ASTRIDE: A Security Threat Modeling Platform for Agentic-AI Applications
Eranga Bandara, Amin Hass, Ross Gore, Sachin Shetty, Ravi Mukkamala, Safdar H. Bouk, Xueping Liang, Ng Wee Keong, Kasun De Zoysa, Aruna Withanage, Nilaan Loganathan

TL;DR
ASTRIDE is an automated threat modeling platform tailored for AI agent systems, extending traditional frameworks with AI-specific threats and leveraging vision-language models and reasoning LLMs for end-to-end analysis.
Contribution
It introduces ASTRIDE, the first framework to extend STRIDE with AI-specific threats and automate threat modeling using vision-language models and reasoning LLMs.
Findings
Provides accurate threat analysis for AI agent systems
Scalable and explainable threat modeling process
First to automate diagram-driven threat modeling for AI agents
Abstract
AI agent-based systems are becoming increasingly integral to modern software architectures, enabling autonomous decision-making, dynamic task execution, and multimodal interactions through large language models (LLMs). However, these systems introduce novel and evolving security challenges, including prompt injection attacks, context poisoning, model manipulation, and opaque agent-to-agent communication, that are not effectively captured by traditional threat modeling frameworks. In this paper, we introduce ASTRIDE, an automated threat modeling platform purpose-built for AI agent-based systems. ASTRIDE extends the classical STRIDE framework by introducing a new threat category, A for AI Agent-Specific Attacks, which encompasses emerging vulnerabilities such as prompt injection, unsafe tool invocation, and reasoning subversion, unique to agent-based applications. To automate threat…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdversarial Robustness in Machine Learning · Multi-Agent Systems and Negotiation · Explainable Artificial Intelligence (XAI)
