Description: AI-generated deepfakes were reportedly used in the "HTML/Nomani" phishing campaign to mimic legitimate platforms like booking services and lured victims into investment scams. These scams allegedly leveraged realistic fake content to deceive users on social media for the purposes of financial fraud. This campaign was part of the rising misuse of AI in cybercrime during the second half of 2024.
Editor Notes: For more information, see the full ESET threat report, including how Lumma Stealer malware reportedly surged in targeting macOS and mobile users, and how RansomHub ransomware allegedly employed AI-driven techniques to enhance evasion and effectiveness, at the following URL: https://web-assets.esetstatic.com/wls/en/papers/threat-reports/eset-threat-report-h22024.pdf. See also: Incident 870: Meeten Malware Campaign Reportedly Undermines Web3 Security Using AI-Legitimized Branding.
Entités
Voir toutes les entitésAlleged: Unknown deepfake technology developers developed an AI system deployed by scammers , HTML/Nomani et Fraudsters, which harmed Phishing victims , Booking.com customers , Booking.com , Airbnb users et Airbnb.
Systèmes d'IA présumés impliqués: Deepfake generation tools , AI-powered cryptostealers et AI-enhanced ransomware systems
Statistiques d'incidents
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
4.3. Fraud, scams, and targeted manipulation
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Malicious Actors & Misuse
Entity
Which, if any, entity is presented as the main cause of the risk
Human
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Intentional
Rapports d'incidents
Chronologie du rapport
Les chercheurs en cybersécurité attirent l'attention sur un nouveau type d'escroquerie à l'investissement qui s'appuie sur une combinaison de publicité malveillante sur les réseaux sociaux, de publications de marque d'entreprise et de témoi…
Variantes
Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.
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