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.
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.
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.
The stolen information is compressed and transmitted to a remote server controlled by the hacker, where it is removed from the target’s device.
India, with rapid digital growth and reliance on technology, is in the hit list of cybercriminals. As one of the world's biggest economies, the country poses a distinct digital threat that cyber-crooks might exploit due to security holes in businesses, institutions, and personal users.
India recently saw a 51 percent surge in ransomware attacks in 2023 according to the Indian Computer Emergency Response Team, or CERT-In. Small and medium-sized businesses have been an especially vulnerable target, with more than 300 small banks being forced to close briefly in July after falling prey to a ransomware attack. For millions of Indians using digital banking for daily purchases and payments, such glitches underscore the need for further improvement in cybersecurity measures. A report from Kaspersky shows that 53% of SMBs operating in India have experienced the incidents of ransomware up till now this year, with more than 559 million cases being reported over just two months, starting from April and May this year.
Cyber Thugs are not only locking computers in businesses but extending attacks to individuals, even if it is personal electronic gadgets, stealing sensitive and highly confidential information. A well-organised group of attacks in the wave includes Mallox, RansomHub, LockBit, Kill Security, and ARCrypter. Such entities take advantage of Indian infrastructure weaknesses and focus on ransomware-as-a-service platforms that support Microsoft SQL databases. Recovery costs for affected organisations usually exceeded ₹11 crore and averaged ₹40 crore per incident in India, according to estimates for 2023. The financial sector, in particular the National Payment Corporation of India (NPCI), has been attacked very dearly, and it is crystal clear that there is an imperative need to strengthen the digital financial framework of India.
Cyber Defence Through AI
Indian organisations are now employing AI to fortify their digital defence. AI-based tools process enormous data in real time and report anomalies much more speedily than any manual system. From financial to healthcare sectors, high-security risks make AI become more integral in cybersecurity strategies in the sector. Lenovo's recent AI-enabled security initiatives exemplify how the technology has become mainstream with 71% of retailers in India adopting or planning to adopt AI-powered security.
As India pushes forward on its digital agenda, the threat of ransomware cannot be taken lightly. It will require intimate collaboration between government and private entities, investment in education in AI and cybersecurity, as well as creating safer environments for digital existence. For this, the government Cyber Commando initiative promises forward movement, but collective endeavours will be crucial to safeguarding India's burgeoning digital economy.
Artificial intelligence, once considered a tool for enhancing security measures, has become a threat. Cybercriminals are leveraging AI to orchestrate more sophisticated and pervasive attacks. AI’s capability to analyze vast amounts of data at lightning speed, identify vulnerabilities, and execute attacks autonomously has rendered traditional security measures obsolete.
Sneha Katkar from Quick Heal notes, “The landscape of cybercrime has evolved significantly with AI automating and enhancing these attacks.”
Cybercriminals employed AI-driven tools to bypass security protocols, resulting in the compromise of sensitive data. Such incidents underscore the urgent need for upgraded security frameworks to counter these advanced threats.
The rise of AI-powered malware and ransomware is particularly concerning. These malicious programs can adapt, learn, and evolve, making them harder to detect and neutralize. Traditional antivirus software, which relies on signature-based detection, is often ineffective against such threats. As Katkar pointed out, “AI-driven cyberattacks require an equally sophisticated response.”
One of the critical challenges in combating AI-driven cyberattacks is the speed at which these attacks can be executed. Automated attacks can be carried out in a matter of minutes, causing significant damage before any countermeasures can be deployed. This rapid execution leaves organizations with little time to react, highlighting the need for real-time threat detection and response systems.
Moreover, the use of AI in phishing attacks has added a new layer of complexity. Phishing emails generated by AI can mimic human writing styles, making them indistinguishable from legitimate communications. This sophistication increases the likelihood of unsuspecting individuals falling victim to these scams. Organizations must therefore invest in advanced AI-driven security solutions that can detect and mitigate such threats.
A new variant of the Rhadamanthys information stealer malware has been identified, which now poses a further threat to cryptocurrency users by adding AI to seed phrase recognition. The bad guys behind the malware were not enough in themselves, but when added into this malware came another functionality that includes optical character recognition or OCR scans for images and seed phrase recognition-the total key information needed to access cryptocurrency wallets.
According to Recorded Future's Insikt Group, Rhadamanthys malware now can scan for seed phrase images stored inside of infected devices in order to extract this information and yet further exploitation.
So, basically this means their wallets may now get hacked through this malware because their seed phrases are stored as images and not as text.
Evolution of Rhadamanthys
First discovered in 2022, Rhadamanthys has proven to be one of the most dangerous information-stealing malware available today that works under the MaaS model. It is a type of service allowing cyber criminals to rent their malware to other cyber criminals for a subscription fee of around $250 per month. The malware lets the attackers steal really sensitive information, including system details, credentials, browser passwords, and cryptocurrency wallet data.
The malware author, known as "kingcrete," continues to publish new versions through Telegram and Jabber despite the ban on underground forums like Exploit and XSS, in which mainly users from Russia and the former Soviet Union were targeted.
The last one, Rhadamanthys 0.7.0, which was published in June 2024, is a big improvement from the structural point of view. The malware is now equipped with AI-powered recognition of cryptocurrency wallet seed phrases by image. This has made the malware look like a very effective tool in the hands of hackers. Client and server-side frameworks were fully rewritten, making them fast and stable. Additionally, the malware now has the strength of 30 wallet-cracking algorithms and enhanced capabilities of extracting information from PDF and saved phrases.
Rhadamanthys also has a plugin system allowing it to further enhance its operations through keylogging ability, cryptocurrency clipping ability- wallet address alteration, and reverse proxy setups. The foregoing tools make it flexible for hackers to snoop for secrets in a stealthy manner.
Higher Risks for Crypto Users in Term of Security
Rhadamanthys is a crucial threat for anyone involved with cryptocurrencies, as the attackers are targeting wallet information stored in browsers, PDFs, and images. The worrying attack with AI at extracting seed phrases from images indicates attackers are always inventing ways to conquer security measures.
This evolution demands better security practices at the individual and organization level, particularly with regards to cryptocurrencies. Even for simple practices, like never storing sensitive data within an image or some other file without proper security, would have prevented this malware from happening.
Broader Implications and Related Threats
Rhdimanthys' evolving development is part of a larger evolutionary progress in malware evolution. Some other related kinds of stealer malware, such as Lumma and WhiteSnake, have also released updates recently that would further provide additional functionalities in extracting sensitive information. For instance, the Lumma stealer bypasses new security features implemented in newly designed browsers, whereas WhiteSnake stealer has been updated to obtain credit card information stored within web browsers.
These persistent updates on stealer malware are a reflection of the fact that cyber threats are becoming more mature. Also, other attacks, such as the ClickFix campaign, are deceiving users into running malicious code masqueraded as CAPTCHA verification systems.
With cybercrime operatives becoming more sophisticated and their tools being perfected day by day, there has never been such a challenge for online security. The user needs to be on the alert while getting to know what threats have risen in cyberspace to prevent misuse of personal and financial data.
OpenAI has admitted that developing ChatGPT would not have been feasible without the use of copyrighted content to train its algorithms. It is widely known that artificial intelligence (AI) systems heavily rely on social media content for their development. In fact, AI has become an essential tool for many social media platforms.
Generative AI, which includes technologies like GPT-4, DALL-E, and other advanced machine learning models, has shown immense potential in creating content, automating tasks, and enhancing decision-making processes.
These technologies can generate human-like text, create realistic images, and even compose music, making them valuable tools across industries such as healthcare, finance, marketing, and entertainment.
However, the capabilities of generative AI also raise significant data privacy concerns. As these models require vast amounts of data to train and improve, the risk of mishandling sensitive information increases. This has led to heightened scrutiny from both regulatory bodies and the public.
Data Collection and Usage: Generative AI systems often rely on large datasets that may include personal and sensitive information. The collection, storage, and usage of this data must comply with stringent privacy regulations such as GDPR and CCPA. Organizations must ensure that data is anonymized and used ethically to prevent misuse.
Transparency and Accountability: One of the major concerns is the lack of transparency in how generative AI models operate. Users and stakeholders need to understand how their data is being used and the decisions being made by these systems. Establishing clear accountability mechanisms is crucial to build trust and ensure ethical use.
Bias and Discrimination: Generative AI models can inadvertently perpetuate biases present in the training data. This can lead to discriminatory outcomes, particularly in sensitive areas like hiring, lending, and law enforcement. Addressing these biases requires continuous monitoring and updating of the models to ensure fairness and equity.
Security Risks: The integration of generative AI into various systems can introduce new security vulnerabilities. Cyberattacks targeting AI systems can lead to data breaches, exposing sensitive information. Robust security measures and regular audits are essential to safeguard against such threats.
80% of respondents are required to complete mandatory technology ethics training, marking a 7% increase since 2022. Nearly three-quarters of IT and business professionals rank data privacy among their top three ethical concerns related to generative AI:
The AI-powered glasses are filled with a range of advanced features that improve user experience. These features include open-ear speakers, a touch panel, camera. The glasses can also play music, click images take videos, and also offer real-time info via the Meta AI assistant. These features give an idea of a future where tech is involved in our daily lives.
Meta makes most of its money from advertising, this raises concerns about how images clicked through glasses will be used by the company. Meta has a history of privacy and data security concerns, users are skeptical about how their data will be used if Mera captures the images without consent.
Another issue adding injury to this concern is Meta smart glasses introducing AI. AI has already caused controversies over its inaccurate information, its easy manipulation, and racial biases.
When users capture images or videos via smart glasses, Meta Cloud processes them with AI. Meta's website says "All photos processed with AI are stored and used to improve Meta products and will be used to train Meta’s AI with help from trained reviewers"
According to Meta, the processing analyses text, objects, and other contents of the image, and any info collected is used under Meta's Privacy Policy. In simple terms, images sent to clouds can be used to train Meta's AI, a potential for misuse.
The evolving tech like smart glasses has had a major impact on how we script our lives, but it has also sparked debates around privacy and user surveillance.
For instance, people in Canada can be photographed publically without their consent, but if the purpose is commercial, suitable restrictions are applied to prevent harm or distress.
Meta has released guidelines to encourage users to exercise caution and respect rights of the others while wearing the glasses. The guidelines suggest giving a formal announcement if you want to use the camera for live streaming and turning off the device when entering a private place.
Meta's reliability on user behavior to assure privacy standards is not enough to combat the concerns around surveillance, consent, and data misuse. Meta's history of privacy battles and its data-driven business model raise questions about whether the current measures can uphold privacy in the evolving digital landscape.
These underground markets that deal with malicious large language models (LLMs) are called Mallas. This blog dives into the details of this dark industry and discusses the impact of these illicit LLMs on cybersecurity.
LLMs, like OpenAI' GPT-4 have shown fine results in natural language processing, bringing applications like chatbots for content generation. However, the same tech that supports these useful apps can be misused for suspicious activities.
Recently, researchers from Indian University Bloomington found 212 malicious LLMs on underground marketplaces between April and September last year. One of the models "WormGPT" made around $28,000 in just two months, revealing a trend among threat actors misusing AI and a rising demand for these harmful tools.
Various LLMs in the market were uncensored and built using open-source standards, few were jailbroken commercial models. Threat actors used Mallas to write phishing emails, build malware, and exploit zero days.
Tech giants working in the AI models industry have built measures to protect against jailbreaking and detecting malicious attempts. But threat actors have also found ways to jump the guardrails and trick AI models like Google Meta, OpenAI, and Anthropic into providing malicious info.
Experts found two uncensored LLMs: DarkGPT, which costs 78 cents per 50 messages, and Escape GPT, a subscription model that charges $64.98 a month. Both models generate harmful code that antivirus tools fail to detect two-thirds of the time. Another model "WolfGPT" costs $150, and allows users to write phishing emails that can escape most spam detectors.
The research findings suggest all harmful AI models could make malware, and 41.5% could create phishing emails. These models were built upon OpenAI's GPT-3.5 and GPT-4, Claude Instant, Claude-2-100k, and Pygmalion 13B.
To fight these threats, experts have suggested a dataset of prompts used to make malware and escape safety features. AI companies should release models with default censorship settings and allow access to illicit models only for research purposes.
Ransomware continues to be a critical threat to businesses worldwide, with a staggering 83% of organisations reporting they experienced at least one ransomware attack in the last year. Alarmingly, almost half of those affected (46%) faced four or more attacks, and 14% encountered ten or more. These attacks, which involve malicious software encrypting valuable data until a ransom is paid, are causing serious disruptions. According to recent research by Onapsis, 61% of organisations impacted by ransomware faced downtime of at least 24 hours, highlighting the critical nature of these incidents. The downtime can cripple operations, leading to financial losses and operational challenges.
ERP Systems Becoming a Prime Target
A key finding from the research reveals that 89% of organisations affected by ransomware reported that their Enterprise Resource Planning (ERP) systems were compromised. ERP systems, which manage vital business functions such as accounting, supply chain management, and human resources, have become attractive targets for cybercriminals. These systems are business-critical, and the increasing frequency of attacks on them underscores the need for dedicated security solutions. In fact, 93% of respondents agreed that securing ERP applications should be a top priority, emphasising the urgency of investing in ERP-specific cybersecurity measures.
AI-Enabled Threats Amplify Concerns
There are growing concerns about the role of artificial intelligence (AI) in amplifying cyber threats. Gartner’s 2024 risk report highlighted AI-enhanced attacks as a top concern for businesses. As attackers leverage AI to craft more sophisticated and damaging threats, the risk to systems like ERP is only expected to increase. Mariano Nunez, CEO of Onapsis, pointed out that ransomware groups are increasingly focusing on disrupting ERP systems because of the immense leverage they gain from causing downtime, which can cost organisations millions of dollars per hour.
How Organisations Are Responding to Ransomware
In response to these rising threats, many organisations have been forced to reconsider their cybersecurity strategies. According to the research, 96% of businesses have adjusted their security approaches as a direct result of ransomware attacks. These adjustments have taken various forms: 57% of companies invested in new security solutions, 54% ramped up employee training on cybersecurity, and 53% added more cybersecurity staff internally to strengthen their defences. Additionally, 36% sought external help by hiring threat research teams to stay ahead of potential risks.
Ransom Demands and Communication with Attackers
When it comes to handling ransom demands, the approach varies across organisations. The study revealed that 69% of respondents communicated with the attackers behind the ransomware incidents. However, when it comes to paying the ransom, businesses are divided: 34% pay every time, 21% pay occasionally, and 45% refuse to pay at all. For those that do pay, the process often involves working with third-party experts like ransomware brokers—83% of organisations that paid a ransom sought help from such intermediaries to facilitate negotiations.
The prevalence of ransomware has forced organisations to acknowledge that their traditional security measures may no longer suffice. The combination of frequent attacks, the targeting of critical ERP systems, and the emerging threat of AI-enhanced attacks calls for a more proactive and specialised approach to cybersecurity. Businesses are investing heavily in solutions and expertise to mitigate the risks, but with ransomware attacks continuing to evolve, ongoing vigilance and adaptation will be key to safeguarding digital assets in the years ahead.
AI technologies have the potential to revolutionise various sectors, from healthcare and finance to transportation and education. However, with great power comes great responsibility. The misuse or unintended consequences of AI can lead to significant ethical, legal, and social challenges. Issues such as bias in AI algorithms, data privacy concerns, and the potential for job displacement are just a few of the risks associated with unchecked AI development.
Australia’s proposed guardrails are designed to address these concerns by establishing a clear regulatory framework that promotes transparency, accountability, and ethical AI practices. These guardrails are not just about mitigating risks but also about fostering public trust and providing businesses with the regulatory certainty they need to innovate responsibly.
Accountability Processes: Organizations must establish clear accountability mechanisms to ensure that AI systems are used responsibly. This includes defining roles and responsibilities for AI governance and oversight.
Risk Management: Implementing comprehensive risk management strategies is crucial. This involves identifying, assessing, and mitigating potential risks associated with AI applications.
Data Protection: Ensuring the privacy and security of data used in AI systems is paramount. Organizations must adopt robust data protection measures to prevent unauthorized access and misuse.
Human Oversight: AI systems should not operate in isolation. Human oversight is essential to monitor AI decisions and intervene when necessary to prevent harm.
Transparency: Transparency in AI operations is vital for building public trust. Organizations should provide clear and understandable information about how AI systems work and the decisions they make.
Bias Mitigation: Addressing and mitigating bias in AI algorithms is critical to ensure fairness and prevent discrimination. This involves regular audits and updates to AI models to eliminate biases.
Ethical Standards: Adhering to ethical standards in AI development and deployment is non-negotiable. Organizations must ensure that their AI practices align with societal values and ethical principles.
Public Engagement: Engaging with the public and stakeholders is essential for understanding societal concerns and expectations regarding AI. This helps in shaping AI policies that are inclusive and reflective of public interests.
Regulatory Compliance: Organizations must comply with existing laws and regulations related to AI. This includes adhering to industry-specific standards and guidelines.
Continuous Monitoring: AI systems should be continuously monitored and evaluated to ensure they operate as intended and do not pose unforeseen risks.
The ASA’s primary objective is to foster collaboration and integration among decentralized AI systems. By merging their respective tokens—AGIX (SingularityNET), OCEAN (Ocean Protocol), and FET (Fetch.ai)—into a single token called ASI, the alliance seeks to streamline operations and enhance interoperability. This unified token is designed to facilitate seamless interactions between different AI platforms, thereby accelerating the development and deployment of advanced AI solutions.
Decentralized AI represents a paradigm shift from traditional, centralized AI models. In a decentralized framework, AI systems are distributed across a network of nodes, ensuring greater transparency, security, and resilience. This approach mitigates the risks associated with central points of failure and enhances the robustness of AI applications.
The ASA’s initiative aligns with the broader trend towards decentralization in the tech industry. By leveraging blockchain technology, the alliance aims to create a trustless environment where AI agents can interact and collaborate without the need for intermediaries. This not only reduces operational costs but also fosters innovation by enabling a more open and inclusive ecosystem.
The introduction of the ASI token is a pivotal aspect of the ASA’s strategy. This unified token serves as the backbone of the alliance’s decentralized AI ecosystem, facilitating transactions and interactions between different AI platforms. The ASI token is designed to be highly versatile, supporting a wide range of use cases, from data sharing and AI model training to decentralized finance (DeFi) applications.
One of the most intriguing applications of the ASI token is in the gambling industry. The integration of AI and blockchain technology has the potential to revolutionize online gambling by enhancing transparency, fairness, and security. AI algorithms can be used to analyze vast amounts of data, providing insights that can improve the user experience and optimize betting strategies. Meanwhile, blockchain technology ensures that all transactions are immutable and verifiable, reducing the risk of fraud and manipulation.
The gambling industry stands to benefit significantly from the advancements brought about by the ASA. By leveraging AI and blockchain technology, online gambling platforms can offer a more secure and transparent environment for users. AI-driven analytics can provide personalized recommendations and insights, enhancing the overall user experience. Additionally, the use of blockchain technology ensures that all transactions are recorded on a public ledger, providing an added layer of security and trust.
The ASI token can also facilitate seamless transactions within the gambling ecosystem. Users can utilize the token to place bets, participate in games, and access various services offered by online gambling platforms. The interoperability of the ASI token across different AI platforms further enhances its utility, making it a valuable asset for users and developers alike.
India is experiencing a rise in cyberattacks, particularly targeting its key sectors such as finance, government, manufacturing, and healthcare. This increase has prompted the Reserve Bank of India (RBI) to urge banks and financial institutions to strengthen their cybersecurity measures.
As India continues to digitise its infrastructure, it has become more vulnerable to cyberattacks. Earlier this year, hackers stole and leaked 7.5 million records from boAt, a leading Indian company that makes wireless audio and wearable devices. This is just one example of how cybercriminals are targeting Indian businesses and institutions.
The RBI has expressed concern about the growing risks in the financial sector due to rapid digitization. In 2023 alone, India’s national cybersecurity team, CERT-In, handled about 16 million cyber incidents, a massive increase from just 53,000 incidents in 2017. Most banks and non-banking financial companies (NBFCs) now see cybersecurity as a major challenge as they move towards digital technology. The RBI’s report highlights that the speed at which information and rumours can spread digitally could threaten financial stability. Cybercriminals are increasingly focusing on financial institutions rather than individual customers.
The public sector, including government agencies, has also seen a dramatic rise in cyberattacks. Many organisations report that these attacks have increased by at least 50%. Earlier this year, a hacking group targeted government agencies and energy companies using a type of malware known as HackBrowserData. Additionally, countries like Pakistan and China have been intensifying their cyberattacks on Indian organisations, with operations like the recent Cosmic Leopard campaign.
According to a report by Cloudflare, 83% of organisations in India experienced at least one cybersecurity incident in the last year, placing India among the top countries in Asia facing such threats. Globally, India is the fifth most breached nation, bringing attention to the bigger picture which screams for stronger cybersecurity measures.
Indian companies are most worried about threats related to cloud computing, connected devices, and software vulnerabilities. The adoption of new technologies like artificial intelligence (AI) and cloud computing, combined with the shift to remote work, has accelerated digital transformation, but it also increases the need for stronger security measures.
Manu Dwivedi, a cybersecurity expert from PwC India, points out that AI-powered phishing and sophisticated social engineering techniques have made ransomware a top concern for organisations. As more companies use cloud services and open-source software, the risk of cyberattacks grows. Dwivedi also stresses the importance of protecting against insider threats, which requires a mix of strategy, culture, training, and governance.
AI is playing a growing role in both defending against and enabling cyberattacks. While AI has the potential to improve security, it also introduces new risks. Cybercriminals are beginning to use AI to create more advanced malware that can avoid detection. Dwivedi warns that as AI continues to evolve, it may become harder to track how these tools are being misused by attackers.
Partha Gopalakrishnan, founder of PG Advisors, emphasises the need for India to update its cybersecurity laws. The current law, the Information Technology Act of 2000, is outdated and does not fully address today’s digital threats. Gopalakrishnan also stressed upon the growing demand for AI skills in India, suggesting that businesses should focus on training in both AI and cybersecurity to close the skills gap. He warns that as AI becomes more accessible, it could empower a wider range of people to carry out sophisticated cyberattacks.
India’s digital growth presents great opportunities, but it also comes with strenuous challenges. It’s crucial for Indian businesses and government agencies to develop comprehensive cybersecurity strategies and stay vigilant.
Cryptocurrencies, with their promise of high returns and decentralized nature, have become a lucrative target for scammers. These scams range from fake initial coin offerings (ICOs) and Ponzi schemes to phishing attacks and fraudulent exchanges. The anonymity and lack of regulation in the crypto space make it an attractive playground for cybercriminals.
ASIC has been vigilant in identifying and shutting down these scams. Over the past year, the regulator has taken down more than 600 crypto-related scams, reflecting the scale of the problem. However, the battle is far from over.
Since April, ASIC has reported a monthly decline in the number of crypto scams. This trend is a positive indicator of the effectiveness of the regulator’s efforts and increased public awareness. Educational campaigns and stricter regulations have played a significant role in this decline. Investors are becoming more cautious and better informed about the risks associated with crypto investments.
Despite the decline, ASIC warns that the threat of crypto scams remains significant. One of the emerging concerns is the use of artificial intelligence (AI) by scammers. AI-enhanced scams are more sophisticated and harder to detect. These scams can create realistic fake identities, automate phishing attacks, and even manipulate market trends to deceive investors.
AI tools can generate convincing fake websites, social media profiles, and communication that can easily trick even the most cautious investors. The use of AI in scams represents a new frontier in cybercrime, requiring regulators and consumers to stay one step ahead.
ASIC continues to adapt its strategies to combat the evolving nature of crypto scams. The regulator collaborates with international bodies, law enforcement agencies, and tech companies to share information and develop new tools for detecting and preventing scams. Public awareness campaigns remain a cornerstone of ASIC’s strategy, educating investors on how to identify and avoid scams.