#FactCheck - "Viral Video Misleadingly Claims Surrender to Indian Army, Actually Shows Bangladesh Army”
Executive Summary:
A viral video has circulated on social media, wrongly showing lawbreakers surrendering to the Indian Army. However, the verification performed shows that the video is of a group surrendering to the Bangladesh Army and is not related to India. The claim that it is related to the Indian Army is false and misleading.

Claims:
A viral video falsely claims that a group of lawbreakers is surrendering to the Indian Army, linking the footage to recent events in India.



Fact Check:
Upon receiving the viral posts, we analysed the keyframes of the video through Google Lens search. The search directed us to credible news sources in Bangladesh, which confirmed that the video was filmed during a surrender event involving criminals in Bangladesh, not India.

We further verified the video by cross-referencing it with official military and news reports from India. None of the sources supported the claim that the video involved the Indian Army. Instead, the video was linked to another similar Bangladesh Media covering the news.

No evidence was found in any credible Indian news media outlets that covered the video. The viral video was clearly taken out of context and misrepresented to mislead viewers.
Conclusion:
The viral video claiming to show lawbreakers surrendering to the Indian Army is footage from Bangladesh. The CyberPeace Research Team confirms that the video is falsely attributed to India, misleading the claim.
- Claim: The video shows miscreants surrendering to the Indian Army.
- Claimed on: Facebook, X, YouTube
- Fact Check: False & Misleading
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Executive Summary:
Recently, there has been a massive amount of fake news about India’s standing in the United Security Council (UNSC), including a veto. This report, compiled scrupulously by the CyberPeace Research Wing, delves into the provenance and credibility of the information, and it is debunked. No information from the UN or any relevant bodies has been released with regard to India’s permanent UNSC membership although India has swiftly made remarkable progress to achieve this strategic goal.

Claims:
Viral posts claim that India has become the first-ever unanimously voted permanent and veto-holding member of the United Nations Security Council (UNSC). Those posts also claim that this was achieved through overwhelming international support, granting India the same standing as the current permanent members.



Factcheck:
The CyberPeace Research Team did a thorough keyword search on the official UNSC official website and its associated social media profiles; there are presently no official announcements declaring India's entry into permanent status in the UNSC. India remains a non-permanent member, with the five permanent actors- China, France, Russia, United Kingdom, and USA- still holding veto power. Furthermore, India, along with Brazil, Germany, and Japan (the G4 nations), proposes reform of the UNSC; yet no formal resolutions have come to the surface to alter the status quo of permanent membership. We then used tools such as Google Fact Check Explorer to uncover the truth behind these viral claims. We found several debunked articles posted by other fact-checking organizations.

The viral claims also lack credible sources or authenticated references from international institutions, further discrediting the claims. Hence, the claims made by several users on social media about India becoming the first-ever unanimously voted permanent and veto-holding member of the UNSC are misleading and fake.
Conclusion:
The viral claim that India has become a permanent member of the UNSC with veto power is entirely false. India, along with the non-permanent members, protests the need for a restructuring of the UN Security Council. However, there have been no official or formal declarations or commitments for alterations in the composition of the permanent members and their powers to date. Social media users are advised to rely on verified sources for information and refrain from spreading unsubstantiated claims that contribute to misinformation.
- Claim: India’s Permanent Membership in UNSC.
- Claimed On: YouTube, LinkedIn, Facebook, X (Formerly Known As Twitter)
- Fact Check: Fake & Misleading.

AI and other technologies are advancing rapidly. This has ensured the rapid spread of information, and even misinformation. LLMs have their advantages, but they also come with drawbacks, such as confident but inaccurate responses due to limitations in their training data. The evidence-driven retrieval systems aim to address this issue by using and incorporating factual information during response generation to prevent hallucination and retrieve accurate responses.
What is Retrieval-Augmented Response Generation?
Evidence-driven Retrieval Augmented Generation (or RAG) is an AI framework that improves the accuracy and reliability of large language models (LLMs) by grounding them in external knowledge bases. RAG systems combine the generative power of LLMs with a dynamic information retrieval mechanism. The standard AI models rely solely on pre-trained knowledge and pattern recognition to generate text. RAG pulls in credible, up-to-date information from various sources during the response generation process. RAG integrates real-time evidence retrieval with AI-based responses, combining large-scale data with reliable sources to combat misinformation. It follows the pattern of:
- Query Identification: When misinformation is detected or a query is raised.
- Evidence Retrieval: The AI searches databases for relevant, credible evidence to support or refute the claim.
- Response Generation: Using the evidence, the system generates a fact-based response that addresses the claim.
How is Evidence-Driven RAG the key to Fighting Misinformation?
- RAG systems can integrate the latest data, providing information on recent scientific discoveries.
- The retrieval mechanism allows RAG systems to pull specific, relevant information for each query, tailoring the response to a particular user’s needs.
- RAG systems can provide sources for their information, enhancing accountability and allowing users to verify claims.
- Especially for those requiring specific or specialised knowledge, RAG systems can excel where traditional models might struggle.
- By accessing a diverse range of up-to-date sources, RAG systems may offer more balanced viewpoints, unlike traditional LLMs.
Policy Implications and the Role of Regulation
With its potential to enhance content accuracy, RAG also intersects with important regulatory considerations. India has one of the largest internet user bases globally, and the challenges of managing misinformation are particularly pronounced.
- Indian regulators, such as MeitY, play a key role in guiding technology regulation. Similar to the EU's Digital Services Act, the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, mandate platforms to publish compliance reports detailing actions against misinformation. Integrating RAG systems can help ensure accurate, legally accountable content moderation.
- Collaboration among companies, policymakers, and academia is crucial for RAG adaptation, addressing local languages and cultural nuances while safeguarding free expression.
- Ethical considerations are vital to prevent social unrest, requiring transparency in RAG operations, including evidence retrieval and content classification. This balance can create a safer online environment while curbing misinformation.
Challenges and Limitations of RAG
While RAG holds significant promise, it has its challenges and limitations.
- Ensuring that RAG systems retrieve evidence only from trusted and credible sources is a key challenge.
- For RAG to be effective, users must trust the system. Sceptics of content moderation may show resistance to accepting the system’s responses.
- Generating a response too quickly may compromise the quality of the evidence while taking too long can allow misinformation to spread unchecked.
Conclusion
Evidence-driven retrieval systems, such as Retrieval-Augmented Generation, represent a pivotal advancement in the ongoing battle against misinformation. By integrating real-time data and credible sources into AI-generated responses, RAG enhances the reliability and transparency of online content moderation. It addresses the limitations of traditional AI models and aligns with regulatory frameworks aimed at maintaining digital accountability, as seen in India and globally. However, the successful deployment of RAG requires overcoming challenges related to source credibility, user trust, and response efficiency. Collaboration between technology providers, policymakers, and academic experts can foster the navigation of these to create a safer and more accurate online environment. As digital landscapes evolve, RAG systems offer a promising path forward, ensuring that technological progress is matched by a commitment to truth and informed discourse.
References
- https://experts.illinois.edu/en/publications/evidence-driven-retrieval-augmented-response-generation-for-onlin
- https://research.ibm.com/blog/retrieval-augmented-generation-RAG
- https://medium.com/@mpuig/rag-systems-vs-traditional-language-models-a-new-era-of-ai-powered-information-retrieval-887ec31c15a0
- https://www.researchgate.net/publication/383701402_Web_Retrieval_Agents_for_Evidence-Based_Misinformation_Detection

Introduction
Generative AI, particularly deepfake technology, poses significant risks to security in the financial sector. Deepfake technology can convincingly mimic voices, create lip-sync videos, execute face swaps, and carry out other types of impersonation through tools like DALL-E, Midjourney, Respeecher, Murf, etc, which are now widely accessible and have been misused for fraud. For example, in 2024, cybercriminals in Hong Kong used deepfake technology to impersonate the Chief Financial Officer of a company, defrauding it of $25 million. Surveys, including Regula’s Deepfake Trends 2024 and Sumsub reports, highlight financial services as the most targeted sector for deepfake-induced fraud.
Deepfake Technology and Its Risks to Financial Systems
India’s financial ecosystem, including banks, NBFCs, and fintech companies, is leveraging technology to enhance access to credit for households and MSMEs. The country is a leader in global real-time payments and its digital economy comprises 10% of its GDP. However, it faces unique cybersecurity challenges. According to the RBI’s 2023-24 Currency and Finance report, banks cite cybersecurity threats, legacy systems, and low customer digital literacy as major hurdles in digital adoption. Deepfake technology intensifies risks like:
- Social Engineering Attacks: Information security breaches through phishing, vishing, etc. become more convincing with deepfake imagery and audio.
- Bypassing Authentication Protocols: Deepfake audio or images may circumvent voice and image-based authentication systems, exposing sensitive data.
- Market Manipulation: Misleading deepfake content making false claims and endorsements can harm investor trust and damage stock market performance.
- Business Email Compromise Scams: Deepfake audio can mimic the voice of a real person with authority in the organization to falsely authorize payments.
- Evolving Deception Techniques: The usage of AI will allow cybercriminals to deploy malware that can adapt in real-time to carry out phishing attacks and inundate targets with increased speed and variations. Legacy security frameworks are not suited to countering automated attacks at such a scale.
Existing Frameworks and Gaps
In 2016, the RBI introduced cybersecurity guidelines for banks, neo-banking, lending, and non-banking financial institutions, focusing on resilience measures like Board-level policies, baseline security standards, data leak prevention, running penetration tests, and mandating Cybersecurity Operations Centres (C-SOCs). It also mandated incident reporting to the RBI for cyber events. Similarly, SEBI’s Cybersecurity and Cyber Resilience Framework (CSCRF) applies to regulated entities (REs) like stock brokers, mutual funds, KYC agencies, etc., requiring policies, risk management frameworks, and third-party assessments of cyber resilience measures. While both frameworks are comprehensive, they require updates addressing emerging threats from generative AI-driven cyber fraud.
Cyberpeace Recommendations
- AI Cybersecurity to Counter AI Cybercrime: AI-generated attacks can be designed to overwhelm with their speed and scale. Cybercriminals increasingly exploit platforms like LinkedIn, Microsoft Teams, and Messenger, to target people. More and more organizations of all sizes will have to use AI-based cybersecurity for detection and response since generative AI is becoming increasingly essential in combating hackers and breaches.
- Enhancing Multi-factor Authentication (MFA): With improving image and voice-generation/manipulation technologies, enhanced authentication measures such as token-based authentication or other hardware-based measures, abnormal behaviour detection, multi-device push notifications, geolocation verifications, etc. can be used to improve prevention strategies. New targeted technological solutions for content-driven authentication can also be implemented.
- Addressing Third-Party Vulnerabilities: Financial institutions often outsource operations to vendors that may not follow the same cybersecurity protocols, which can introduce vulnerabilities. Ensuring all parties follow standardized protocols can address these gaps.
- Protecting Senior Professionals: Senior-level and high-profile individuals at organizations are at a greater risk of being imitated or impersonated since they hold higher authority over decision-making and have greater access to sensitive information. Protecting their identity metrics through technological interventions is of utmost importance.
- Advanced Employee Training: To build organizational resilience, employees must be trained to understand how generative and emerging technologies work. A well-trained workforce can significantly lower the likelihood of successful human-focused human-focused cyberattacks like phishing and impersonation.
- Financial Support to Smaller Institutions: Smaller institutions may not have the resources to invest in robust long-term cybersecurity solutions and upgrades. They require financial and technological support from the government to meet requisite standards.
Conclusion
According to The India Cyber Threat Report 2025 by the Data Security Council of India (DSCI) and Seqrite, deepfake-enabled cyberattacks, especially in the finance and healthcare sectors, are set to increase in 2025. This has the potential to disrupt services, steal sensitive data, and exploit geopolitical tensions, presenting a significant risk to the critical infrastructure of India.
As the threat landscape changes, institutions will have to continue to embrace AI and Machine Learning (ML) for threat detection and response. The financial sector must prioritize robust cybersecurity strategies, participate in regulation-framing procedures, adopt AI-based solutions, and enhance workforce training, to safeguard against AI-enabled fraud. Collaborative efforts among policymakers, financial institutions, and technology providers will be essential to strengthen defenses.
Sources
- https://sumsub.com/newsroom/deepfake-cases-surge-in-countries-holding-2024-elections-sumsub-research-shows/
- https://www.globenewswire.com/news-release/2024/10/31/2972565/0/en/Deepfake-Fraud-Costs-the-Financial-Sector-an-Average-of-600-000-for-Each-Company-Regula-s-Survey-Shows.html
- https://www.sipa.columbia.edu/sites/default/files/2023-05/For%20Publication_BOfA_PollardCartier.pdf
- https://edition.cnn.com/2024/02/04/asia/deepfake-cfo-scam-hong-kong-intl-hnk/index.html
- https://www.rbi.org.in/Commonman/English/scripts/Notification.aspx?Id=1721
- https://elplaw.in/leadership/cybersecurity-and-cyber-resilience-framework-for-sebi-regulated-entities/
- https://economictimes.indiatimes.com/tech/artificial-intelligence/ai-driven-deepfake-enabled-cyberattacks-to-rise-in-2025-healthcarefinance-sectors-at-risk-report/articleshow/115976846.cms?from=mdr