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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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Digitisation in Agriculture

The traditional way of doing agriculture has undergone massive digitization in recent years, whereby several agricultural processes have been linked to the Internet. This globally prevalent transformation, driven by smart technology, encompasses the use of sensors, IoT devices, and data analytics to optimize and automate labour-intensive farming practices. Smart farmers in the country and abroad now leverage real-time data to monitor soil conditions, weather patterns, and crop health, enabling precise resource management and improved yields. The integration of smart technology in agriculture not only enhances productivity but also promotes sustainable practices by reducing waste and conserving resources. As a result, the agricultural sector is becoming more efficient, resilient, and capable of meeting the growing global demand for food.

Digitisation of Food Supply Chains

There has also been an increase in the digitisation of food supply chains across the globe since it enables both suppliers and consumers to keep track of the stage of food processing from farm to table and ensures the authenticity of the food product. The latest generation of agricultural robots is being tested to minimise human intervention. It is thought that AI-run processes can mitigate labour shortage, improve warehousing and storage and make transportation more efficient by running continuous evaluations and adjusting the conditions real-time while increasing yield. The company Muddy Machines is currently trialling an autonomous asparagus-harvesting robot called Sprout that not only addresses labour shortages but also selectively harvests green asparagus, which traditionally requires careful picking. However, Chris Chavasse, co-founder of Muddy Machines, highlights that hackers and malicious actors could potentially hack into the robot's servers and prevent it from operating by driving it into a ditch or a hedge, thereby impending core crop activities like seeding and harvesting. Hacking agricultural pieces of machinery also implies damaging a farmer’s produce and in turn profitability for the season.

Case Study: Muddy Machines and Cybersecurity Risks

A cyber attack on digitised agricultural processes has a cascading impact on online food supply chains. Risks are non-exhaustive and spill over to poor protection of cargo in transit, increased manufacturing of counterfeit products, manipulation of data, poor warehousing facilities and product-specific fraud, amongst others. Additional impacts on suppliers are also seen, whereby suppliers have supplied the food products but fail to receive their payments. These cyber-threats may include malware(primarily ransomware) that accounts for 38% of attacks, Internet of Things (IoT) attacks that comprise 29%, Distributed Denial of Service (DDoS) attacks, SQL Injections, phishing attacks etc. 

Prominent Cyber Attacks and Their Impacts

Ransomware attacks are the most popular form of cyber threats to food supply chains and may include malicious contaminations, deliberate damage and destruction of tangible assets (like infrastructure) or intangible assets (like reputation and brand). In 2017, NotPetya malware disrupted the world’s largest logistics giant Maersk and destroyed all end-user devices in more than 60 countries. Interestingly, NotPetya was also linked to the malfunction of freezers connected to control systems. The attack led to these control systems being compromised, resulting in freezer failures and potential spoilage of food, highlighting the vulnerability of industrial control systems to cyber threats.

Further Case Studies

NotPetya also impacted Mondelez, the maker of Oreos but disrupting its email systems, file access and logistics for weeks. Mondelez’s insurance claim was also denied since NotPetya malware was described as a “war-like” action, falling outside the purview of the insurance coverage. In April 2021, over the Easter weekend, Bakker Logistiek, a logistics company based in the Netherlands that offers air-conditioned warehousing and food transportation for Dutch supermarkets, experienced a ransomware attack. This incident disrupted their supply chain for several days, resulting in empty shelves at Albert Heijn supermarkets, particularly for products such as packed and grated cheese. Despite the severity of the attack, the company successfully restored their operations within a week by utilizing backups. JBS, one of the world’s biggest meat processing companies, also had to pay $11 million in ransom via Bitcoin to resolve a cyber attack in the same year, whereby computer networks at JBS were hacked, temporarily shutting down their operations and endangering consumer data. The disruption threatened food supplies and risked higher food prices for consumers. Additional cascading impacts also include low food security and hindrances in processing payments at retail stores. 

Credible Threat Agents and Their Targets

Any cyber-attack is usually carried out by credible threat agents that can be classified as either internal or external threat agents. Internal threat agents may include contractors, visitors to business sites, former/current employees, and individuals who work for suppliers. External threat agents may include activists, cyber-criminals, terror cells etc. These threat agents target large organisations owing to their larger ransom-paying capacity, but may also target small companies due to their vulnerability and low experience, especially when such companies are migrating from analogous methods to digitised processes.

The Federal Bureau of Investigation warns that the food and agricultural systems are most vulnerable to cyber-security threats during critical planting and harvesting seasons. It noted an increase in cyber-attacks against six agricultural co-operatives in 2021, with ancillary core functions such as food supply and distribution being impacted. Resultantly, cyber-attacks may lead to a mass shortage of food not only meant for human consumption but also for animals.

Policy Recommendations

To safeguard against digital food supply chains, Food defence emerges as one of the top countermeasures to prevent and mitigate the effects of intentional incidents and threats to the food chain. While earlier, food defence vulnerability assessments focused on product adulteration and food fraud, including vulnerability assessments of agriculture technology now be more relevant.  

Food supply organisations must prioritise regular backups of data using air-gapped and password-protected offline copies, and ensure critical data copies are not modifiable or deletable from the main system.  For this, blockchain-based food supply chain solutions may be deployed, which are not only resilient to hacking, but also allow suppliers and even consumers to track produce. Companies like Ripe.io, Walmart Global Tech, Nestle and Wholechain deploy blockchain for food supply management since it provides overall process transparency, improves trust issues in the transactions, enables traceable and tamper-resistant records and allows accessibility and visibility of data provenance. Extensive recovery plans with multiple copies of essential data and servers in secure, physically separated locations, such as hard drives, storage devices, cloud or distributed ledgers should be adopted in addition to deploying operations plans for critical functions in case of system outages. For core processes which are not labour-intensive,  including manual operation methods may be used to reduce digital dependence. Network segmentation, updates or patches for operating systems, software, and firmware are additional steps which can be taken to secure smart agricultural technologies. 

References

1. Muddy Machines website, Accessed 26 July 2024.  https://www.muddymachines.com/ 
2. “Meat giant JBS pays $11m in ransom to resolve cyber-attack”, BBC, 10 June 2021. https://www.bbc.com/news/business-57423008 
3. Marshall, Claire & Prior, Malcolm, “Cyber security: Global food supply chain at risk from malicious hackers.”, BBC, 20 May 2022. https://www.bbc.com/news/science-environment-61336659 
4. “Ransomware Attacks on Agricultural Cooperatives Potentially Timed to Critical Seasons.”, Private Industry Notification, Federal Bureau of Investigation, 20 April  https://www.ic3.gov/Media/News/2022/220420-2.pdf. 
5. Manning, Louise & Kowalska, Aleksandra. (2023). “The threat of ransomware in the food supply chain: a challenge for food defence”, Trends in Organized Crime. https://doi.org/10.1007/s12117-023-09516-y 
6. “NotPetya: the cyberattack that shook the world”, Economic Times, 5 March 2022. https://economictimes.indiatimes.com/tech/newsletters/ettech-unwrapped/notpetya-the-cyberattack-that-shook-the-world/articleshow/89997076.cms?from=mdr 
7. Abrams, Lawrence, “Dutch supermarkets run out of cheese after ransomware attack.”, Bleeping Computer, 12 April 2021. https://www.bleepingcomputer.com/news/security/dutch-supermarkets-run-out-of-cheese-after-ransomware-attack/ 
8. Pandey, Shipra; Gunasekaran, Angappa; Kumar Singh, Rajesh & Kaushik, Anjali, “Cyber security risks in globalised supply chains: conceptual framework”, Journal of Global Operations and Strategic Sourcing, January 2020. https://www.researchgate.net/profile/Shipra-Pandey/publication/338668641_Cyber_security_risks_in_globalized_supply_chains_conceptual_framework/links/5e2678ae92851c89c9b5ac66/Cyber-security-risks-in-globalized-supply-chains-conceptual-framework.pdf 
9. Daley, Sam, “Blockchain for Food: 10 examples to know”, Builin, 22 March 2023 https://builtin.com/blockchain/food-safety-supply-chain 

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Introduction

As India moves full steam ahead towards a trillion-dollar digital economy, how user data is gathered, processed and safeguarded is under the spotlight. One of the most pervasive but least known technologies used to gather user data is the cookie. Cookies are inserted into every website and application to improve functionality, measure usage and customize content. But they also present enormous privacy threats, particularly when used without explicit user approval. 

In 2023, India passed the Digital Personal Data Protection Act (DPDP) to give strong legal protection to data privacy. Though the act does not refer to cookies by name, its language leaves no doubt as to the inclusion of any technology that gathers or processes personal information and thus cookies regulation is at the centre of digital compliance in India. This blog covers what cookies are, how international legislation, such as the GDPR, has addressed them and how India's DPDP will regulate their use.

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What Are Cookies and Why Do They Matter?

Cookies are simply small pieces of data that a website stores in the browser. They were originally designed to help websites remember useful information about users, such as your login session or what is in your shopping cart. Netscape initially built them in 1994 to make web surfing more efficient. 

Cookies exist in various types. Session cookies are volatile and are deleted when the browser is shut down, whereas persistent cookies are stored on the device to monitor users over a period of time. First-party cookies are made by the site one is visiting, while third-party cookies are from other domains, usually utilised for advertisements or analytics. Special cookies, such as secure cookies, zombie cookies and tracking cookies, differ in intent and danger. They gather information such as IP addresses, device IDs and browsing history information associated with a person, thus making it personal data per the majority of data protection regulations.

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A Brief Overview of the GDPR and Cookie Policy

The GDPR regulates how personal data can be processed in general. However, if a cookie collects personal data (like IP addresses or identifiers that can track a person), then GDPR applies as well, because it sets the rules on how that personal data may be processed, what lawful bases are required, and what rights the user has.

The ePrivacy Directive (also called the “Cookie Law”) specifically regulates how cookies and similar technologies can be used. Article 5(3) of the ePrivacy Directive says that storing or accessing information (such as cookies) on a user’s device requires prior, informed consent, unless the cookie is strictly necessary for providing the service requested by the user.

In the seminal Planet49 decision, the Court of Justice of the European Union held that pre-ticked boxes do not represent valid consent. Another prominent enforcement saw Amazon fined €35 million by France's CNIL for using tracking cookies without user consent.

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Cookies and India’s Digital Personal Data Protection Act (DPDP), 2023

India's Digital Personal Data Protection Act, 2023 does not refer to cookies specifically but its provisions necessarily come into play when cookies harvest personal data like user activity, IP addresses, or device data. According to DPDP, personal data is to be processed for legitimate purposes with the individual's consent. The consent has to be free, informed, clear and unambiguous. The individuals have to be informed of what data is collected, how it will be processed.. The Act also forbids behavioural monitoring and targeted advertising in the case of children.

The Ministry of Electronics and IT released the Business Requirements Document for Consent Management Systems (BRDCMS) in June 2025. Although it is not binding by law, it provides operational advice on cookie consent. It recommends that websites use cookie banners with "Accept," "Reject," and "Customize" choices. Users must be able to withdraw or change their consent at any moment. Multi-language handling and automatic expiry of cookie preferences are also suggested to suit accessibility and privacy requirements.

The DPDP Act and the BRDCMS together create a robust user-rights model, even in the absence of a special cookie law.

What Should Indian Websites Do?

For the purposes of staying compliant, Indian websites and online platforms need to act promptly to harmonise their use of cookies with DPDP principles. This begins with a transparent and simple cookie banner providing users with an opportunity to accept or decline non-essential cookies. Consent needs to be meaningful; coercive tactics such as cookie walls must not be employed. Websites need to classify cookies (e.g., necessary, analytics and ads) and describe each category's function in plain terms under the privacy policy. Users must be given the option to modify cookie settings anytime using a Consent Management Platform (CMP). Monitoring children or their behavioural information must be strictly off-limits.

These are not only about being compliant with the law, they're about adhering to ethical data stewardship and user trust building.

What Should Users Do?

Cookies need to be understood and controlled by users to maintain online personal privacy. Begin by reading cookie notices thoroughly and declining unnecessary cookies, particularly those associated with tracking or advertising. The majority of browsers today support blocking third-party cookies altogether or deleting them periodically.

It is also recommended to check and modify privacy settings on websites and mobile applications. It is possible to minimise surveillance with the use of browser add-ons such as ad blockers or privacy extensions. Users are also recommended not to blindly accept "accept all" in cookie notices and instead choose "customise" or "reject" where not necessary for their use.

Finally, keeping abreast of data rights under Indian law, such as the right to withdraw consent or to have data deleted, will enable people to reclaim control over their online presence.

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Conclusion

Cookies are a fundamental component of the modern web, but they raise significant concerns about individual privacy. India's DPDP Act, 2023, though not explicitly referring to cookies, contains an effective legal framework that regulates any data collection activity involving personal data, including those facilitated by cookies.

As India continues to make progress towards comprehensive rulemaking and regulation, companies need to implement privacy-first practices today. And so must the users, in an active role in their own digital lives. Collectively, compliance, transparency and awareness can build a more secure and ethical internet ecosystem where privacy is prioritised by design.

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References

• https://prsindia.org/billtrack/digital-personal-data-protection-bill-2023
• https://gdpr-info.eu/
• https://d38ibwa0xdgwxx.cloudfront.net/create-edition/7c2e2271-6ddd-4161-a46c-c53b8609c09d.pdf
• https://oag.ca.gov/privacy/ccpa
• https://www.barandbench.com/columns/cookie-management-under-the-digital-personal-data-protection-act-2023#:~:text=The%20Business%20Requirements%20Document%20for,the%20DPDP%20Act%20and%20Rules.
• https://samistilegal.in/cookies-meaning-legal-regulations-and-implications/#
• https://secureprivacy.ai/blog/india-digital-personal-data-protection-act-dpdpa-cookie-consent-requirements
• https://law.asia/cookie-use-india/‍
• https://www.cookielawinfo.com/major-gdpr-fines-2020-2021/#:~:text=4.,French%20websites%20could%20refuse%20cookies.