#FactCheck - AI-Cloned Audio in Viral Anup Soni Video Promoting Betting Channel Revealed as Fake

Introduction

The use of digital information and communication technologies for healthcare access has been on the rise in recent times. Mental health care is increasingly being provided through online platforms by remote practitioners, and even by AI-powered chatbots, which use natural language processing (NLP) and machine learning (ML) processes to simulate conversations between the platform and a user. Thus, AI chatbots can provide mental health support from the comfort of the home, at any time of the day, via a mobile phone.  While this has great potential to enhance the mental health care ecosystem, such chatbots can present technical and ethical challenges as well.

Background

According to the WHO’s World Mental Health Report of 2022, every 1 in 8 people globally is estimated to be suffering from some form of mental health disorder. The need for mental health services worldwide is high but the supply of a care ecosystem is inadequate both in terms of availability and quality. In India, it is estimated that there are only 0.75 psychiatrists per 100,000 patients and only 30% of the mental health patients get help. Considering the slow thawing of social stigma regarding mental health, especially among younger demographics and support services being confined to urban Indian centres, the demand for a telehealth market is only projected to grow. This paves the way for, among other tools, AI-powered chatbots to fill the gap in providing quick, relatively inexpensive, and easy access to mental health counseling services.

Challenges

Users who seek mental health support are already vulnerable, and AI-induced oversight can exacerbate distress due to some of the following reasons: 

1. Inaccuracy: Apart from AI’s tendency to hallucinate data, chatbots may simply provide incorrect or harmful advice since they may be trained on data that is not representative of the specific physiological and psychological propensities of various demographics. 
2. Non-Contextual Learning: The efficacy of mental health counseling often relies on rapport-building between the service provider and client, relying on circumstantial and contextual factors. Machine learning models may struggle with understanding interpersonal or social cues, making their responses over-generalised. 
3. Reinforcement of Unhelpful Behaviors: In some cases, AI chatbots, if poorly designed, have the potential to reinforce unhealthy thought patterns. This is especially true for complex conditions such as OCD, treatment for which requires highly specific therapeutic interventions. 
4. False Reassurance: Relying solely on chatbots for counseling may create a partial sense of safety, thereby discouraging users from approaching professional mental health support services. This could reinforce unhelpful behaviours and exacerbate the condition. 
5. Sensitive Data Vulnerabilities: Health data is sensitive personal information. Chatbot service providers will need to clarify how health data is stored, processed, shared, and used. Without strong data protection and transparency standards, users are exposed to further risks to their well-being. 

Way Forward

1. Addressing Therapeutic Misconception: A lack of understanding of the purpose and capabilities of such chatbots, in terms of care expectations and treatments they can offer, can jeopardize user health. Platforms providing such services should be mandated to lay disclaimers about the limitations of the therapeutic relationship between the platform and its users in a manner that is easy to understand. 
2. Improved Algorithm Design: Training data for these models must undertake regular updates and audits to enhance their accuracy, incorporate contextual socio-cultural factors for profile analysis, and use feedback loops from customers and mental health professionals. 
3. Human Oversight: Models of therapy where AI chatbots are used to supplement treatment instead of replacing human intervention can be explored. Such platforms must also provide escalation mechanisms in cases where human-intervention is sought or required. 

Conclusion

It is important to recognize that so far, there is no substitute for professional mental health services. Chatbots can help users gain awareness of their mental health condition and play an educational role in this regard, nudging them in the right direction, and provide assistance to both the practitioner and the client/patient. However, relying on this option to fill gaps in mental health services is not enough. Addressing this growing —and arguably already critical— global health crisis requires dedicated public funding to ensure comprehensive mental health support for all. 

Sources 

• https://www.who.int/news/item/17-06-2022-who-highlights-urgent-need-to-transform-mental-health-and-mental-health-care 
• https://health.economictimes.indiatimes.com/news/industry/mental-healthcare-in-india-building-a-strong-ecosystem-for-a-sound-mind/105395767#:~:text=Indian%20mental%20health%20market%20is,access%20to%20better%20quality%20services. 
• https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2023.1278186/full 

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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

Recently the attackers employed the CVE-2017-0199 vulnerability in Microsoft Office to deliver a fileless form of the Remcos RAT. The Remcos RAT makes the attacker have full control of the systems that have been infected by this malware. This research will give a detailed technical description of the identified vulnerability, attack vector, and tactics together with the practical steps to counter the identified risks.

The Targeted Malware: Remcos RAT

Remcos RAT (Remote Control & Surveillance) is a commercially available remote access tool designed for legitimate administrative use. However, it has been widely adopted by cybercriminals for its stealth and extensive control capabilities, enabling:

• System control and monitoring
• Keylogging
• Data exfiltration
• Execution of arbitrary commands

The fileless variant utilised in this campaign makes detection even more challenging by running entirely in system memory, leaving minimal forensic traces.

Attack Vector: Phishing with Malicious Excel Attachments

The phishing email will be sent which appears as legitimate business communication, such as a purchase order or invoice. This email contains an Excel attachment that is weaponized to exploit the CVE-2017-0199 vulnerability.

Technical Analysis: CVE-2017-0199 Exploitation

Vulnerability Assessment

• CVE-2017-0199 is a Remote Code Execution (RCE) vulnerability in Microsoft Office which uses Object Linking and Embedding (OLE) objects.
• Affected Components:some text
  • Microsoft Word
  • Microsoft Excel
  • WordPad
• CVSS Score: 7.8 (High Severity)

Mechanism of Exploitation

The vulnerability enables attackers to craft a malicious document when opened, it fetches and executes an external payload via an HTML Application (HTA) file. The execution process occurs without requiring user interaction beyond opening the document.

Detailed Exploitation Steps

1. Phishing Email and Malicious Document some text
   • The email contains an Excel file designed to make use of CVE-2017-0199.
   • When the email gets opened, the document automatically connects to a remote server (e.g., 192.3.220[.]22) to download an HTA file (cookienetbookinetcache.hta).
2. Execution via mshta.exe some text
   • The downloaded HTA file is executed using mshta.exe, a legitimate Windows process for running HTML Applications.
   • This execution is seamless and does not prompt the user, making the attack stealthy.
3. Multi-Layer Obfuscation some text
   • The HTA file is wrapped in several layers of scripting, including: some text
     • JavaScript
     • VBScript
     • PowerShell
   • This obfuscation helps evade static analysis by traditional antivirus solutions.
4. Fileless Payload Deployment some text
   • The downloaded executable leverages process hollowing to inject malicious code into legitimate system processes.
   • The Remcos RAT payload is loaded directly into memory, avoiding the creation of files on disk.

Fileless Malware Techniques

1. Process Hollowing
The attack replaces the memory of a legitimate process (e.g., explorer.exe) with the malicious Remcos RAT payload. This allows the malware to:

• Evade detection by blending into normal system activity.
• Run with the privileges of the hijacked process.

2. Anti-Analysis Techniques

• Anti-Debugging: Detects the presence of debugging tools and terminates malicious processes if found.
• Anti-VM and Sandbox Evasion: Ensures execution only on real systems to avoid detection during security analysis.

3. In-Memory Execution

• By running entirely in system memory, the malware avoids leaving artifacts on the disk, making forensic analysis and detection more challenging.

Capabilities of Remcos RAT

Once deployed, Remcos RAT provides attackers with a comprehensive suite of functionalities, including:

• Data Exfiltration: some text
  • Stealing system information, files, and credentials.
• Remote Execution: some text
  • Running arbitrary commands, scripts, and additional payloads.
• Surveillance: some text
  • Enabling the camera and microphone.
  • Capturing screen activity and clipboard contents.
• System Manipulation: some text
  • Modifying Windows Registry entries.
  • Controlling system services and processes.
  • Disabling user input devices (keyboard and mouse).

Advanced Phishing Techniques in Parallel Campaigns

1. DocuSign Abuse
Attackers exploit legitimate DocuSign APIs to create authentic-looking phishing invoices. These invoices can trick users into authorising payments or signing malicious documents, bypassing traditional email security systems.

2. ZIP File Concatenation
By appending multiple ZIP archives into a single file, attackers exploit inconsistencies in how different tools handle these files. This allows them to embed malware that evades detection by certain archive managers.

Broader Implications of Fileless Malware

Fileless malware like Remcos RAT poses significant challenges:

• Detection Difficulties: Traditional signature-based antivirus systems struggle to detect fileless malware, as there are no static files to scan.
• Forensic Limitations: The lack of disk artifacts complicates post-incident analysis, making it harder to trace the attack's origin and scope.
• Increased Sophistication: These campaigns demonstrate the growing technical prowess of cybercriminals, leveraging legitimate tools and services for malicious purposes.

Mitigation Strategies

1. Patch Management some text
   • It is important to regularly update software to address known vulnerabilities like CVE-2017-0199. Microsoft released a patch for this vulnerability in April 2017.
2. Advanced Email Security some text
   • It is important to implement email filtering solutions that can detect phishing attempts, even those using legitimate services like DocuSign.
3. Endpoint Detection and Response (EDR)some text
   • Always use EDR solutions to monitor for suspicious behavior, such as unauthorized use of mshta.exe or process hollowing.
4. User Awareness and Training some text
   • Educate users about phishing techniques and the risks of opening unexpected attachments.
5. Behavioral Analysis some text
   • Deploy security solutions capable of detecting anomalous activity, even if no malicious files are present.

Conclusion

The attack via CVE-2017-0199 further led to the injection of a new fileless variant of Remcos RAT, proving how threats are getting more and more sophisticated. Thanks to the improved obfuscation and the lack of files, the attackers eliminate all traditional antiviral protection and gain full control over the infected computers. It is real and organisations have to make sure that they apply patches on time, that they build better technologies for detection and that the users themselves are more wary of the threats.

References

• Fortinet FortiGuard Labs: Analysis by Xiaopeng Zhang
• Perception Point: Research on ZIP File Concatenation
• Wallarm: DocuSign Phishing Analysis
• Microsoft Security Advisory: CVE-2017-0199

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