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AI incident #1077 ·

FBI Reports Ongoing Vishing and Smishing Campaign Allegedly Targeting Government Officials Using Purportedly AI-Generated Voices

Open on the AI Incident Database 3 news reports Snapshot 7 Sep 2026

What happened

According to a May 15, 2025 public alert from the FBI and IC3, malicious actors have been using purported AI-generated voice messages and smishing tactics since April 2025 to impersonate senior U.S. officials. The campaign reportedly targets government personnel and their contacts to gain access to personal or official accounts. The FBI warns the scheme may involve credential theft and social engineering, with AI voice cloning used to increase believability.

Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.

News reports (3)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

  1. Alert Number: I-051525-PSA May 15, 2025 Senior US Officials Impersonated in Malicious Messaging Campaign
    ic3.gov · Federal Bureau of Investigation, FBI · AIID #5226
  2. FBI warns of fake texts, deepfake calls impersonating senior U.S. officials
    cyberscoop.com · Derek B. Johnson · AIID #5315
  3. Impersonator breached Chief of Staff Susie Wiles’s phone, Trump says
    washingtonpost.com · Vivian Ho · AIID #5275

Who was involved

Alleged deployer
Scammers
Alleged harmed party
United States State Government Officials, United States Federal Government Officials, Former United States Government Officials, Family And Friends Of United States Government Officials

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
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Sectors
—
Countries
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Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

  • Impersonation/identity theft

    "Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • IP/copyright loss

    "IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Dehumanisation/objectification

    "Dehumanisation/objectification - Use or misuse of a technology system to depict and/or treat people as not human, less than human, or as objects."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Defamation/libel/slander

    "Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Financial and business

    "Financial and Business - Use or misuse of a technology system in a manner that damages the financial interests of an individual or group, or which causes strategic, operational, legal or financial harm to a business or...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Cheating/plagiarism

    "Cheating/plagiarism - Use of another person’s or group’s words or ideas without consent and/or acknowledgement."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Cybersecurity

    "LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  • Domain-Specific Misuses

    "Improvements in LLMs may exert greater pressure to apply LLMs to various domains, such as health and education (Eloundou et al., 2023). Crude efforts to use LLMs in such domains, however, may incur harm and should be di...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

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