Description: A Telegram user or channel known as Torswats reportedly offered paid swatting services and uploaded recordings of false emergency calls using synthesized or computer-generated voices. Reported targets included high schools, private residences, streamers, businesses, and police departments; some calls prompted lockdowns, searches, or armed law-enforcement responses. The exact voice-generation tool was not identified.
Entities
View all entitiesAlleged: Unknown deepfake technology developers and Unknown voice cloning technology developers developed an AI system deployed by Torswats, which harmed Your CBD Store , University of Pittsburgh Police Department , Phillipsburg High School , Hempstead High School , Dubuque Police Department , Bellefonte Area High School , students and Educational communities.
Alleged implicated AI systems: Unknown deepfake technology , Unknown voice cloning technology and Telegram
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
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“Hello, I just committed a crime and I want to confess,” a panicked sounding man said in a call to a police department in February. “I’ve placed explosives inside a local school,’ the man continued.
“You did what?!” the operator responded.
…Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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