Descripción: A study by Indiana University researchers uncovered widespread misuse of large language models (LLMs) for cybercrime. Cybercriminals, according to that study, use LLMs like OpenAI's GPT-3.5 and GPT-4 to create malware, phishing scams, and scam websites. These models are available on underground markets, often bypassing safety checks through jailbreaking. Named malicious LLMs are BadGPT, XXXGPT, Evil-GPT, WormGPT, FraudGPT, BLACKHATGPT, EscapeGPT, DarkGPT, and WolfGPT.
Entidades
Ver todas las entidadesAlleged: OpenAI developed an AI system deployed by Cybercriminals , BadGPT , XXXGPT , Evil-GPT , WormGPT , FraudGPT , BLACKHATGPT , EscapeGPT , DarkGPT y WolfGPT, which harmed internet users , Organizations y Individuals targeted by malware.
Estadísticas de incidentes
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
Informes del Incidente
Cronología de Informes
Despite the hype around them, readers of Tech Policy Press are well aware that the advance of large language models (LLMs) and their various applications-- ranging from chatbots and coding assistants to recommendation systems-- has raised v…
The internet, a vast and indispensable resource for modern society, has a darker side where malicious activities thrive.
From identity theft to sophisticated malware attacks, cyber criminals keep coming up with new scam methods.
Widely avai…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.
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