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Autores principales: Chhabra, Anshuman, Datta, Shrestha, Nahin, Shahriar Kabir, Mohapatra, Prasant
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2510.23883
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author Chhabra, Anshuman
Datta, Shrestha
Nahin, Shahriar Kabir
Mohapatra, Prasant
author_facet Chhabra, Anshuman
Datta, Shrestha
Nahin, Shahriar Kabir
Mohapatra, Prasant
contents Agentic AI systems powered by large language models (LLMs) and endowed with planning, tool use, memory, and autonomy, are emerging as powerful, flexible platforms for automation. Their ability to autonomously execute tasks across web, software, and physical environments creates new and amplified security risks, distinct from both traditional AI safety and conventional software security. This survey outlines a taxonomy of threats specific to agentic AI, reviews recent benchmarks and evaluation methodologies, and discusses defense strategies from both technical and governance perspectives. We synthesize current research and highlight open challenges, aiming to support the development of secure-by-design agent systems.
format Preprint
id arxiv_https___arxiv_org_abs_2510_23883
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
Chhabra, Anshuman
Datta, Shrestha
Nahin, Shahriar Kabir
Mohapatra, Prasant
Artificial Intelligence
Agentic AI systems powered by large language models (LLMs) and endowed with planning, tool use, memory, and autonomy, are emerging as powerful, flexible platforms for automation. Their ability to autonomously execute tasks across web, software, and physical environments creates new and amplified security risks, distinct from both traditional AI safety and conventional software security. This survey outlines a taxonomy of threats specific to agentic AI, reviews recent benchmarks and evaluation methodologies, and discusses defense strategies from both technical and governance perspectives. We synthesize current research and highlight open challenges, aiming to support the development of secure-by-design agent systems.
title Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
topic Artificial Intelligence
url https://arxiv.org/abs/2510.23883