Scammers Reportedly Used AI Images of Former Papua New Guinea Television Host in Sexualized Posts and Fake Giveaways

Scammers reportedly used AI-altered photos of former Papua New Guinea television host Jennifer Baing to depict her in lingerie and handing out cash, and used her likeness on Facebook to promote fake giveaways soliciting money. Baing described reputational harm and concerns about her safety. She said impersonating accounts remained online despite her reports to the platform.

Risk classification

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

The incident primarily involves scammers using AI-generated deepfakes of a public figure's likeness to run fraudulent giveaway scams and target her with humiliating synthetic imagery.

Additional risk subdomains

• 1.2 Exposure to toxic content: The report highlights a severe regional trend of creating non-consensual AI-generated sexually explicit images of young women, leading to extreme distress.

Causal factors

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

The harm was caused by human scammers intentionally using deployed AI image generation tools to create deepfakes for fraud and harassment.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Risk Level 3: Limited Risk. The report describes the use of AI to generate deepfakes, which falls under the category of AI-generated content requiring transparency obligations under the EU AI Act.

AI system and alleged parties

• AI system: None named
• AI purpose: Deepfake Image Generation; Image Generation
• Behaviour type: Tool
• Alleged developer: Synthetic media technology developers, Synthetic image generation technology developers, Deepfake technology developers
• Alleged deployer: Synthetic media creators, Scammers in Papua New Guinea, Scammers impersonating Jennifer Baing, Scammers, Impersonation scammers, Deepfake creators, Cybercriminals
• Alleged harmed parties: Women and girls, Women, Victims of deepfake abuse, Public figures, Privacy, Jennifer Baing, Impersonated public figures, General public of Papua New Guinea, General public, Epistemic integrity

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Negligible. 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 Substantial
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Negligible
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Negligible, indirect Substantial
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Minor
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Minor
• Psychological: direct Negligible, indirect Substantial
• Epistemic: direct Negligible, indirect Minor
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Physical

Reported: Yes, the report explicitly describes indirect physical harm (suicide) resulting from the distress of AI-generated explicit images.

Indirectly caused: The PNG Assistant Commissioner of Police reported several instances where young women committed suicide due to the severe mental stress caused by AI-generated explicit images.

Malicious content

Reported: Yes, the report describes the creation and spread of AI-manipulated fake images, including revealing lingerie and non-consensual nude images.

Indirectly caused: Scammers and malicious actors created and distributed AI-manipulated images of Jennifer Baing in revealing lingerie and naked images of other young girls on Facebook.

Inferred additional harm: It is highly likely that thousands of social media users were exposed to these toxic and non-consensual synthetic images across Facebook.

Civil rights

Reported: Yes, the report describes violations of personal dignity, safety, and the non-consensual exploitation of women's likenesses.

Indirectly caused: The non-consensual generation of sexually explicit images of young women violates their fundamental right to privacy, dignity, and personal safety.

Inferred additional harm: Many more women in PNG likely face similar violations of their digital safety and human rights due to the proliferation of unregulated AI tools.

Privacy

Reported: Yes, the report describes the unauthorized use and manipulation of the victim's social media photos.

Indirectly caused: Scammers violated Jennifer Baing's privacy by taking photos from her social media accounts and using AI to manipulate them into revealing lingerie images.

Inferred additional harm: The privacy of numerous other young women has likely been violated through the scraping and synthetic manipulation of their public social media profiles.

Psychological

Reported: Yes, the report explicitly describes severe psychological distress and mental stress among victims.

Indirectly caused: Jennifer Baing reported feeling concerned for her personal safety, and the police assistant commissioner noted devastating psychological impacts and serious mental stress among young female victims of deepfakes.

Inferred additional harm: Widespread psychological trauma and anxiety are highly likely among the many victims of the 100 fake accounts and other daily deepfake cases reported to PNG police.

Epistemic

Reported: Yes, the report describes the generation of fake images to deceive people into believing the victim was promoting cash giveaways.

Indirectly caused: AI-generated fake images of Jennifer Baing holding cash misled Facebook users into believing she was running legitimate giveaways.

Inferred additional harm: The widespread availability of deepfakes erodes public trust in online information, particularly in rural communities with limited digital literacy.

People affected

• Occurrences reported: 1
• People reportedly harmed: 5
• People reportedly exposed: 1000

Potential causes

Management

• Under-resourced Police Unit: PNG's Cybercrime Unit has only seven officers for ten million people.
• Inadequate Platform Moderation: Social media platforms lack effective oversight to prevent impersonation.

Technology

• AI Deepfake Generators: AI tools enable easy manipulation of photos to create explicit content.
• Profile Cloning Capabilities: Scammers cloned social media profiles to impersonate the victim online.

Data Inputs

• Public Social Media Photos: Scammers harvested photos from the victim's public social media accounts.

Human Factors

• Scammer Malicious Intent: Scammers intentionally exploited the victim's likeness to defraud people.
• Limited Public AI Awareness: Rural communities lack understanding of how AI can be used to deceive.
• Underestimation of AI Risks: Pacific communities underestimate the personal safety risks posed by AI.

Process and Methods

• Ineffective Content Takedown: Meta failed to remove reported fake accounts and deepfakes promptly.
• Inefficient Reporting Systems: Victims repeatedly reported fake accounts but they remained online.

Regulatory Environment

• Outdated Cybercrime Laws: Existing legal frameworks failed to specifically criminalize AI deepfakes.
• Lagging Legal Frameworks: Pacific countries' laws are still catching up to evolving AI crimes.

Information quality

• Classification confidence: High
• Reason for confidence: The report provides clear, firsthand accounts from the primary victim, Jennifer Baing, and official statements from the PNG Assistant Commissioner of Police regarding the rise of AI-related cybercrime. The details of the scam, the platform used (Facebook), and the real-world harms (reputational, psychological, and physical) are well-documented.
• Ambiguities identified: The specific AI models or platforms used by the scammers to generate the deepfakes are not identified.

The incident highlights the growing threat of AI-generated deepfakes used for financial fraud and non-consensual sexual harassment in Papua New Guinea. The societal impact is substantial, with police reporting multiple suicides among young female victims of synthetic explicit imagery, emphasizing the urgent need for updated cybercrime frameworks.

• Overall national security impact: Substantial
• Scope: Single nation
• Primary target: Papua New Guinea
• Alleged perpetrator: Unknown

Threat characteristics

• Imminence: Near-term. The threat of AI-enabled fraud and harassment is ongoing and requires continuous monitoring and regulatory response.
• Autonomy: Human-controlled. The AI tools were directly operated by human scammers to generate specific fraudulent and explicit images.
• Novelty: Evolved capability. While cyber fraud is established, the ease of generating realistic synthetic media representing specific individuals is an evolved capability.

Impact by dimension

• Physical security: Negligible. No kinetic threats, physical attacks, or critical infrastructure compromise were reported in this incident.
• Information security: Minor. The incident involves localized deepfake scams rather than coordinated state-sponsored information warfare or intelligence compromise.
• Sovereignty: Negligible. No direct threat to state authority or current government operations, though a future political candidate expressed concerns regarding election integrity.
• Economic security: Minor. Financial fraud occurred through fake giveaways targeting individuals, but it does not threaten national economic stability or strategic industries.
• Societal stability: Substantial. The proliferation of non-consensual AI-generated explicit images has caused severe psychological distress, leading to multiple reported suicides among young women.