Holz, Thorsten
Max Planck Institute for Security and Privacy
7 papers on CoChatORCID 0000-0002-2783-1264
Most cited papers
- Verified
Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Greshake, K., Abdelnabi, S., Mishra, S., Endres, C., Holz, T., & Fritz, M. (2023) · Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 667
- Verified
Leveraging Frequency Analysis for Deep Fake Image Recognition
Frank, J., Eisenhofer, T., Schönherr, L., Fischer, A., Kolossa, D., & Holz, T. (2020) · arXiv
Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis
Cited by 390
- Verified
Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection
Greshake, K., Abdelnabi, S., Mishra, S., Endres, C., Holz, T., & Fritz, M. (2023) · arXiv
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 50
- Verified
AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images
Ricker, J., Assenmacher, D., Holz, T., Fischer, A., & Quiring, E. (2024) · The 27th International Symposium on Research in Attacks, Intrusions and Defenses
Misinformation and Its ImpactsDigital Media Forensic Detection
Cited by 22
- Verified
"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation
Höltervennhoff, S., Ricker, J., Raphael, M. M., Schwedes, C., Weil, R., Fischer, A., Holz, T., Schönherr, L., & Fahl, S. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Misinformation and Its ImpactsDigital Media Forensic Detection
Cited by 3
- Verified
ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?
Wang, Z., Schiller, N., Li, H., Narayana, S. S., Nasr, M., Carlini, N., Qi, X., Wallace, E., Bursztein, E., Invernizzi, L., et al. (2026) · arXiv
Security and Verification in ComputingAdversarial Robustness in Machine Learning
Cited by 3
- Verified
A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory
Wei, Q., Yang, T., Wang, Y., Li, X., Li, L., Yin, Z., Zhan, Y., Holz, T., Lin, Z., & Wang, X. (2025) · arXiv
Adversarial Robustness in Machine LearningSecurity and Verification in Computing
Cited by 1
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