Chinese-Backed Operation Reportedly Used AI-Generated Deepfake Videos of Indian Stock Experts in Investment Fraud Campaign

Mumbai Cyber Police reportedly uncovered a coordinated investment fraud campaign that used purported deepfake videos of Indian stock market experts to mislead investors. Between July 1 and July 18, 2025, the videos reportedly circulated on social media as paid promotions by a Bengaluru-based firm, Valueleaf, allegedly contracted by a Hong Kong company, First Bridge. Four individuals were arrested.

Risk classification

• Primary risk domain: 4 Malicious actors
• Primary risk subdomain: 4.3 Fraud, scams, and targeted manipulation

The incident involved the coordinated use of deepfake videos of stock market experts to run fraudulent investment advertisements and scam investors for financial gain.

Additional risk subdomains

• 6.3 Economic and cultural devaluation of human effort: The public likeness and identity of prominent stock market experts were reproduced and exploited without their consent to create the fraudulent videos.

Causal factors

• Entity: Human
• Intent: Intentional
• Timing: Post-deployment

The incident was caused by human actors who intentionally deployed deepfake generation technology to commit financial fraud.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Risk Level 3 (Limited Risk): The incident involves AI-generated content such as deepfakes, which are subject to transparency obligations under the EU AI Act.

AI system and alleged parties

• AI system: unspecified
• AI purpose: Deepfake Video Generation; Social Media Content Generation
• Behaviour type: Tool
• Alleged developer: Unknown voice cloning technology developers, Unknown deepfake technology developers
• Alleged deployer: Valueleaf, First Bridge
• Alleged harmed parties: Unnamed Indian stock market experts, Investors, Indian investors, General public of India

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Minor. Severity is scored from Negligible to Catastrophic in each harm category, for harm the reports describe as caused directly or indirectly by the AI system.

• Physical: direct Negligible, indirect Negligible
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Negligible
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Minor, indirect Negligible
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Minor, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Malicious content

Reported: Yes, the report describes deepfake promotional videos spreading false and misleading information about share trading.

Directly caused: Deepfake videos of stock market experts were created and promoted across 18 to 38 advertising accounts on Meta platforms.

Inferred additional harm: It is likely that these videos reached hundreds of thousands of social media users before being taken down.

Epistemic

Reported: Yes, the report describes deepfake videos spreading false and misleading information about share trading, undermining public trust.

Directly caused: The deepfake videos fabricated statements from stock market experts to mislead investors.

Inferred additional harm: The campaign likely eroded public trust in online financial advice and the authenticity of digital media.

People affected

• Occurrences reported: 1
• People reportedly harmed: 5
• People reportedly exposed: 5

Potential causes

Management

• Financial Incentive Prioritization: Marketing firm prioritized a 3 crore contract over ethical and legal safety.
• Lack of Campaign Oversight: No internal compliance review to check the legitimacy of the ad content.

Technology

• Deepfake Video Generation: AI was used to generate highly realistic fake videos of stock market experts.
• Evasion of Platform Detection: Exploiting ad platform algorithms by scaling accounts and changing domains.

Data Inputs

• Manipulated Expert Footage: Authentic videos of stock market experts were used to train deepfake models.
• Misleading Ad Creative Data: Fraudulent investment claims and fake data were injected into ad campaigns.

Human Factors

• Intentional Deception by Creators: Engineers and MBA graduates knowingly deployed deepfakes to defraud investors.
• Public Trust in Expert Personas: Investors trusted the simulated personas of well-known stock market experts.

Process and Methods

• Delayed Content Takedown: Social media platforms took several weeks to detect and remove the fake ads.
• Ad Account Proliferation: Spreading ads across 38 accounts to bypass platform moderation filters.

Regulatory Environment

• Lack of Proactive Ad Screening: Regulatory and platform policies failed to prevent deepfake ads before launch.

Information quality

• Classification confidence: High
• Reason for confidence: The report provides clear factual details about the arrest of the fraudsters, the budget of the campaign, the platforms used, and the nature of the deepfakes. There is little ambiguity about the events.
• Ambiguities identified: The exact number of defrauded investors and the total financial amount stolen from them are still under investigation.

A sophisticated, cross-border investment fraud campaign in India utilized deepfake videos of stock market experts to deceive investors. Funded by a Hong Kong firm and executed by an Indian agency, the operation highlights the evolving threat of AI-generated synthetic media in financial crime. While it does not pose a systemic threat to national security, it demonstrates an advanced capability of malicious actors to exploit AI for targeted economic fraud.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: India
• Alleged perpetrator: First Bridge and Valueleaf

Threat characteristics

• Imminence: Long-term. The specific campaign has been dismantled by police, representing an ongoing strategic concern regarding deepfake-enabled financial fraud rather than an active crisis.
• Autonomy: Human-controlled. AI was used as a tool by human actors to generate synthetic videos; the campaign deployment, evasion, and target selection were fully controlled by humans.
• Novelty: Evolved capability. Represents an advanced, well-funded evolution of existing deepfake fraud techniques, utilizing cross-border funding and sophisticated evasion tactics.

Impact by dimension

• Physical security: Negligible. No physical systems, critical infrastructure, or human safety elements were compromised or targeted in this financial fraud incident.
• Information security: Minor. The incident involved a coordinated deepfake campaign, but it was aimed at financial fraud rather than state-sponsored information warfare, intelligence compromise, or targeting national leadership.
• Sovereignty: Negligible. Core government operations, electoral systems, and state sovereignty were not targeted or affected by this commercial investment fraud.
• Economic security: Minor. Represents a sophisticated financial scam targeting retail investors with foreign funding, but lacks the scale to threaten systemic national economic stability or strategic technology.
• Societal stability: Minor. While eroding public trust in digital media and financial advice, the incident did not cause widespread civil unrest, systematic discrimination, or mass human rights violations.