What Happened
Cybersecurity researchers have disclosed details of a phishing-as-a-service (PhaaS) platform built to strip Apple's Activation Lock from stolen devices, using rented AI voice agents that call theft victims posing as Apple Support and ask for their device passcode. SOCRadar Threat Research Unit (STRU) said the platform, which it tracks as AnonyMousKIT, is credit-metered and drives lures across
Why It Matters
Report facts: Researchers describe a phishing-as-a-service platform, AnonyMousKIT, that rents AI voice agents posing as Apple Support to call owners of stolen devices and socially engineer them into revealing passcodes and 2FA codes, enabling removal of Apple’s Activation Lock. The service is credit‑metered and industrializes voice-based impersonation attacks. RealGround analysis: This demonstrates malicious operational use of AI agents to automate high‑credibility social engineering at scale, increasing success rates against non-technical users. Organizations should test and harden incident-response and account-recovery workflows against AI-powered voice phishing, enforce strong policies on never sharing passcodes/2FA over calls, and regularly red-team support processes to detect and mitigate similar AI-augmented scams.
RealGround Analysis
This signal maps to malicious AI use. Organizations using AI agents, LLM APIs, SaaS integrations, or sensitive data workflows should review whether this class of issue could create unauthorized tool execution, data leakage, weak approval gates, or unmanaged supply-chain exposure.
Recommended Actions
- Restrict AI agent tool permissions and production write paths.
- Review sensitive data access across prompts, logs, embeddings, memory, and SaaS integrations.
- Add human approval workflows for high-impact or state-changing actions.
- Run prompt injection and indirect prompt injection tests against affected workflows.
- Document the owner, control gap, and remediation deadline for this risk class.
Source
https://thehackernews.com/2026/08/fake-apple-support-ai-calls-target.html
