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Executive Summary:

Given that AI technologies are evolving at a fast pace in 2024, an AI-oriented phishing attack on a large Indian financial institution illustrated the threats. The documentation of the attack specifics involves the identification of attack techniques, ramifications to the institution, intervention conducted, and resultant effects. The case study also turns to the challenges connected with the development of better protection and sensibilisation of automatized threats. 

Introduction

Due to the advancement in AI technology, its uses in cybercrimes across the world have emerged significant in financial institutions. In this report a serious incident that happened in early 2024 is analysed, according to which a leading Indian bank was hit by a highly complex, highly intelligent AI-supported phishing operation. Attack made use of AI’s innate characteristic of data analysis and data persuasion which led into a severe compromise of the bank’s internal structures.

Background

The chosen financial institution, one of the largest banks in India, had a good background regarding the extremity of its cybersecurity policies. However, these global cyberattacks opened up new threats that AI-based methods posed that earlier forms of security could not entirely counter efficiently. The attackers concentrated on the top managers of the bank because it is evident that controlling such persons gives the option of entering the inner systems as well as financial information. 

Attack Execution

The attackers utilised AI in sending the messages that were an exact look alike of internal messages sent between employees. From Facebook and Twitter content, blog entries, and lastly, LinkedIn connection history and email tenor of the bank’s executives, the AI used to create these emails was highly specific. Some of these emails possessed official formatting, specific internal language, and the CEO’s writing; this made them very realistic. 

 It also used that link in phishing emails that led the users to a pseudo internal portal in an attempt to obtain the login credentials. Due to sophistication, the targeted individuals thought the received emails were genuine, and entered their log in details easily to the bank’s network, thus allowing the attackers access. 

Impact

It caused quite an impact to the bank in every aspect. Numerous executives of the company lost their passwords to the fake emails and compromised several financial databases with information from customer accounts and transactions. The break-in permitted the criminals to cease a number of the financial’s internet services hence disrupting its functions and those of its customers for a number of days. 

 They also suffered a devastating blow to their customer trust because the breach revealed the bank’s weakness against contemporary cyber threats. Apart from managing the immediate operations which dealt with mitigating the breach, the financial institution was also toppling a long-term reputational hit. 

Technical Analysis and Findings

1. The AI techniques that are used in generation of the phishing emails are as follows: 

•  The attack used powerful NLP technology, which was most probably developed using the large-scaled transformer, such as GPT (Generative Pre-trained Transformer). Since these models are learned from large data samples they used the examples of the conversation pieces from social networks, emails and PC language to create quite credible emails. 

 Key Technical Features: 

•  Contextual Understanding: The AI was able to take into account the nature of prior interactions and thus write follow up emails that were perfectly in line with prior discourse. 
•  Style Mimicry: The AI replicated the writing of the CEO given the emails of the CEO and then extrapolated from the data given such elements as the tone, the language, and the format of the signature line. 
•  Adaptive Learning: The AI actively adapted from the mistakes, and feedback to tweak the generated emails for other tries and this made it difficult to detect. 

2. Sophisticated Spear-Phishing Techniques

Unlike ordinary phishing scams, this attack was phishing using spear-phishing where the attackers would directly target specific people using emails. The AI used social engineering techniques that significantly increased the chances of certain individuals replying to certain emails based on algorithms which machine learning furnished. 

 Key Technical Features: 

•  Targeted Data Harvesting: Cyborgs found out the employees of the organisation and targeted messages via the public profiles and messengers were scraped. 
•  Behavioural Analysis: The latest behaviour pattern concerning the users of the social networking sites and other online platforms were used by the AI to forecast the courses of action expected to be taken by the end users such as clicking on the links or opening of the attachments. 
•  Real-Time Adjustments: These are times when it was determined that the response to the phishing email was necessary and the use of AI adjusted the consequent emails’ timing and content. 

3. Advanced Evasion Techniques

The attackers were able to pull off this attack by leveraging AI in their evasion from the normal filters placed in emails. These techniques therefore entailed a modification of the contents of the emails in a manner that would not be easily detected by the spam filters while at the same time preserving the content of the message. 

Key Technical Features: 

•  Dynamic Content Alteration: The AI merely changed the different aspects of the email message slightly to develop several versions of the phishing email that would compromise different algorithms. 
•  Polymorphic Attacks: In this case, polymorphic code was used in the phishing attack which implies that the actual payloads of the links changed frequently, which means that it was difficult for the AV tools to block them as they were perceived as threats. 
•  Phantom Domains: Another tactic employed was that of using AI in generating and disseminating phantom domains, that are actual web sites that appear to be legitimate but are in fact short lived specially created for this phishing attack, adding to the difficulty of detection. 

4. Exploitation of Human Vulnerabilities

This kind of attack’s success was not only in AI but also in the vulnerability of people, trust in familiar language and the tendency to obey authorities. 

Key Technical Features: 

•  Social Engineering: As for the second factor, AI determined specific psychological principles that should be used in order to maximise the chance of the targeted recipients opening the phishing emails, namely the principles of urgency and familiarity. 
•  Multi-Layered Deception: The AI was successfully able to have a two tiered approach of the emails being sent as once the targeted individuals opened the first mail, later the second one by pretext of being a follow up by a genuine company/personality. 

Response

On sighting the breach, the bank’s cybersecurity personnel spring into action to try and limit the fallout. They reported the matter to the Indian Computer Emergency Response Team (CERT-In) to find who originated the attack and how to block any other intrusion. The bank also immediately started taking measures to strengthen its security a bit further, for instance, in filtering emails, and increasing the authentication procedures. 

 Knowing the risks, the bank realised that actions should be taken in order to enhance the cybersecurity level and implement a new wide-scale cybersecurity awareness program. This programme consisted of increasing the awareness of employees about possible AI-phishing in the organisation’s info space and the necessity of checking the sender’s identity beforehand.

Outcome

Despite the fact and evidence that this bank was able to regain its functionality after the attack without critical impacts with regards to its operations, the following issues were raised. Some of the losses that the financial institution reported include losses in form of compensation of the affected customers and costs of implementing measures to enhance the financial institution’s cybersecurity. However, the principle of the incident was significantly critical of the bank as customers and shareholders began to doubt the organisation’s capacity to safeguard information in the modern digital era of advanced artificial intelligence cyber threats. 

 This case depicts the importance for the financial firms to align their security plan in a way that fights the new security threats. The attack is also a message to other organisations in that they are not immune from such analysis attacks with AI and should take proper measures against such threats.

Conclusion

The recent AI-phishing attack on an Indian bank in 2024 is one of the indicators of potential modern attackers’ capabilities. Since the AI technology is still progressing, so are the advances of the cyberattacks. Financial institutions and several other organisations can only go as far as adopting adequate AI-aware cybersecurity solutions for their systems and data. 

 Moreover, this case raises awareness of how important it is to train the employees to be properly prepared to avoid the successful cyberattacks. The organisation’s cybersecurity awareness and secure employee behaviours, as well as practices that enable them to understand and report any likely artificial intelligence offences, helps the organisation to minimise risks from any AI attack.

Recommendations

1. Enhanced AI-Based Defences: Financial institutions should employ AI-driven detection and response products that are capable of mitigating AI-operation-based cyber threats in real-time. 
2.  Employee Training Programs: CYBER SECURITY: All employees should undergo frequent cybersecurity awareness training; here they should be trained on how to identify AI-populated phishing. 
3.  Stricter Authentication Protocols: For more specific accounts, ID and other security procedures should be tight in order to get into sensitive ones. 
4.  Collaboration with CERT-In: Continued engagement and coordination with authorities such as the Indian Computer Emergency Response Team (CERT-In) and other equivalents to constantly monitor new threats and valid recommendations. 
5.  Public Communication Strategies: It is also important to establish effective communication plans to address the customers of the organisations and ensure that they remain trusted even when an organisation is facing a cyber threat. 

Through implementing these, financial institutions have an opportunity for being ready with new threats that come with AI and cyber terrorism on essential financial assets in today’s complex IT environments.

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Executive Summary:

A widely circulated social media post claims that the Government of India has reportedly opened an account—Army Welfare Fund Battle Casualty—at Canara Bank to support the modernization of the Indian Army and assist injured or martyred soldiers. Citizens can voluntarily contribute starting from ₹1, with no upper limit. The fund is said to have been launched based on a suggestion by actor Akshay Kumar, which was later acknowledged by the Prime Minister of India through Mann Ki Baat and social media platforms. However, the fact is that no such decision has been taken by the cabinet recently, and no such decision has been officially announced.

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Claim:

A viral social media post claims that the Government of India has launched a new initiative aimed at modernizing the Indian Army and supporting battle casualties through public donations. According to the post, a special bank account has been created to enable citizens to contribute directly toward the procurement of arms and equipment for the armed forces.

It further states that this initiative was introduced following a Cabinet decision and was inspired by a suggestion from Bollywood actor Akshay Kumar, which was reportedly acknowledged by the Prime Minister during his Mann Ki Baat address.

The post encourages individuals to donate any amount starting from ₹1, with no upper limit, and estimates that widespread public participation could generate up to ₹36,000 crore annually to support the armed forces. It also lists two bank accounts—one at Canara Bank (Account No: 90552010165915) and another at State Bank of India (Account No: 40650628094)—allegedly designated for the "Armed Forces Battle Casualties Welfare Fund."

The statement said,” The government established a range of welfare schemes for soldiers killed or disabled while undertaking military operations in recent combat. In 2020, the government established the 'Armed Forces Battle Casualty Welfare Fund (AFBCWF)', which is used to provide immediate financial assistance to families of soldiers, sailors and airmen who lose their lives or sustain grievous injury as a result of active military service.” 

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We also found a similar post from the past, which can be seen here.
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Fact Check:

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The Press Information Bureau (PIB) have responded to the viral post stating that it is misleading, and the Government has not launched any message inviting public donations towards the modernisation of the Indian Army or for purchasing Weapons for the army. The only known official initiative by the Ministry of Defence is the "Armed Forces Battle Casualties Welfare Fund", which is an initiative set up to support the families of our soldiers who have been marshalled or grievously disabled in the line of duty, not for buying military equipment.

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In addition, the bank account details mentioned in the Viral post are false, and donations and charitable donations submitted to the account have been dishonoured. 

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The other false claim says that actor Akshay Kumar is promoting or heading this message-there is no official/disclosure record or announcement related to him leading or sponsoring this project. Having said that in 2017, Akshay Kumar encouraged public contributions of just one rupee per month to support the armed forces, through a web portal called “Bharat Ke Veer”. The platform was developed in partnership with the Ministry of Home Affairs

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Citizens have to rely on only official government sources and ignore misleading messages on such social media platforms.

Conclusion:

The viral social media post suggesting that the Government of India has initiated a donation drive for the modernisation of the Indian Army and the purchase of weapons is misleading and inaccurate. According to the Press Information Bureau (PIB), no such initiative has been launched by the government, and the bank account details provided in the post are false, with reported cases of dishonoured transactions. The only legitimate initiative is the Armed Forces Battle Casualties Welfare Fund (AFBCWF), which provides financial assistance to the families of soldiers who are martyred or seriously injured in the line of duty. While actor Akshay Kumar played a key role in launching the Bharat Ke Veer portal in 2017 to support paramilitary personnel, he has no official connection to the viral claims.

• Claim: The government has launched a public donation message to fund Army weapon purchases.
• Claimed On:  Social Media
• Fact Check: False and Misleading

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‍Brief Overview of the EU AI Act

The EU AI Act, Regulation (EU) 2024/1689, was officially published in the EU Official Journal on 12 July 2024. This landmark legislation on Artificial Intelligence (AI) will come into force just 20 days after publication, setting harmonized rules across the EU. It amends key regulations and directives to ensure a robust framework for AI technologies.  The AI Act, a set of EU rules governing AI, has been in development for two years and now, the EU AI Act enters into force across all 27 EU Member States on 1 August 2024, with certain future deadlines tied up and the enforcement of the majority of its provisions will commence on 2 August 2026. The law prohibits certain uses of AI tools, including those that threaten citizens' rights, such as biometric categorization, untargeted scraping of faces, and systems that try to read emotions are banned in the workplace and schools, as are social scoring systems. It also prohibits the use of predictive policing tools in some instances. The law takes a phased approach to implementing the EU's AI rulebook, meaning there are various deadlines between now and then as different legal provisions will start to apply.

The framework puts different obligations on AI developers, depending on use cases and perceived risk. The bulk of AI uses will not be regulated as they are considered low-risk, but a small number of potential AI  use cases are banned under the law. High-risk use cases, such as biometric uses of AI or AI used in law enforcement, employment, education, and critical infrastructure, are allowed under the law but developers of such apps face obligations in areas like data quality and anti-bias considerations. A third risk tier also applies some lighter transparency requirements for makers of tools like AI chatbots.

In case of failure to comply with the Act, the companies in the EU providing, distributing, importing, and using AI systems and GPAI models, are subject to fines of up to EUR 35 million or seven per cent of the total worldwide annual turnover, whichever is higher.

Key highlights of EU AI Act Provisions

• The AI Act classifies AI according to its risk. It prohibits Unacceptable risks such as social scoring systems and manipulative AI. The regulation mostly addresses high-risk AI systems.
• Limited-risk AI systems are subject to lighter transparency obligations and according to the act, the developers and deployers must ensure that the end-users are aware that the interaction they are having is with AI such as Chatbots and Deepfakes. The AI Act allows the free use of minimal-risk AI. This includes the majority of AI applications currently available in the EU single market like AI-enabled video games, and spam filters, but with the advancement of Gen AI changes with regards to this might be done. The majority of obligations fall on providers (developers) of high-risk AI systems that intend to place on the market or put into service high-risk AI systems in the EU, regardless of whether they are based in the EU or a third country. And also, a third-country provider where the high-risk AI system’s output is used in the EU.
• Users are natural or legal persons who deploy an AI system in a professional capacity, not affected end-users. Users (deployers) of high-risk AI systems have some obligations, though less than providers (developers). This applies to users located in the EU, and third-country users where the AI system’s output is used in the EU.
• General purpose AI or GPAI model providers must provide technical documentation, and instructions for use, comply with the Copyright Directive, and publish a summary of the content used for training. Free and open license GPAI model providers only need to comply with copyright and publish the training data summary, unless they present a systemic risk. All providers of GPAI models that present a systemic risk – open or closed – must also conduct model evaluations, and adversarial testing, and track and report serious incidents and ensure cybersecurity protections.
• The Codes of Practice will account for international approaches. It will cover but not necessarily be limited to the obligations, particularly the relevant information to include in technical documentation for authorities and downstream providers, identification of the type and nature of systemic risks and their sources, and the modalities of risk management accounting for specific challenges in addressing risks due to the way they may emerge and materialize throughout the value chain. The AI Office may invite GPAI model providers, and relevant national competent authorities to participate in drawing up the codes, while civil society, industry, academia, downstream providers and independent experts may support the process.

Application & Timeline of Act

The EU AI Act will be fully applicable 24 months after entry into force, but some parts will be applicable sooner, for instance the ban on AI systems posing unacceptable risks will apply six months after the entry into force. The Codes of Practice will apply nine months after entry into force. Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force. High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force. The expected timeline for the same is:

• August 1st, 2024: The AI Act will enter into force.
• February 2025: Prohibition of certain AI systems - Chapters I (general provisions) & II (prohibited AI systems) will apply; Prohibition of certain AI systems.
• August 2025: Chapter III Section 4 (notifying authorities), Chapter V (general purpose AI models), Chapter VII (governance), Chapter XII (confidentiality and penalties), and Article 78 (confidentiality) will apply, except for Article 101 (fines for General Purpose AI providers); Requirements for new GPAI models. 
• August 2026: The whole AI Act applies, except for Article 6(1) & corresponding obligations (one of the categories of high-risk AI systems);
•  August 2027: Article 6(1) & corresponding obligations apply.

The AI Act sets out clear definitions for the different actors involved in AI, such as the providers, deployers, importers, distributors, and product manufacturers. This means all parties involved in the development, usage, import, distribution, or manufacturing of AI systems will be held accountable. Along with this, the AI Act also applies to providers and deployers of AI systems located outside of the EU, e.g., in Switzerland, if output produced by the system is intended to be used in the EU. The Act applies to any AI system within the EU that is on the market, in service, or in use, covering both AI providers (the companies selling AI systems) and AI deployers (the organizations using those systems).

In short, the AI Act will apply to different companies across the AI distribution chain, including providers, deployers, importers, and distributors (collectively referred to as “Operators”). The EU AI Act also has extraterritorial application and can also apply to companies not established in the EU, or providers outside the EU if they -make an AI system or GPAI model available on the EU market. Even if only the output generated by the AI system is used in the EU, the Act still applies to such providers and deployers. 

CyberPeace Outlook 

The EU AI Act, approved by EU lawmakers in 2024, is a landmark legislation designed to protect citizens' health, safety, and fundamental rights from potential harm caused by AI systems. The AI Act will apply to AI systems and GPAI models. The Act creates a tiered risk categorization system with various regulations and stiff penalties for noncompliance. The Act adopts a risk-based approach to AI governance, categorizing potential risks into four tiers: unacceptable, high, limited, and low. Violations of banned systems carry the highest fine: €35 million, or 7 percent of global annual revenue. It establishes transparency requirements for general-purpose AI systems. The regulation also provides specific rules for general-purpose AI (GPAI) models and lays down more stringent requirements for GPAI models with 'high-impact capabilities' that could pose a systemic risk and have a significant impact on the internal market. For high-risk AI systems, the AI Act addresses the issues of fundamental rights impact assessment and data protection impact assessment.

The EU AI Act aims to enhance trust in AI technologies by establishing clear regulatory standards governing AI. We encourage regulatory frameworks that strive to balance the desire to foster innovation with the critical need to prevent unethical practices that may cause user harm. The legislation can be seen as strengthening the EU's position as a global leader in AI innovation and developing regulatory frameworks for emerging technologies. It sets a global benchmark for regulating AI. The companies to which the act applies will need to make sure their practices align with the same. The act may inspire other nations to develop their own legislation contributing to global AI governance. The world of AI is complex and challenging, the implementation of regulatory checks, and compliance by the concerned companies, all pose a conundrum. However, in the end, balancing innovation with ethical considerations is paramount. 

At the same hand, the tech sector welcomes regulatory progress but warns that overly-rigid regulations could stifle innovation. Hence flexibility and adaptability are key to effective AI governance. The journey towards robust AI regulation has begun in major countries, and it is important that we find the right balance between safety and innovation and also take into consideration the industry reactions.

References: 

1. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401689
2. https://www.theverge.com/2024/7/12/24197058/eu-ai-act-regulations-bans-deadline
3. https://techcrunch.com/2024/07/12/eus-ai-act-gets-published-in-blocs-official-journal-starting-clock-on-legal-deadlines/
4. https://www.wsgr.com/en/insights/eu-ai-act-to-enter-into-force-in-august.html
5. https://www.techtarget.com/searchenterpriseai/tip/Is-your-business-ready-for-the-EU-AI-Act
6. https://www.simmons-simmons.com/en/publications/clyimpowh000ouxgkw1oidakk/the-eu-ai-act-a-quick-guide

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