Phishing remains one of the most persistent and effective attack vectors in cybersecurity, with attackers constantly refining their methods to bypass modern defenses. Recent research highlights new techniques, including file-based evasion, AI-driven threats, and IoT-specific risks, which challenge traditional security measures1. This article examines these emerging threats, their technical underpinnings, and actionable mitigation strategies.
Executive Summary for Security Leaders
Phishing attacks have evolved beyond traditional email scams, leveraging advanced file formats, cloud storage, and AI to bypass filters. Key trends include SVG/PDF exploits, dynamic payloads via OneDrive links, and IoT device targeting. Below is a high-level overview:
- File-Based Evasion: Malicious scripts embedded in SVG/PDF files bypass email filters1.
- AI-Driven Threats: Tools like WormGPT generate hyper-personalized lures2.
- IoT Risks: 98% of IoT traffic lacks encryption, enabling credential theft4.
- Mitigation: AI email filters, zero-trust architectures, and STRIDE modeling for IoT5.
Technical Breakdown of Emerging Phishing Techniques
Attackers are exploiting trusted file formats to evade detection. SVG files with Base64-encoded JavaScript and PDF annotations are increasingly used to deliver malware1. These methods bypass static email scans by hiding malicious code within seemingly benign files. For example, MHT files archived in OpenXML formats have been observed in QR code phishing campaigns1.
Cloud storage platforms like OneDrive are also abused. Attackers send legitimate-looking links that load phishing URLs only after delivery, evading pre-delivery scans1. This technique, known as dynamic payload delivery, relies on time-delayed malicious content activation.
AI and IoT: Expanding the Attack Surface
AI tools such as WormGPT and ChatGPT are automating spear-phishing campaigns, generating convincing lures that mimic legitimate communications2. Deepfake audio is another growing threat, particularly in business email compromise (BEC) scams where attackers impersonate executives2.
IoT devices present unique vulnerabilities. Research indicates that 98% of IoT traffic is unencrypted, making it easy for attackers to intercept credentials4. Smart homes and autonomous vehicles are particularly at risk, with spoofed sensor data (e.g., LiDAR/camera inputs) disrupting navigation systems4.
Mitigation Strategies
Technical controls like AI-powered email filters can detect behavioral anomalies in dynamic payloads5. Zero-trust architectures, including MFA and FIDO2 passwordless authentication, reduce reliance on static credentials5.
For IoT, STRIDE threat modeling helps identify vulnerabilities pre-deployment. Below is a summary of IoT-specific threats and mitigations:
| Threat Type | Example | Mitigation |
|---|---|---|
| Spoofing | Fake sensor data in autonomous vehicles | TLS/PSK for device authentication |
| Information Disclosure | Eavesdropping on IoT traffic | Encrypt device-to-gateway communications |
Human-centric measures, such as regular phishing simulations and sector-specific training (e.g., QR code scanning tools for finance), are equally critical5.
Conclusion
Phishing techniques continue to evolve, demanding adaptive defenses. Organizations must combine technical controls like AI filters with continuous training and IoT-specific threat modeling. As attackers leverage AI and IoT vulnerabilities, proactive measures will be essential to mitigate risks.
References
- “Emerging Phishing Techniques: New Threats and Attack Vectors,” Intezer, 2025.
- “AI Is Changing Phishing Tactics,” VIPRE, 2025.
- “Is Your Email Security Up to Date Against Emerging Phishing Threats?,” BitLyft, 2025.
- “STRIDE Threat Modeling for IoT Devices,” MDPI Sensors Journal, 2021.
- “Phishing Types and Defensive Measures,” Perception Point.
