TrendAI Presents Research on Agentic Cybercrime and EV Charging Security at RSAC 2026

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Summary

At RSAC 2026, TrendAI researchers discussed proof-of-concept agentic AI cybercrime and security risks at interfaces in EV charging infrastructure, recommending NIST IR 8473 as a unifying framework for vendors.

Key points

  • TrendAI researchers described a proposed criminal AI architecture using specialized agents for tasks such as reconnaissance, social engineering, and extortion.
  • Proof-of-concept examples showed agentic systems automating ransomware data analysis, personalized extortion messages, and large-scale social engineering.
  • A session drawing on Pwn2Own Automotive and VicOne research highlighted vulnerabilities in electric vehicle supply equipment and risks at system interfaces.
  • The speakers recommended that EV charging vendors adopt NIST IR 8473 as a framework for reducing systemic cybersecurity risk.
  • The article calls for secure-by-design engineering, ongoing vulnerability research, and collaboration across the mobility ecosystem.

Article Details

Event Type
TrendAI™ Research presented two sessions at RSAC 2026 on agentic AI-driven cybercrime and cybersecurity risks in electric vehicle charging infrastructure.
Impact
The sessions described proof-of-concept agentic systems capable of automating ransomware data analysis, personalized extortion messages, and large-scale social engineering, and highlighted exploitable vulnerabilities and systemic security risks at interfaces across the EV charging ecosystem. No specific real-world victim impact was reported.

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