Description: 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.
Entities
View all entitiesAlleged: OpenAI developed an AI system deployed by Cybercriminals , BadGPT , XXXGPT , Evil-GPT , WormGPT , FraudGPT , BLACKHATGPT , EscapeGPT , DarkGPT and WolfGPT, which harmed internet users , Organizations and Individuals targeted by malware.
Incident Stats
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
Incident Reports
Reports Timeline
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…
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
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