Purported Russian-Linked Network Allegedly Used Deepfake of Maria Ressa on Facebook and Bing to Promote Cryptocurrency Scam Targeting Filipinos

A purportedly Russian-linked scam network allegedly circulated an AI-generated deepfake of journalist Maria Ressa on Facebook and Microsoft Bing. The video reportedly manipulated a 2022 interview to falsely depict Ressa endorsing cryptocurrency. Fraudulent websites allegedly impersonating Rappler and CNN Philippines reportedly amplified the scam. Investigators reportedly linked the operation to a fraudulent network targeting Filipino audiences. Meta and Microsoft removed the content, but similar scams allegedly continue to resurface.

Risk classification

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

The incident involved using AI-generated voice clones and deepfakes to impersonate a trusted individual for financial benefit through a cryptocurrency scam.

Additional risk subdomains

• 3.1 False or misleading information: The campaign generated false news articles and videos to mislead the public about Maria Ressa's involvement in a cryptocurrency scam.

Causal factors

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

The incident was caused by a Russian scam network intentionally deploying AI-generated deepfakes to defraud users.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Limited Risk: The report describes the creation of AI-generated deepfakes, which are subject to transparency obligations under the EU AI Act to ensure users are aware they are interacting with synthetic content.

AI system and alleged parties

• AI system: unspecified
• AI purpose: Deepfake Video Generation; Voice Generation
• Behaviour type: Tool
• Alleged developer: Unknown deepfake technology developers, Unknown AI voice cloning developers
• Alleged deployer: TD Globus Contract, Russian-linked scam network, M1 Shop
• Alleged harmed parties: Rappler, Public trust in media institutions, Potential cryptocurrency scam victims, Maria Ressa, Filipino social media users, CNN Philippines

Harm severity

Highest direct severity in any category: Substantial. 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 Substantial
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Malicious content

Reported: The report explicitly describes the creation and spread of malicious deepfake video and audio content.

Directly caused: An AI-generated deepfake video and voice clone of Maria Ressa was created and distributed on Facebook and Microsoft Bing to promote a scam.

Indirectly caused: N/A

Inferred additional harm: Similar malicious deepfakes targeting other Filipino businessmen and media anchors were also circulated using similar methods.

Epistemic

Reported: The report explicitly describes epistemic harm through the creation of fake news articles and a deepfake video that fabricated statements by Maria Ressa.

Directly caused: The scammers created cloned websites of Rappler and CNN Philippines containing fabricated articles and an AI-generated video to mislead the public.

Indirectly caused: The use of cloned news sites and deepfakes of journalists undermines public trust in legitimate news organizations and media credibility.

Inferred additional harm: The proliferation of such highly convincing deepfakes erodes the general public's trust in digital information and shared consensus reality.

People affected

• Occurrences reported: 1
• People reportedly harmed: 1
• People reportedly exposed: 22000

Potential causes

Management

• Inadequate Ad Monitoring: Platforms failed to proactively monitor and block AI-generated scam ads.
• Profit from Disinformation: Platforms profit from ad revenues, reducing incentive for strict pre-screening.

Technology

• Open-Source AI Misuse: Open-source LLMs allow bad actors to modify code and strip watermarks.
• Watermark Removal Tech: Existing tools can easily remove watermarks designed to label AI content.
• Realistic AI Voice Generation: Generative AI voice cloning mimics authoritative voices to deceive users.

Data Inputs

• Scraped Media Data: Scraped original video and audio utilized to train and generate deepfakes.
• Lack of Provenance Data: Absence of secure metadata on original media allowed unauthorized manipulation.

Human Factors

• User Inattention: Users not paying attention fail to notice lip-syncing errors in deepfakes.
• Trust in Authority Figures: Scammers exploit trust in journalists' reputations to make scams believable.

Process and Methods

• Weak Ad Review Processes: Bing and Facebook allowed fraudulent ads promoting deepfakes to be published.
• Slow Platform Response: Delayed takedowns allowed deepfakes to garner tens of thousands of views.
• Whack-a-Mole Domain Tactics: Scammers rapidly register new domains to bypass platform domain bans.

Regulatory Environment

• Lack of Platform Accountability: No strong legal frameworks to hold platforms liable for hosting fake ads.
• Anonymity in Domain Registration: Scammers exploit loose domain registration rules to remain anonymous.

Information quality

• Classification confidence: High
• Reason for confidence: The report is highly detailed, coming directly from Rappler (the targeted organization) and supported by a digital forensic investigation by Qurium, providing clear evidence of the scam's mechanics and impact.
• Ambiguities identified: The specific AI models used to generate the voice clone and deepfake video are not identified.

A Russian-linked scam network utilized AI-generated deepfakes and voice clones of Nobel laureate Maria Ressa to run cryptocurrency fraud campaigns targeting Philippine audiences. While demonstrating evolved capabilities in synthetic media generation and ad-network evasion, the incident's impact remains confined to localized financial fraud and reputational damage, posing minor national security concerns.

• Overall national security impact: Minor
• Response level: Moderate
• Scope: Multiple nations
• Primary target: Philippines
• Alleged perpetrator: Russian scam network

Threat characteristics

• Imminence: Long-term. Represents an ongoing strategic concern regarding the proliferation of deepfake technology for fraud rather than an immediate national security crisis.
• Autonomy: Human-controlled. The AI systems were utilized strictly as tools by human operators to generate specific media assets.
• Novelty: Evolved capability. While deepfake scams are established, the integration of voice cloning with multi-layered ad-evasion networks targeting specific national figures represents an evolved threat.

Impact by dimension

• Physical security: Negligible. No threats to physical systems, critical infrastructure, or human safety were reported in this incident.
• Information security: Minor. Foreign-linked network deployed AI-generated deepfakes of a prominent journalist to spread disinformation, but it was primarily a financially motivated scam rather than state-directed information warfare.
• Sovereignty: Negligible. No impact on state authority, government operations, or constitutional processes.
• Economic security: Minor. Involves localized financial fraud and cryptocurrency scams, but does not threaten national economic stability or strategic industries.
• Societal stability: Minor. Targeted reputational damage against a prominent journalist and potential erosion of public trust in media, but no mass-scale societal disruption.