Trend Micro forecasts deepfake-powered malicious digital twins and hyper-personalized AI attacks in 2025
Trend Micro published its 2025 security predictions report, The Easy Way In/Out: Securing The Artificial Future, warning that highly customized, AI-powered attacks will supercharge scams, phishing and influence operations in 2025 and beyond. The central prediction is the emergence of malicious "digital twins": breached or leaked PII used to train an LLM to mimic a victim's or employee's knowledge, personality and writing style. Combined with deepfake audio/video and compromised biometric data, these could enable identity fraud or "honeytrap" attacks on friends, colleagues or family. The report also expects attackers to adapt to EDR advances and to target enterprise AI adoption. This is a vendor forecast, not a report of an observed incident.
Technical Details
- AI-enabled fraud at scale: enhanced BEC/BPC and "fake employee" scams, identification and romancing of pig butchering victims before handoff to a human operator using an LLM "personality filter", improved OSINT gathering, and authentic-seeming social media personas for mis/disinformation and scams.
- Enterprise AI risks: exploitation and hijacking of AI agents to perform harmful or unauthorized actions, unintended GenAI information leakage, and benign or malicious resource consumption by AI agents leading to denial of service.
- Vulnerability trends: memory corruption bugs, vulnerability chains, API-targeting exploits, older flaws such as XSS and SQL injection, and single flaws that ripple across many models and manufacturers (e.g. a connected vehicle ECU).
- EDR evasion: kill chains through systems without EDR (cloud, mobile, edge, IoT), disabling AV/EDR, BYOVD techniques, shellcode hidden in inconspicuous loaders, and redirecting Windows subsystem execution. The result is faster attacks with fewer kill chain steps that are harder to detect.
Remediation
- Adopt a risk-based approach with centralized asset identification and risk prioritization.
- Use AI for threat intelligence, asset profiling, attack path prediction and remediation guidance.
- Update user training and awareness for AI-enabled cybercrime.
- Monitor and secure AI technology, including input/response validation and action validation.
- For LLM security, harden sandboxes, enforce strict data validation and deploy multi-layered defenses against prompt injection.
- Understand supply chain position, address vulnerabilities in public-facing servers and layer defenses inside internal networks.
- Ensure end-to-end visibility into AI agents and use attack path prediction for cloud threats.
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Trend Micro forecasts deepfake-powered malicious digital twins and hyper-personalized AI attacks in 2025
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Trend Micro published its 2025 security predictions report, The Easy Way In/Out: Securing The Artificial Future, warning that highly customized, AI-powered attacks will supercharge scams, phishing and influence operations in 2025 and beyond. The central prediction is the emergence of malicious "digital twins": breached or leaked PII used to train an LLM to mimic a victim's or employee's knowledge, personality and writing style. Combined with deepfake audio/video and compromised biometric data, these could enable identity fraud or "honeytrap" attacks on friends, colleagues or family. The report also expects attackers to adapt to EDR advances and to target enterprise AI adoption. This is a vendor forecast, not a report of an observed incident.
Technical Details
- AI-enabled fraud at scale: enhanced BEC/BPC and "fake employee" scams, identification and romancing of pig butchering victims before handoff to a human operator using an LLM "personality filter", improved OSINT gathering, and authentic-seeming social media personas for mis/disinformation and scams.
- Enterprise AI risks: exploitation and hijacking of AI agents to perform harmful or unauthorized actions, unintended GenAI information leakage, and benign or malicious resource consumption by AI agents leading to denial of service.
- Vulnerability trends: memory corruption bugs, vulnerability chains, API-targeting exploits, older flaws such as XSS and SQL injection, and single flaws that ripple across many models and manufacturers (e.g. a connected vehicle ECU).
- EDR evasion: kill chains through systems without EDR (cloud, mobile, edge, IoT), disabling AV/EDR, BYOVD techniques, shellcode hidden in inconspicuous loaders, and redirecting Windows subsystem execution. The result is faster attacks with fewer kill chain steps that are harder to detect.
Remediation
- Adopt a risk-based approach with centralized asset identification and risk prioritization.
- Use AI for threat intelligence, asset profiling, attack path prediction and remediation guidance.
- Update user training and awareness for AI-enabled cybercrime.
- Monitor and secure AI technology, including input/response validation and action validation.
- For LLM security, harden sandboxes, enforce strict data validation and deploy multi-layered defenses against prompt injection.
- Understand supply chain position, address vulnerabilities in public-facing servers and layer defenses inside internal networks.
- Ensure end-to-end visibility into AI agents and use attack path prediction for cloud threats.