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The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls
Voice honeypot measurement finds at least 26.9% of unwanted US inbound calls open with machine voices, 13.1% with fresh synthetic speech.
An interactive voice honeypot using language-model personas on real US numbers recorded 10,987 calls over 66 days, following the FCC's February 2024 ruling that AI-generated voices fall under the TCPA. Of 7,233 greeted calls, 13.8% opened with recordings replayed from other calls and 13.1% with fresh audio labeled synthetic, with replays making up 45% of the detector's flagged rate. Synthetic openings concentrated in lead-generation spam (33.8%) rather than fraud (21.1%), and only 0.44% of calls disclosed automation. Prevalence tracked how long a bait number had circulated, and campaigns outlasted their numbers, with one synthetic voice serving nine campaigns.
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Hackers Use LLMs to Generate Exploit Scripts and Automate Post-Exploitation Across Latin America
Unit 42 says Latin American attackers used LLMs to automate post-exploitation in campaigns hitting Mexican government, water utilities, and Brazilian financial firms.
Unit 42 identified two campaigns in Latin America whose operators used commercial LLMs (Claude, GPT-4.1) behind a self-hosted NextChat interface to generate and debug post-exploitation scripts. Cluster CL-CRI-1131 compromised a transportation organization, Mexican federal ministries, and water utilities in Mexico and Ecuador, using native Windows tools and Volume Shadow Copies to dump the SAM registry hive and NTDS.dit. Cluster CL-CRI-1163 targeted Brazilian financial organizations with job-themed phishing, custom RATs, and a Go-based reverse SOCKS5 tunneling utility called SockTz, with nine versions deployed within roughly two hours. Trend Micro tracks related AI-augmented activity as SHADOW-AETHER-040 and SHADOW-AETHER-064.
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