#FactCheck -Edited Jaishankar Video Falsely Links Him to ‘Cockroach Party’ Remarks; Fact Check Finds No Such Statement

Introduction

The advent of AI-driven deepfake technology has facilitated the creation of explicit counterfeit videos for sextortion purposes. There has been an alarming increase in the use of Artificial Intelligence to create fake explicit images or videos for sextortion.

What is AI Sextortion and Deepfake Technology

AI sextortion refers to the use of artificial intelligence (AI) technology, particularly deepfake algorithms, to create counterfeit explicit videos or images for the purpose of harassing, extorting, or blackmailing individuals. Deepfake technology utilises AI algorithms to manipulate or replace faces and bodies in videos, making them appear realistic and often indistinguishable from genuine footage. This enables malicious actors to create explicit content that falsely portrays individuals engaging in sexual activities, even if they never participated in such actions.

Background on the Alarming Increase in AI Sextortion Cases

Recently there has been a significant increase in AI sextortion cases. Advancements in AI and deepfake technology have made it easier for perpetrators to create highly convincing fake explicit videos or images. The algorithms behind these technologies have become more sophisticated, allowing for more seamless and realistic manipulations. And the accessibility of AI tools and resources has increased, with open-source software and cloud-based services readily available to anyone. This accessibility has lowered the barrier to entry, enabling individuals with malicious intent to exploit these technologies for sextortion purposes.

The proliferation of sharing content on social media

The proliferation of social media platforms and the widespread sharing of personal content online have provided perpetrators with a vast pool of potential victims’ images and videos. By utilising these readily available resources, perpetrators can create deepfake explicit content that closely resembles the victims, increasing the likelihood of success in their extortion schemes.

Furthermore, the anonymity and wide reach of the internet and social media platforms allow perpetrators to distribute manipulated content quickly and easily. They can target individuals specifically or upload the content to public forums and pornographic websites, amplifying the impact and humiliation experienced by victims.

What are law agencies doing?

The alarming increase in AI sextortion cases has prompted concern among law enforcement agencies, advocacy groups, and technology companies. This is high time to make strong Efforts to raise awareness about the risks of AI sextortion, develop detection and prevention tools, and strengthen legal frameworks to address these emerging threats to individuals’ privacy, safety, and well-being.

There is a need for Technological Solutions, which develops and deploys advanced AI-based detection tools to identify and flag AI-generated deepfake content on platforms and services. And collaboration with technology companies to integrate such solutions.

Collaboration with Social Media Platforms is also needed. Social media platforms and technology companies can reframe and enforce community guidelines and policies against disseminating AI-generated explicit content. And can ensure foster cooperation in developing robust content moderation systems and reporting mechanisms.

There is a need to strengthen the legal frameworks to address AI sextortion, including laws that specifically criminalise the creation, distribution, and possession of AI-generated explicit content. Ensure adequate penalties for offenders and provisions for cross-border cooperation.

Proactive measures to combat AI-driven sextortion

Prevention and Awareness: Proactive measures raise awareness about AI sextortion, helping individuals recognise risks and take precautions.

Early Detection and Reporting: Proactive measures employ advanced detection tools to identify AI-generated deepfake content early, enabling prompt intervention and support for victims.

Legal Frameworks and Regulations: Proactive measures strengthen legal frameworks to criminalise AI sextortion, facilitate cross-border cooperation, and impose offender penalties.

Technological Solutions: Proactive measures focus on developing tools and algorithms to detect and remove AI-generated explicit content, making it harder for perpetrators to carry out their schemes.

International Cooperation: Proactive measures foster collaboration among law enforcement agencies, governments, and technology companies to combat AI sextortion globally.

Support for Victims: Proactive measures provide comprehensive support services, including counselling and legal assistance, to help victims recover from emotional and psychological trauma.

Implementing these proactive measures will help create a safer digital environment for all.

Misuse of Technology

Misusing technology, particularly AI-driven deepfake technology, in the context of sextortion raises serious concerns.

Exploitation of Personal Data: Perpetrators exploit personal data and images available online, such as social media posts or captured video chats, to create AI- manipulation violates privacy rights and exploits the vulnerability of individuals who trust that their personal information will be used responsibly.

Facilitation of Extortion: AI sextortion often involves perpetrators demanding monetary payments, sexually themed images or videos, or other favours under the threat of releasing manipulated content to the public or to the victims’ friends and family. The realistic nature of deepfake technology increases the effectiveness of these extortion attempts, placing victims under significant emotional and financial pressure.

Amplification of Harm: Perpetrators use deepfake technology to create explicit videos or images that appear realistic, thereby increasing the potential for humiliation, harassment, and psychological trauma suffered by victims. The wide distribution of such content on social media platforms and pornographic websites can perpetuate victimisation and cause lasting damage to their reputation and well-being.

Targeting teenagers– Targeting teenagers and extortion demands in AI sextortion cases is a particularly alarming aspect of this issue. Teenagers are particularly vulnerable to AI sextortion due to their increased use of social media platforms for sharing personal information and images. Perpetrators exploit to manipulate and coerce them.

Erosion of Trust: Misusing AI-driven deepfake technology erodes trust in digital media and online interactions. As deepfake content becomes more convincing, it becomes increasingly challenging to distinguish between real and manipulated videos or images.

Proliferation of Pornographic Content: The misuse of AI technology in sextortion contributes to the proliferation of non-consensual pornography (also known as “revenge porn”) and the availability of explicit content featuring unsuspecting individuals. This perpetuates a culture of objectification, exploitation, and non-consensual sharing of intimate material.

Conclusion

Addressing the concern of AI sextortion requires a multi-faceted approach, including technological advancements in detection and prevention, legal frameworks to hold offenders accountable, awareness about the risks, and collaboration between technology companies, law enforcement agencies, and advocacy groups to combat this emerging threat and protect the well-being of individuals online.

In the digital era of the present day, a nation’s strength no longer gets measured only by the number of missiles or aircraft it has in its inventory. Rather, it also calls for defending the digital borders. Major infrastructures like power grids and dams are increasingly being targeted by cyberattacks in the global security environment that modern militaries operate in. When communication channels are vulnerable to an information breach, cybersecurity becomes a crucial component of national defence. 

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Why is cybersecurity a crucial national security concern in the modern era?

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The technologies and procedures that shield digital devices, networks, and systems from unwanted access or attacks are referred to as cybersecurity. Cyberattacks are silent in the context of national security, in contrast to conventional warfare. They are swift and are also capable of causing a massive disruption without even a single case of physical infiltration. However, hostile states, terrorist organisations, or criminal networks may be able to steal any classified information or disrupt military infrastructure due to a cybersecurity breach in a military network. 

To fully comprehend the significance of cybersecurity, let's examine the various approaches, such as: 

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• Protecting critical infrastructures- Today's nations rely heavily on digital networks to run vital services like banking, transportation, electricity, water supply, and healthcare. Therefore, a cyberattack on these systems could cause problems across the country and interfere with our daily activities. Therefore, it is also seen that the military forces of a nation closely work in synergy with other government agencies and private organizations to create a strong ecosystem of security in this sector. 

• Safeguarding military operations in the present age- The armed forces heavily rely on digital tools for communication, mission planning, surveillance, and coordination. In case the cyber intruders get access to those systems, then a lot of major operational hurdles can come up in the form of breach of mission details, disruption of channels, and compromise of the confidentiality of military operations. These are certain conditions that make cybersecurity an important aspect for protecting the physical bases and the security architectures. 
• Preventing cyber warfare- With the evolution of the geopolitical landscape, state and non-state actors are now resorting to cyberattacks to gather intelligence, disrupt security networks, and influence political outcomes. Still, strong cybersecurity can help nations to ensure, detect, defend, and respond to threats in an effective manner. 
• Securing government databases- The government databases are known for storing sensitive information about the citizens, military assets, diplomatic data, and vital information related to major national infrastructures. If these get compromised, then it can weaken the strategic position of the nation and put the national security of the nation at a grave risk. Therefore, it becomes necessary to protect government data as a priority. 

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How can countries improve their cybersecurity defences?

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Countries all over the world are developing their cyber capabilities using a variety of tactics to protect against the increasing number of cyber threats. A few of these can be interpreted as;

• Creating cyber defence units- The majority of contemporary armed forces have created specialised cyber domains devoted to threat identification. Their responsibilities have been centred on keeping an eye on those dangers, stopping intrusions, and reacting quickly to cyberattacks. 
• Public-Private Partnerships- To safeguard vital industries like energy grids, financial networks, and communication systems, the government collaborates with private businesses and technology suppliers. Additionally, these collaborations foster innovation to improve the overall defence against cyberattacks.

• Establishing international collaborations- Cyber threats do not respect our borders. As a result, which countries are increasing their share of intelligence, best practices, and defensive strategies with their allies? Groups like NATO have conducted a joint cyber defence exercise to prepare for dealing with a digital future. 

However, these collaborations can help to develop a united front against cybercrime. 

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Core Pillars of the modern military cyber defence

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The modern defence strategies have been built upon several key designated pillars that are designed to prevent, detect, and respond to cyber threats, which can be mentioned as; 

• Cyberspace as an operational domain- Militaries have now begun to treat cyberspace like the land, air, sea, and space as domains where wars can both begin and also end. Developing some dedicated cyber units to conduct digital operations to defend networks and engage in a range of counter-cyber activities when required. 
• Active and proactive defence- Instead of passively waiting for the attacks to happen, real-time monitoring tools are used for blocking the threats that arise. Proactive defence goes a step further by hunting for potential threats before they can reach the networks. 
• • Protection of vital infrastructures- The armed forces collaborate closely with civilian organisations and agencies to secure vital infrastructures that are important to the country. Critical infrastructure is protected from cyberattacks by layered defence, which includes encryption, stringent access control, and ongoing monitoring. 
• • Strengthening alliances- Countries can develop a strong and well-coordinated defence system by exchanging intelligence to carry out cooperative cyber operations. 
• Fostering innovation for the development of a workforce- Cyber threats evolve at a rapid pace, which calls for the military to invest in advanced technologies like AI-driven systems, secure cloud technologies, besides ensure continuous training related to cybersecurity.   

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Conclusion

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The modern militaries have adopted the method of protecting digital networks to defend their land and seas. Cybersecurity has become the new line of defence to protect government data and vital defence infrastructure from serious and unseen threats. The countries are building a secure, robust, and resilient digital future with the aid of solid alliances, cutting-edge technologies, knowledgeable workers, and a proactive defence strategy. 

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References

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• https://www.ssh.com/academy/cyber-defense-strategy-dod-perspective#:~:text=Defence%20organizations%20are%20prime%20targets,SSH%20Key%20Management%20and%20Compliance
• https://www.fortinet.com/resources/cyberglossary/cyber-warfare#:~:text=Advanced%20endpoint%20security%20adds%20proactive,information%20by%20halting%20unauthorized%20transfers
• https://medium.com/@lynnfdsouza/the-impact-of-cyber-warfare-on-modern-military-strategies-c77cf6d1a788
• https://ccoe.dsci.in/blog/why-cybersecurity-is-critical-for-national-defense-protecting-countries-in-the-digital-age 

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Introduction

Digital evidence has become part of almost every modern investigation. A photograph can place a person at a location, an audio recording can capture a conversation, and a video can appear to show an event as it happened. For years, the main forensic concern was whether such material had been altered. The rapid growth of generative artificial intelligence has added a harder question: even when a file is preserved exactly as received, can investigators still trust what it appears to show?

Deepfakes have made this question practical rather than theoretical. Synthetic or manipulated audio, video and images can imitate real people and real events with increasing realism. CERT-In describes deepfakes as a high-risk threat because they can support disinformation, fraud, social engineering and reputational harm.[1] NIST research likewise treats AI-generated media as a digital-forensics challenge that requires systematic evaluation of detection technologies.[2]

The result is an evidence problem. The answer is not to stop trusting digital evidence, but to become more disciplined about establishing its origin, integrity, context and authenticity.

The evidence problem begins before the laboratory

When a suspicious video reaches an investigator through WhatsApp, Telegram, email or social media, the file may already have passed through several transformations. It may have been compressed, re-encoded, cropped, renamed or stripped of metadata. A screenshot may preserve what is visible but lose the original file structure. A forwarded audio clip may contain no reliable information about where it was first recorded.

For that reason, forensic examination should begin with acquisition and provenance, not with a quick “deepfake detector” result. Investigators should ask: Who supplied the file? Where was it obtained? Is there an original version? What device or account produced it? What happened to the file before it reached the investigator?

Cryptographic hashing remains important because it can demonstrate that an acquired working copy has not changed during examination. But a valid hash does not prove that the underlying event was genuine. A perfectly preserved fake is still a fake.

What a professional examination should look for

A reliable assessment combines several forms of evidence rather than relying on one technical indicator.

Source and acquisition. The original artefact should be preserved whenever possible. Investigators should record the acquisition method, date and time, source account or device, and any known transformations before collection. A documented chain of custody is essential when material may later support a legal, disciplinary or regulatory decision.

Metadata and file structure. Metadata may provide useful clues about creation, encoding, editing software and timestamps. File structure, compression behaviour and related technical characteristics can also reveal inconsistencies. However, these indicators are supporting evidence, not proof on their own, because metadata can be removed or rewritten during normal processing.

Content-level examination. Forensic analysis can include frame-by-frame video review, audio waveform and spectral examination, and inspection for inconsistencies in lighting, reflections, facial movement, lip synchronisation or background elements. Such signs may help guide an investigation, but they are not a permanent checklist. Generative systems continue to improve.

Independent corroboration. This is often the strongest step. If a recording allegedly shows that a person was in a particular place at a particular time, investigators can compare it with CCTV, access-control records, device artefacts, communications, location information, eyewitness accounts or other independent records. The goal is to determine whether the wider evidence supports the event represented by the media.

A real-world lesson: the Pikesville case

The 2024 Pikesville High School incident in Maryland provides a practical example of why authenticity cannot be assumed from appearance alone. An audio recording circulated online that was presented as the principal making racist and antisemitic comments. On January 17, 2024, Baltimore County Public Schools said it could not yet confirm the recording’s veracity and opened an investigation.[3]

Several months later, the school district reported that investigators, with assistance from the FBI and other experts, had verified that the audio had been created using artificial intelligence.[4] Police subsequently arrested the school’s former athletic director in connection with the fabricated recording.[5]

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The forensic lesson is larger than the incident itself. The recording had social consequences before its authenticity was established. In a fast-moving online environment, the first version of an event can travel much further than the later correction. Deepfake investigations therefore have to consider not only whether media is authentic, but also how quickly unverified material can influence decisions.

From deepfake detection to content provenance

Detection tools will remain useful, but they should be treated as part of an examination rather than an automatic verdict. NIST’s Guardians of Forensic Evidence work reflects the need to evaluate how analytic systems perform against changing forms of AI-generated media and how well they generalise beyond controlled conditions.[2]

Another important direction is content provenance. The Coalition for Content Provenance and Authenticity (C2PA) has developed a technical framework for recording verifiable information about how digital content was created and changed. Content Credentials can bind provenance information to an asset using cryptographic techniques, allowing later users to inspect a recorded content history when that information is available.[6]

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Provenance does not mean that every claim associated with a file is automatically true. It adds context: who created it, what actions were taken and how the asset changed. In a deepfake environment, that context can be as important as the content itself.

Why this matters in India

The issue is especially relevant to India’s fast-growing digital environment. CERT-In’s 2024 advisory identifies misinformation, fraud and reputational damage among the risks associated with synthetic media.[1] In August 2026, the Government of India stated that the regulatory framework addresses AI-generated deepfakes and noted amendments to the IT Rules in February 2026 concerning harms arising from synthetically generated information, including requirements related to labelling and traceable metadata for permissible AI-generated content.[7]

For organisations, deepfake response should therefore not be treated only as a media or public-relations issue. It can become an incident-response and forensic issue. A suspicious executive voice note, a manipulated employee video or a fabricated screen recording may require preservation, technical examination and independent corroboration before any action is taken.

Conclusion

Deepfakes do not make digital evidence useless. Deepfakes make handling of evidence more dangerous. The professional response is not to believe everything or to doubt everything. The professional response is to build a process around evidence: preserve the original where possible document how evidence was acquired, calculate and record hashes, examine metadata and technical characteristics use detection tools while understanding their limitations compare media with independent evidence and examine provenance information where it is available.

Importantly investigators and decision-makers should separate three questions: Is the file intact? Is the content authentic? Does the content actually prove the event being alleged? Deepfakes can pass the test while failing the other two.

In the age of AI evidence will increasingly be judged not only by how convincing it looks but, by how well its origin, integrity, context and history can be demonstrated. That is the standard that can help preserve trust when seeing and hearing're no longer enough.

References

1. CERT-In, “Deepfakes - Threats and Countermeasures,” Advisory CIAD-2024-0060, 27 November 2024. View source

2. NIST, “Guardians of Forensic Evidence: Evaluating Analytic Systems Against AI-Generated Deepfakes,” 27 January 2025. View source

3. Baltimore County Public Schools, “January 17, 2024, Community Update: Message from Superintendent Dr. Myriam Rogers Regarding Pikesville High School.” View source

4. Baltimore County Public Schools, “April 24, 2024 Staff and Community Update: Message from Superintendent Dr. Myriam Rogers Regarding Pikesville High School Investigation.” View source

5. The Baltimore Banner / WYPR, “Ex-athletic director framed principal with AI-generated voice, police say,” 25 April 2024. View source

6. Coalition for Content Provenance and Authenticity (C2PA), “Content Credentials: C2PA Technical Specification,” Version 2.1. View source

7. Government of India, Ministry of Electronics & Information Technology, “Government Strengthens Regulatory Framework to Address AI-Generated Deepfakes,” 6 August 2026. View source

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