Targeted Phone-line Attacks: Automated Social Engineering & Manipulation using Public Information
Advanced AI-driven voice emulation represents a significant security threat when combined with automated calling systems. Our demonstration showcases how malicious actors could leverage state-of-the-art text-to-speech (TTS) technology and Large Language Models (LLMs) to generate synthetic voices capable of conducting human-like conversations at scale.
This proof-of-concept system demonstrates the full attack chain: from scraping publicly available business data across targeted areas, to aggregating context from sources like Google and Yelp, to conducting real-time adaptive conversations. The platform can automatically place calls to businesses and government offices, highlighting the urgent need for protective measures against such potential attacks.
Audio Demonstrations
Listen to examples of AI-generated voice calls that demonstrate the capabilities and potential risks of this technology:
Emergency Services Demo
Demonstration of potential attacks on emergency service lines
Technical Capabilities
- Real-Time Voice Synthesis: Integration of ElevenLabs' text-to-speech API with OpenAI's models enables instant, dynamic voice generation with human-like qualities.
- Automated Intelligence Gathering: Sophisticated backend system that builds detailed target profiles by aggregating data from multiple public sources.
- Scalable Infrastructure: End-to-end pipeline utilizing Twilio for mass deployment of convincing automated calls.
- Conversation Monitoring: Real-time transcript analysis for adaptive dialogue management and interaction optimization.
Social Engineering Risks
- Communication Channel Flooding: Potential for thousands of automated calls to overwhelm businesses, financial institutions, or government offices across targeted areas.
- Public Perception Manipulation: Near-perfect voice imitation enabling spread of disinformation through trusted voices.
- Critical Infrastructure Exploitation: Potential disruption of essential services and emergency communication systems.
- Democratic Process Interference: Risk of overwhelming Congressional offices with fake constituent calls, distorting policy feedback channels.
Policy Recommendations
- Mandatory Watermarking: Implement digital watermarking for synthetic voices to ensure traceability.
- Verification Protocols: Develop robust systems to verify voice communication authenticity, especially in critical sectors.
- Regulatory Framework: Establish comprehensive legal measures to deter and penalize malicious use of AI voice technology.
- Balanced Approach: Create policies that protect against harmful uses while supporting beneficial AI development.
Demo Format
During the Congressional Exhibition on Advanced AI, attendees will experience:
- Pre-Recorded Calls: Real-world examples of AI-generated calls placed to volunteering businesses, illustrating how the system scrapes details (e.g., hours of operation, basic info from Yelp) and then initiates convincing, time-wasting conversations.
- Live Demonstration: When feasible, a real-time call to a willing test business will show the platform's full capabilities—from data gathering to automated phone dialing.
- Interactive Explanation: Technical walkthrough of data scraping, neural voice generation, and the low-latency response pipeline. We will also discuss potential expansions, such as targeting congressional offices for demonstration purposes.
Contact Information
For inquiries about this demonstration, please contact David Turturean at davidct@mit.edu or Gatlen Culp at gculp@mit.edu