Cyberspace risks (Risks of information leakage due to improper usage)

Classification

Domain

2. Privacy & Security

Subdomain

2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information

Causal entity

Human

Intent

Unintentional

Timing

Post-deployment

Subdomain definition: AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or loss of confidential intellectual property.

Real-world incidents in this subdomain

• 27 Feb 2026Meta AI Smart Glasses Reportedly Routed Intimate Imagery to Reviewers at Kenyan Contractor Sama Before Meta Ended Contract
• 19 Feb 2026Grok Reportedly Disclosed Adult Performer Siri Dahl's Legal Name and Birthdate, Allegedly Contributing to Doxxing and Harassment
• 23 Jan 2026NPR Host David Greene Alleged Google's NotebookLM Replicated His Voice Without Consent, Prompting Lawsuit
• 10 Jan 2026Border Patrol Agent Allegedly Claimed Facial Recognition Identified Minneapolis ICE Observer and Global Entry Was Reportedly Revoked Three Days Later
• 4 Dec 2025Perplexity AI Reportedly Accused in Federal Lawsuit of Purported Copyright Infringement and False Attribution of Chicago Tribune Content
• 19 Nov 2025Secret Desires AI Platform Reportedly Exposed Nearly Two Million Sensitive Images in Cloud Storage Leak

How other frameworks describe this risk

• Risks to privacy

  International Scientific Report on the Safety of Advanced AI (Bengio2024)

• Risks to privacy

  International AI Safety Report 2025 (Bengio2025)

• Privacy Leakage

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Private Training Data

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Memorization in LLMs

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Association in LLMs

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Privacy Leakage

  Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

• Privacy and regulation violations

  Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)

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