API access to these chatbot platforms were found delivering a malware known as "JarkaStealer" to their victims.


Exploiting Developers’ Interest in AI

Free and free-ish generative AI platforms are gaining popularity, but the benefits of most of their advanced features cost money. This led certain developers to look for free alternatives, many of whom didn't really check the source to be sure. Cybercrime follows trends and the trend is that malicious code is being inserted into open-source software packages that at least initially may appear legitimate.

As George Apostopoulos, a founding engineer at Endor Labs, describes, attackers target less cautious developers, lured by free access to popular AI tools. "Many people don't know better and fall for these offers," he says.


The Harmful Python Packages

Two evil Python packages, "gptplus" and "claudeai-eng," were uploaded to the Python Package Index, PyPI, one of the official repositories of open-source Python projects. The GPT-4 Turbo model by OpenAI and Claude chatbot by Anthropic were promised by API integrations from the user "Xeroline.".

While the packages seemed to work by connecting users to a demo version of ChatGPT, their true functionality was much nastier. The code also contained an ability to drop a Java archive (JAR) file which delivered the JarkaStealer malware to unsuspecting victims' systems.


What Is JarkaStealer?

The JarkaStealer is an infostealer malware that can extract sensitive information from infected systems. It has been sold on the Dark Web for as little as $20, but its more elaborate features can be bought for a few dollars more, which is designed to steal browser data and session tokens along with credentials for apps like Telegram, Discord, and Steam. It can also take screenshots of the victim's system, often revealing sensitive information.

Though the malware's effectiveness is highly uncertain, it is cheap enough and readily available to many attackers as an attractive tool. Its source code is even freely accessible on platforms like GitHub for an even wider reach.


Lessons for Developers

This incident points to risks in downloading unverified packages of open source, more so when handling emerging technologies such as AI. Development firms should screen all software sources to avoid shortcuts that seek free premium tools. Taking precautionary measures can save individuals and organizations from becoming victims of such attacks.

With regard to caution and best practices, developers are protected from malicious actors taking advantage of the GenAI boom.

PyPI Attack: Hackers Use AI Models to Deliver JarkaStealer via Python Libraries

PyPI Attack: Hackers Use AI Models to Deliver JarkaStealer via Python Libraries

Cybersecurity researchers have discovered two malicious packages uploaded to the Python Package Index (PyPI) repository that impersonated popular artificial intelligence (AI) models like OpenAI ChatGPT and Anthropic Claude to deliver an information stealer called JarkaStealer. 

The supply chain campaign shows the advancement of cyber threats attacking developers and the urgent need for caution in open-source activities. 

Experts have found two malicious packages uploaded to the Python Index (PyPI) repository pretending to be popular artificial intelligence (AI) models like OpenAI Chatgpt and Anthropic Claude to distribute an information stealer known as JarkaStealer. 

About attack vector

Called gptplus and claudeai-eng, the packages were uploaded by a user called "Xeroline" last year, resulting in 1,748 and 1,826 downloads. The two libraries can't be downloaded from PyPI. According to Kaspersky, the malicious packages were uploaded to the repository by one author and differed only in name and description. 

Experts believe the package offered a way to access GPT-4 Turbo and Claude AI API but contained malicious code that, upon installation, started the installation of malware. 

Particularly, the "__init__.py" file in these packages included Base64-encoded data that included code to download a Java archive file ("JavaUpdater.jar") from a GitHub repository, also downloading the Java Runtime Environment (JRE) from a Dropbox URL in case Java isn't already deployed on the host, before running the JAR file.

The impact

Based on information stealer JarkaStealer, the JAR file can steal a variety of sensitive data like web browser data, system data, session tokens, and screenshots from a wide range of applications like Steam, Telegram, and Discord. 

In the last step, the stolen data is archived, sent to the attacker's server, and then removed from the target's machine.JarkaStealer is known to offer under a malware-as-a-service (MaaS) model through a Telegram channel for a cost between $20 and $50, however, the source code has been leaked on GitHub. 

ClickPy stats suggest packages were downloaded over 3,500 times, primarily by users in China, the U.S., India, Russia, Germany, and France. The attack was part of an all-year supply chain attack campaign. 

How JarkaStealer steals

  • Steals web browser data- cookies, browsing history, and saved passwords. 
  • Compromises system data and setals OS details and user login details.
  • Steals session tokens from apps like Discord, Telegram, and Steam.
  • Captures real-time desktop activity through screenshots.

The stolen information is compressed and transmitted to a remote server controlled by the hacker, where it is removed from the target’s device.

OpenAI's Latest AI Model Faces Diminishing Returns

 

OpenAI's latest AI model is yielding diminishing results while managing the demands of recent investments. 

The Information claims that OpenAI's upcoming AI model, codenamed Orion, is outperforming its predecessors in terms of performance gains. In staff testing, Orion reportedly achieved the GPT-4 performance level after only 20% of its training. 

However, the shift from GPT-4 to the upcoming GPT-5 is expected to result in fewer quality gains than the jump from GPT-3 to GPT-4.

“Some researchers at the company believe Orion isn’t reliably better than its predecessor in handling certain tasks,” noted employees in the report. “Orion performs better at language tasks but may not outperform previous models at tasks such as coding, according to an OpenAI employee.”

AI training often yields the biggest improvements in performance in the early stages and smaller gains in subsequent phases. As a result, the remaining 80% of training is unlikely to provide breakthroughs comparable to earlier generational improvements. This predicament with its latest AI model comes at a critical juncture for OpenAI, following a recent investment round that raised $6.6 billion.

With this financial backing, investors' expectations rise, as do technical hurdles that confound typical AI scaling approaches. If these early versions do not live up to expectations, OpenAI's future fundraising chances may not be as attractive. The report's limitations underscore a major difficulty for the entire AI industry: the decreasing availability of high-quality training data and the need to remain relevant in an increasingly competitive environment.

A June research (PDF) predicts that between 2026 and 2032, AI companies will exhaust the supply of publicly accessible human-generated text data. Developers have "largely squeezed as much out of" the data that has been utilised to enable the tremendous gains in AI that we have witnessed in recent years, according to The Information. OpenAI is fundamentally rethinking its approach to AI development in order to meet these challenges. 

“In response to the recent challenge to training-based scaling laws posed by slowing GPT improvements, the industry appears to be shifting its effort to improving models after their initial training, potentially yielding a different type of scaling law,” states The Information.

Want to Make the Most of ChatGPT? Here Are Some Go-To Tips

 







Within a year and a half, ChatGPT has grown from an AI prototype to a broad productivity assistant, even sporting its text and code editor called Canvas. Soon, OpenAI will add direct web search capability to ChatGPT, putting the platform at the same table as Google's iconic search. With these fast updates, ChatGPT is now sporting quite a few features that may not be noticed at first glance but are deepening the user experience if one knows where to look.

This is the article that will teach you how to tap into ChatGPT, features from customization settings to unique prompting techniques, and not only five must-know tips will be useful in unlocking the full range of abilities of ChatGPT to any kind of task, small or big.


1. Rename Chats for Better Organisation

A new conversation with ChatGPT begins as a new thread, meaning that it will remember all details concerning that specific exchange but "forget" all the previous ones. This way, you can track the activities of current projects or specific topics because you can name your chats. The chat name that it might try to suggest is related to the flow of the conversation, and these are mostly overlooked contexts that users need to recall again. Renaming your conversations is one simple yet powerful means of staying organised if you rely on ChatGPT for various tasks.

To give a name to a conversation, tap the three dots next to the name in the sidebar. You can also archive older chats to remove them from the list without deleting them entirely, so you don't lose access to the conversations that are active.


2. Customise ChatGPT through Custom Instructions

Custom Instructions in ChatGPT is a chance to make your answers more specific to your needs because you will get to share your information and preferences with the AI. This is a two-stage personalization where you are explaining to ChatGPT what you want to know about yourself and, in addition, how you would like it to be returned. For instance, if you ask ChatGPT for coding advice several times a week, you can let the AI know what programming languages you are known in or would like to be instructed in so it can fine-tune the responses better. Or, you should be able to ask for ChatGPT to provide more verbose descriptions or to skip steps in order to make more intuitive knowledge of a topic.

To set up personal preferences, tap the profile icon on the upper right, and then from the menu, "Customise ChatGPT," and then fill out your preferences. Doing this will enable you to get responses tailored to your interests and requirements.


3. Choose the Right Model for Your Use

If you are a subscriber to ChatGPT Plus, you have access to one of several AI models each tailored to different tasks. The default model for most purposes is GPT-4-turbo (GPT-4o), which tends to strike the best balance between speed and functionality and even supports other additional features, including file uploads, web browsing, and dataset analysis.

However, other models are useful when one needs to describe a rather complex project with substantial planning. You may initiate a project using o1-preview that requires deep research and then shift the discussion to GPT-4-turbo to get quick responses. To switch models, you can click on the model dropdown at the top of your screen or type in a forward slash (/) in the chat box to get access to more available options including web browsing and image creation.


4. Look at what the GPT Store has available in the form of Mini-Apps

Custom GPTs, and the GPT Store enable "mini-applications" that are able to extend the functionality of the platform. The Custom GPTs all have some inbuilt prompts and workflows and sometimes even APIs to extend the AI capability of GPT. For instance, with Canva's GPT, you are able to create logos, social media posts, or presentations straight within the ChatGPT portal by linking up the Canva tool. That means you can co-create visual content with ChatGPT without having to leave the portal.

And if there are some prompts you often need to apply, or some dataset you upload most frequently, you can easily create your Custom GPT. This would be really helpful to handle recipes, keeping track of personal projects, create workflow shortcuts and much more. Go to the GPT Store by the "Explore GPTs" button in the sidebar. Your recent and custom GPTs will appear in the top tab, so find them easily and use them as necessary.


5. Manage Conversations with a Fresh Approach

For the best benefit of using ChatGPT, it is key to understand that every new conversation is an independent document with its "memory." It does recall enough from previous conversations, though generally speaking, its answers depend on what is being discussed in the immediate chat. This made chats on unrelated projects or topics best started anew for clarity.

For long-term projects, it might even be logical to go on with a single thread so that all relevant information is kept together. For unrelated topics, it might make more sense to start fresh each time to avoid confusion. Another way in which archiving or deleting conversations you no longer need can help free up your interface and make access to active threads easier is


What Makes AI Unique Compared to Other Software?

AI performs very differently from other software in that it responds dynamically, at times providing responses or "backtalk" and does not simply do what it is told to do. Such a property leads to some trial and error to obtain the desired output. For instance, one might prompt ChatGPT to review its own output as demonstrated by replacing single quote characters by double quote characters to generate more accurate results. This is similar to how a developer optimises an AI model, guiding ChatGPT to "think" through something in several steps.

ChatGPT Canvas and other features like Custom GPTs make the AI behave more like software in the classical sense—although, of course, with personality and learning. If ChatGPT continues to grow in this manner, features such as these may make most use cases easier and more delightful.

Following these five tips should help you make the most of ChatGPT as a productivity tool and keep pace with the latest developments. From renaming chats to playing around with Custom GPTs, all of them add to a richer and more customizable user experience.


OpenAI’s Disruption of Foreign Influence Campaigns Using AI

 

Over the past year, OpenAI has successfully disrupted over 20 operations by foreign actors attempting to misuse its AI technologies, such as ChatGPT, to influence global political sentiments and interfere with elections, including in the U.S. These actors utilized AI for tasks like generating fake social media content, articles, and malware scripts. Despite the rise in malicious attempts, OpenAI’s tools have not yet led to any significant breakthroughs in these efforts, according to Ben Nimmo, a principal investigator at OpenAI. 

The company emphasizes that while foreign actors continue to experiment, AI has not substantially altered the landscape of online influence operations or the creation of malware. OpenAI’s latest report highlights the involvement of countries like China, Russia, Iran, and others in these activities, with some not directly tied to government actors. Past findings from OpenAI include reports of Russia and Iran trying to leverage generative AI to influence American voters. More recently, Iranian actors in August 2024 attempted to use OpenAI tools to generate social media comments and articles about divisive topics such as the Gaza conflict and Venezuelan politics. 

A particularly bold attack involved a Chinese-linked network using OpenAI tools to generate spearphishing emails, targeting OpenAI employees. The attack aimed to plant malware through a malicious file disguised as a support request. Another group of actors, using similar infrastructure, utilized ChatGPT to answer scripting queries, search for software vulnerabilities, and identify ways to exploit government and corporate systems. The report also documents efforts by Iran-linked groups like CyberAveng3rs, who used ChatGPT to refine malicious scripts targeting critical infrastructure. These activities align with statements from U.S. intelligence officials regarding AI’s use by foreign actors ahead of the 2024 U.S. elections. 

However, these nations are still facing challenges in developing sophisticated AI models, as many commercial AI tools now include safeguards against malicious use. While AI has enhanced the speed and credibility of synthetic content generation, it has not yet revolutionized global disinformation efforts. OpenAI has invested in improving its threat detection capabilities, developing AI-powered tools that have significantly reduced the time needed for threat analysis. The company’s position at the intersection of various stages in influence operations allows it to gain unique insights and complement the work of other service providers, helping to counter the spread of online threats.