most citedSemantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CR2026

Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines

Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +2

Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-augmented generation (RAG), and multi-…

cs.CR2026

Security Engineering of OpenClaw: Analyzing Attack Surface Expansion and Trust-Boundary Violations

Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1

Agentic large language model (LLM) systems can now execute actions, not only produce text. When model outputs trigger privileged operations such as shell commands, browser automati…

cs.CR2026

Game-Theoretic Multi-Agent Control for Robust Contextual Reasoning in LLMs

Saeid Jamshidi, Amin Nikanjam, Arghavan Moradi Dakhel +2

Large Language Models (LLMs) in multi-turn interactions maintain evolving context rather than generating isolated responses, making them vulnerable to prompt-injection and context-…

cs.CR2026

Hallucination Cascade: Analyzing Error Propagation in Multi-Agent LLM Systems

Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1

Large Language Models (LLMs) generate fluent text but remain vulnerable to hallucinations, producing unsupported, inconsistent, and factually incorrect claims. Most prior work trea…

cs.CR20261 cited

Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation

Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1

The Model Context Protocol (MCP) enables Large Language Models (LLMs) to interact with external tools via tool descriptors, thereby extending their capabilities for task execution,…

cs.AI2026

Adversarial Moral Stress Testing of Large Language Models

Saeid Jamshidi, Foutse Khomh, Arghavan Moradi Dakhel +3

Evaluating the ethical robustness of large language models (LLMs) deployed in software systems remains challenging, particularly under sustained adversarial user interaction. Exist…