Dozens of Dutch Women, Including Politicians and Public Figures, Were Reportedly Targeted With AI-Manipulated Deepfake Pornography

Dutch reporting in March 2024 identified roughly 70–80 prominent women, including politicians, presenters, athletes, celebrities, and members of the royal family, as reportedly depicted in pornographic deepfake videos made by using AI to place their faces on performers' bodies. Some videos had more than 100,000 views. Several women said they had not known the videos existed and filed or planned police reports.

Risk classification

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

The incident involves the creation of humiliating sexual imagery targeting specific female public figures for targeted humiliation and financial gain.

Additional risk subdomains

• 1.2 Exposure to toxic content: The synthetic pornographic videos expose internet users and the victims themselves to highly toxic, non-consensual sexual content.

Causal factors

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

The harm was caused by human actors intentionally using deployed AI deepfake generation tools to create and distribute non-consensual pornographic videos of specific victims.

EU AI Act risk tier

• Risk tier: 3 Limited Risk

Limited Risk: The report describes the creation of deepfakes, which are explicitly classified under the EU AI Act as posing a moderate risk requiring transparency obligations.

AI system and alleged parties

• AI system: unspecified
• AI purpose: Deepfake Video Generation; Deepfake Image Generation
• Behaviour type: Tool
• Alleged developer: Synthetic video generation technology developers, Synthetic media generation technology developers, Deepfake technology developers, AI face-swapping technology developers
• Alleged deployer: Synthetic media creators, Deepfake website operators, Deepfake creators
• Alleged harmed parties: Women and girls, Women, Victims of non-consensual deepfakes, Victims of deepfake abuse, Sylvana IJsselmuiden, Simone Simons, Sharon Dijksma, Sandra Beckerman, Public figures and celebrities depicted in explicit AI images, Public figures, Privacy, Politicians in the Netherlands, Politicians, Olcay Gulsen, Noa Vahle, Mirjam Bikker, Leontine Ruiters, Jennifer Hoffman, Individuals whose likenesses were used without consent, Hélène Hendriks, Epistemic integrity, Eline Vedder, Celebrities, Caroline van der Plas

Harm severity

Severity ratings are based on this scale.

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 Substantial, indirect Minor
• Differential treatment: direct Minor, indirect Minor
• Civil rights: direct Minor, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Minor, indirect Negligible
• Psychological: direct Minor, indirect Negligible
• Epistemic: direct Minor, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Malicious content

Reported: Yes, the reports describe the creation and spread of non-consensual deepfake pornographic videos.

Directly caused: Dozens of deepfake pornographic videos of 70-80 Dutch female public figures were created and uploaded to Platform S, which receives 13 million monthly visitors.

Indirectly caused: Comments under the videos encouraged uploaders and suggested new victims, spreading toxic behavior.

Inferred additional harm: Thousands of viewers exposed to non-consensual sexual content across multiple mirror sites.

Differential treatment

Reported: Yes, the reports highlight that this is a form of sexual violence and harassment targeting women specifically.

Directly caused: Female politicians, artists, and athletes were disproportionately targeted with sexualized deepfakes compared to their male counterparts.

Indirectly caused: The targeting reinforces gender-based harassment and creates a hostile online environment for women in public roles.

Inferred additional harm: Increased systemic barriers and harassment for women entering public life or politics due to the threat of sexualized deepfakes.

Civil rights

Reported: Yes, the reports describe violations of personal integrity and sexual safety.

Directly caused: The right to personal dignity, self-determination, and protection from sexual harassment was violated for the 70-80 victims.

Inferred additional harm: Broader chilling effect on women's freedom of expression and participation in public life.

Privacy

Reported: Yes, the reports mention filing complaints with the Autoriteit Persoonsgegevens (Data Protection Authority) for privacy violations.

Directly caused: The unauthorized use of the victims' faces and identities to generate sexual content.

Psychological

Reported: Yes, the reports explicitly describe psychological distress and feelings of violation among the victims.

Directly caused: Victims described the videos as feeling like 'digitale verkrachting' (digital rape) and causing significant shock, anxiety, and taking up a lot of time and energy to deal with.

Inferred additional harm: Widespread psychological trauma, anxiety, and reputational distress among the 70-80 targeted women, many of whom had to seek security advice or legal help.

Epistemic

Reported: Yes, the creation of highly realistic fake videos that depict individuals doing things they never did.

Directly caused: Highly realistic deepfake videos created a false reality where public figures appeared to participate in pornographic acts.

Inferred additional harm: General erosion of trust in video evidence and digital media.

People affected

• Occurrences reported: 1
• People reportedly harmed: 80
• People reportedly exposed: 80

Potential causes

Management

• Platform Anonymity Policies: Platforms advise uploaders to stay anonymous to avoid legal consequences.
• Monetization of Exploitation: Payment processors and sites historically facilitated deepfake monetization.

Technology

• Advanced AI Face Swapping: AI algorithms convincingly paste faces onto explicit video bodies.
• Proliferation of Deepfake Apps: Easy-to-use applications allow anyone to generate realistic deepfakes.

Data Inputs

• Publicly Accessible Photos: Abundant online images of public figures provide training data for AI.

Human Factors

• Uploader Financial Motivation: Creators are incentivized by platform payouts tied to video view counts.
• Audience Demand and Sharing: Viewer consumption and requests drive the creation of new deepfakes.
• Dismissal of Real Harm: Perpetrators justify deepfakes as harmless fantasy rather than abuse.

Process and Methods

• Slow Law Enforcement Response: Victims face months of police silence after filing official complaints.
• Ineffective Takedown Procedures: Lack of rapid administrative orders prevents quick removal of videos.
• Advice to Remain Silent: Initial advice to stay quiet to avoid driving traffic delayed action.

Regulatory Environment

• Offshore Hosting Havens: Platforms register in jurisdictions like Nevis to evade legal prosecution.
• Inadequate Law Enforcement: Existing laws against deepfakes are not actively or quickly enforced.

Information quality

• Classification confidence: High
• Reason for confidence: The reports are highly detailed, consistent, and come from reputable Dutch news outlets. They explicitly identify the victims, the platform, the technology used, and the societal/legal responses.
• Ambiguities identified: The exact AI models or apps used by the creators are not named.

Dozens of Dutch female public figures, including MPs and ministers, were targeted with AI-generated non-consensual deepfake pornography hosted on an offshore platform. While not a state-sponsored national security threat, the incident highlights how AI-enabled harassment can target state leadership, threaten democratic participation, and challenge law enforcement capabilities.

• Overall national security impact: Substantial
• Scope: Single nation
• Primary target: Netherlands
• Alleged perpetrator: Unknown

Threat characteristics

• Imminence: Long-term. Represents an ongoing capability and strategic concern regarding the weaponization of synthetic media against public figures.
• Autonomy: Human-controlled. The AI tools were directly operated by human users to perform specific face-swapping tasks based on direct inputs.
• Novelty: Evolved capability. While non-consensual deepfakes are an established threat, the scale of targeting dozens of high-profile public figures simultaneously represents an evolved and highly coordinated harassment capability.

Impact by dimension

• Physical security: Negligible. No physical security threats or critical infrastructure disruptions were reported in connection with this incident.
• Information security: Minor. While involving deepfakes targeting public figures, the activity was driven by financial gain and harassment rather than a coordinated state-sponsored intelligence or disinformation campaign.
• Sovereignty: Minor. The harassment of female ministers and MPs caused personal distress and political debate, but did not compromise core government decision-making or state sovereignty.
• Economic security: Negligible. No significant threats to financial systems, strategic technologies, or economic security were identified.
• Societal stability: Substantial. The systematic targeting of dozens of female public figures and politicians violates human rights, erodes privacy, and threatens democratic participation by creating a hostile environment for women in public office.