Description: President Trump announced that White House Chief of Staff Susie Wiles had been impersonated via a phone breach involving AI-generated voice messages and spoofed texts. The attacker reportedly contacted high-profile individuals in her network while posing as Wiles. The incident is linked to a campaign identified by the FBI in April 2025, involving malicious actors using social engineering and AI to impersonate senior U.S. officials and gain access to sensitive information. See Incident 1077.
Editor Notes: This incident is a specific variant of Incident 1077: FBI Reports Ongoing Vishing and Smishing Campaign Allegedly Targeting Government Officials Using Purportedly AI-Generated Voices. This report is included in Incident 1077, but merits its own distinct incident ID archive as well.
Entities
View all entitiesAlleged: Unknown deepfake technology developer and Unknown voice cloning technology developer developed an AI system deployed by Unknown scammers and Unknown fraudsters, which harmed Susie Wiles and Susie Wiles's network.
Alleged implicated AI systems: Unknown voice cloning technology , Unknown deepfake technology , Vishing infrastructure , Smishing infrastructure , Mobile messaging networks and Account authentication systems
Incident Stats
Incident ID
1085
Report Count
1
Incident Date
2025-05-30
Editors
Daniel Atherton
Incident Reports
Reports Timeline
An impersonator breached the phone of White House Chief of Staff Susie Wiles, President Donald Trump said Friday, and pretended to be her in calls and messages received by her high-profile contacts.
Trump did not go into detail about the im…
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.
