11 citations · 25 across the 9 of their papers we have counts for
9 papers
Sleeper Channels and Provenance Gates: Persistent Prompt Injection in Always-on Autonomous AI Agents
Narek Maloyan, Dmitry Namiot
Always-on AI agents (OpenClaw, Hermes Agent) run as a single persistent process under the owner's identity, folding messaging, memory, self-authored skills, scheduling, and shell i…
Breaking the Protocol: Security Analysis of the Model Context Protocol Specification and Prompt Injection Vulnerabilities in Tool-Integrated LLM Agents
Narek Maloyan, Dmitry Namiot
The Model Context Protocol (MCP) has emerged as a de facto standard for integrating Large Language Models with external tools, yet no formal security analysis of the protocol speci…
Prompt Injection Attacks on Agentic Coding Assistants: A Systematic Analysis of Vulnerabilities in Skills, Tools, and Protocol Ecosystems
Narek Maloyan, Dmitry Namiot
The proliferation of agentic AI coding assistants, including Claude Code, GitHub Copilot, Cursor, and emerging skill-based architectures, has fundamentally transformed software dev…
Investigating the Vulnerability of LLM-as-a-Judge Architectures to Prompt-Injection Attacks
Narek Maloyan, Bislan Ashinov, Dmitry Namiot
Large Language Models (LLMs) are increasingly employed as evaluators (LLM-as-a-Judge) for assessing the quality of machine-generated text. This paradigm offers scalability and cost…
Adversarial Attacks on LLM-as-a-Judge Systems: Insights from Prompt Injections
Narek Maloyan, Dmitry Namiot
LLM as judge systems used to assess text quality code correctness and argument strength are vulnerable to prompt injection attacks. We introduce a framework that separates content…
Prompt Injection Attacks in Defended Systems
Daniil Khomsky, Narek Maloyan, Bulat Nutfullin
Large language models play a crucial role in modern natural language processing technologies. However, their extensive use also introduces potential security risks, such as the pos…
Trojan Detection in Large Language Models: Insights from The Trojan Detection Challenge
Narek Maloyan, Ekansh Verma, Bulat Nutfullin +1
Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, but their vulnerability to trojan or backdoor attacks poses significant security risks. T…
DN at SemEval-2023 Task 12: Low-Resource Language Text Classification via Multilingual Pretrained Language Model Fine-tuning
Daniil Homskiy, Narek Maloyan
In recent years, sentiment analysis has gained significant importance in natural language processing. However, most existing models and datasets for sentiment analysis are develope…
DIALOG-22 RuATD Generated Text Detection
Narek Maloyan, Bulat Nutfullin, Eugene Ilyushin
Text Generation Models (TGMs) succeed in creating text that matches human language style reasonably well. Detectors that can distinguish between TGM-generated text and human-writte…