Real-world risks (Risks of using AI in illegal and criminal activities)

Classification

Domain

4. Malicious actors

Subdomain

4.3 Fraud, scams, and targeted manipulation

Causal entity

Human

Intent

Intentional

Timing

Post-deployment

Subdomain definition: Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.

Real-world incidents in this subdomain

• 31 May 2026Italian Mediaset Journalist Safiria Leccese's Image Was Reportedly Used in a Purportedly AI-Generated Fake Loan Scam
• 24 May 2026Scammers Reportedly Used AI-Cloned Daughter's Voice to Defraud Bay Area Mother in Fake Kidnapping Call
• 19 May 2026Texas Man Arturo Hernandez Allegedly Published AI-Generated Deepfake Pornography Depicting Women in TAKE IT DOWN Act Case
• 5 May 2026Guelph, Ontario, Woman Reportedly Lost $14,000 in Purported Deepfake MrBeast Cryptocurrency Scam
• 4 May 2026Purportedly AI-Recreated Clips from Beastie Boys' 'Sabotage' Video Reportedly Appeared in FBI Promotional Video Posted by Kash Patel
• 28 Apr 2026Ahmedabad Aadhaar Fraud Racket Reportedly Used Purportedly AI-Generated Deepfakes to Change Businessman's Linked Mobile Number

How other frameworks describe this risk

• Impersonation/identity theft

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• IP/copyright loss

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• Dehumanisation/objectification

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• Defamation/libel/slander

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• Financial and business

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• Cheating/plagiarism

  A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

• Cybersecurity

  Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

• Domain-Specific Misuses

  Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Other entries from TC2602024

• AI's inherent safety risks Risk Category
• Risks from models and algorithms (Risks of explainability) Risk Sub-Category · 7.4
• Risks from models and algorithms (Risks of bias and discrimination) Risk Sub-Category · 1.1
• Risks from models and algorithms (Risks of robustness) Risk Sub-Category · 7.3
• Risks from models and algorithms (Risks of stealing and tampering) Risk Sub-Category · 2.2
• Risks from models and algorithms (Risks of unreliable output) Risk Sub-Category · 3.1
• Risks from models and algorithms (Risks of adversarial attack) Risk Sub-Category · 2.2
• Risks from data (Risks of illegal collection and use of data) Risk Sub-Category · 2.1
• Risks from data (Risks of improper content and poisoning in training data) Risk Sub-Category · 1.2
• Risks from data (Risks of unregulated training data annotation) Risk Sub-Category · 7.3
• Risks from data (Risks of data leakage) Risk Sub-Category · 2.1
• Risks from AI systems (Risks of exploitation through defects and backdoors) Risk Sub-Category · 2.2