#FactCheck - Uncovered: Viral LA Wildfire Video is a Shocking AI-Generated Fake!

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.

Introduction

In June 2026, Eros Innovation launched Eros Music Worlds, describing itself as the world's first "large cultural music platform". Its first two acts, Jordan and Tanu, are not singers in any conventional sense; they are AI-native personas built from Eros's own film characters, powered by models trained on a licensed corpus of roughly 1.5 trillion cultural tokens drawn from 11,000 films. Alongside them sits a strategic partnership with the family of Mohammed Rafi, the late playback legend, to produce new recordings, a live concert franchise, and a music academy in his name. It's a tidy preview of where AI in music is actually headed: not a novelty generator bolted onto the old industry, but a new kind of media company built around owned IP, licensed data, and characters designed to outlive any single song.

Beyond the demo

The last eighteen months have produced a stream of "firsts". Xania Monet, an AI-voiced R&B act built by Mississippi poet Telisha Jones using Suno, became the first AI artist to chart on a Billboard airplay ranking and was signed by Hallwood Media after a bidding war that reportedly reached $3 million. Breaking Rust, Enlly Blue and Juno Skye followed onto country, rock and Christian charts within weeks. None of this happened in a vacuum: Suno and Udio, the two dominant AI music generators, went from being sued by every major label in mid-2024 to signing licensing settlements with Universal and Warner by late 2025. Voice cloning has run a parallel track from the viral 2023 track "Heart on My Sleeve", which mimicked Drake and The Weeknd without consent, to a wave of Indian cases where AI tools recreated a specific singer's timbre for commercial use. Composition and production tools are now routine studio infrastructure rather than curiosities; the interesting frontier has shifted to multilingual adaptation and catalogue reanimation. Eros has promised 34-language localisation for its AI artists, a scale no dubbing studio could match manually. A related, if less music-specific, signal came from Collective Artists Network's AI-powered Mahabharat: Ek Dharmayudh, produced with Prasar Bharati. AI tools handled pre-visualisation, multi-language dubbing sync and sound design, while composers and voice directors retained control of tone and emotion, a template other Indian studios are likely to copy for scoring and localising large-scale cultural content cheaply.

Where the money actually is?

The commercial case for labels isn't "AI makes music at scale", because scale alone isn't value. Deezer, the only major platform publishing detection data, reported in July 2026 that AI-generated tracks had crossed 50% of daily uploads, around 90,000 tracks a day, up from 10,000 in January 2025. Yet those tracks account for only 1–3% of actual streams, and Deezer flags 85% of that listening as fraudulent bot activity. Generating music has become nearly free; getting anyone to listen hasn't. The real opportunity for rights holders lies elsewhere: licensing catalogues into controlled ecosystems (Universal's 2026 platform with Udio, Warner's deals with both Udio and Suno), reviving legacy artists for new audiences (Eros-Rafi), and using AI for the unglamorous, high-volume work of localisation, sync placement and short-form content that never justified full production budgets before. AI-native performers also travel well into gaming, virtual concerts and brand collaboration formats built for characters rather than people, where a synthetic act never ages, never cancels a tour and can be licensed into a dozen campaigns simultaneously. That is a genuinely new revenue line, but it's a narrow one; it monetises IP ownership, not music generation itself. IFPI's Global Music Report 2026 shows the underlying business is healthy: revenues reached $31.7 billion, up 6.4% — but that growth is still driven overwhelmingly by human catalogues and paid subscriptions, not AI-generated volumes.

The legal fault lines

This is where India's position is genuinely instructive and unresolved. The Copyright Act, 1957, defines the author of a "computer-generated" work as the person who causes it to be created (language added in 1994 for a world of human-directed software, not autonomous generative models), and Indian courts haven't yet settled how far it stretches. What's clearer is the industry's stance on training data: The Indian music industry body, alongside T-Series, Saregama and Sony Music, has sought to join the ANI Media suit against OpenAI in the Delhi High Court, arguing that scraping sound recordings to train models without a licence breaches copyright, a case they say is "crucial for the entire music industry in India, and even worldwide".

Personality rights have moved faster than legislation. In the absence of a dedicated statute, Indian courts have built protection case by case: the Delhi High Court's 2023 order shielding Anil Kapoor's voice and likeness from AI misuse and the Bombay High Court's 2024 ruling in Arijit Singh v Codible Ventures, India's first AI voice-cloning judgement, which granted an injunction spanning every medium, explicitly including the metaverse and generative-AI tools, and rejected fair-use and parody defences outright. Similar orders have since followed for Amitabh Bachchan, Aishwarya Rai Bachchan and others. The pattern mirrors, but predates, statutory responses abroad: Tennessee's 2024 ELVIS Act was the first US law to protect voice explicitly as property, and the federal NO FAKES Act remains pending. The US Copyright Office's January 2025 report reaffirmed that human authorship is the bedrock of copyrightability, denying protection to fully AI-generated output while leaving substantially human-directed hybrid works to case-by-case review. Two regimes are converging on the same instinct that consent and human contribution must anchor ownership through different legal tools: India via judge-made personality rights and the US via statute and Copyright Office guidance.

Who bears the risk?

The disruption isn't evenly spread. Session singers, jingle artists, dubbing performers and early-career composers, the layer of the industry that supplies craft rather than fame, are most exposed since their work is precisely what generative tools now approximate cheaply. A PRS for Music survey of over 2,600 creators found 79% worried about AI competing directly with their output and 76% expecting it to hurt their livelihoods. CISAC has projected AI could erode musicians' incomes by nearly a quarter by 2028. Separately, roughly a fifth of professional voice actors surveyed say they've already lost work to a synthetic voice. For streaming platforms, the risk is structural: as AI supply floods catalogues, royalty pools shared across all streams get diluted, discoverability worsens, and fraud bot streams on AI tracks are designed purely to harvest royalties, which becomes a live threat to the economics everyone else depends on.

Recommendations

None of this points to AI simply replacing musicians, nor to it staying a background production tool. A third category is emerging AI-native "characters" with continuity, backstory and owned IP, closer to franchise properties than bands, which is exactly the model Eros and Hallwood Media are betting on. The deeper shift underneath it is economic: once the marginal cost of producing a new track approaches zero, the constraint on the industry stops being supplied and becomes attention. Whether AI-native artists become a durable category depends on questions still unresolved, training data legality chief among them, and on whether audiences keep listening once the novelty fades. Deezer's own research found 97% of listeners can't reliably distinguish AI from human music, yet 52% still believe fully AI-generated songs shouldn't sit on the same charts as human ones. Provenance matters even when perception can't detect it.

Conclusion

Scarcity in the age of AI will not be creative output but genuine human connection. As AI makes music production abundant and inexpensive, the qualities it cannot replicate authenticity, lived experience, artistic identity, and trust – become increasingly valuable. Audiences will continue to seek creators with compelling stories and meaningful live experiences. In an era of infinite synthetic content, originality is no longer the premium; credibility, human presence, and emotional connection are.

Sources

1. https://www.livemint.com/industry/media/ai-music-ai-native-artists-eros-music-worlds-eros-innovation-copyright-intellectual-property-music-industry-11785053693997.html
2. https://www.facebook.com/KJSIMofficial/posts/the-mint-featured-insights-from-dr-alka-agarwal-assistant-professor-general-mana/1375301184595168/
3. https://www.linkedin.com/posts/livemint_how-ai-brought-the-mahabharat-to-life-collective-activity-7389643662193999873-6BKG
4. https://musically.com/2026/07/02/ai-powered-platform-eros-music-worlds-is-turning-film-characters-into-virtual-singers/
5. https://www.business-standard.com/companies/news/bollywood-t-series-saregama-sony-music-copyright-lawsuit-openai-delhi-hc-125021400876_1.html 

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Executive Summary

A video is going viral on social media with the claim that it shows an exchange of fire between Indian and Chinese troops in Arunachal Pradesh. In the video, amid the firing, one soldier can be seen holding another soldier and taking him to a safe location. Several soldiers are also seen continuously firing between the mountains. The post claims that the country’s media is not showing these visuals. CyberPeace Research found that the video was actually filmed during a military training exercise in Kazakhstan.

Claim

A Facebook user shared the viral video with the caption: “The anti-national media will not show this.”

https://www.facebook.com/reel/2210190566198227 

https://archive.ph/yWiLZ 

Fact Check

To verify the authenticity of the video being shared as footage of an exchange of fire between Indian and Chinese troops in Arunachal Pradesh, we first conducted a Google search using relevant keywords. However, we did not find any credible media reports mentioning any recent incident of firing between the two sides. We also did not find the video in any media report describing it as footage of firing along the India-China border.

We then conducted a reverse search of the video’s keyframes and found the same video uploaded on the Instagram account of the Tactical Training Federation of Kazakhstan. The video was uploaded on July 28, 2026. According to the caption, “Training sessions were conducted by the Federation of Tactical Training with soldiers of the Special Operations Forces (SSO) of the Ministry of Defence of the Republic of Kazakhstan at the Koktal training ground in the city of Zharkent. The main objective of these sessions was to bring training conditions as close as possible to the realities of modern warfare, thereby improving the soldiers’ practical skills, tactical thinking and readiness to operate in complex situations.”

https://www.instagram.com/reels/DbTcbswsRdS/

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Additionally, several other videos related to military training are available on the account. According to the bio, the organisation is involved in defence activities and the training of military personnel.

https://www.instagram.com/p/Dci49EiMjje/ 

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Conclusion

Our research found that the video being shared as footage of an exchange of fire between Indian and Chinese troops in Arunachal Pradesh is actually from Kazakhstan. The video was filmed during a military training exercise organised by Kazakhstan’s Federation of Tactical Training.

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