Systems Security Foundations for Agentic Computing

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Christodorescu, Mihai, Fernandes, Earlence, Hooda, Ashish, Jha, Somesh, Rehberger, Johann, Chaudhuri, Kamalika, Fu, Xiaohan, Shams, Khawaja, Amir, Guy, Choi, Jihye, Choudhary, Sarthak, Palumbo, Nils, Labunets, Andrey, Pandya, Nishit V.
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914339065167872
author Christodorescu, Mihai
Fernandes, Earlence
Hooda, Ashish
Jha, Somesh
Rehberger, Johann
Chaudhuri, Kamalika
Fu, Xiaohan
Shams, Khawaja
Amir, Guy
Choi, Jihye
Choudhary, Sarthak
Palumbo, Nils
Labunets, Andrey
Pandya, Nishit V.
author_facet Christodorescu, Mihai
Fernandes, Earlence
Hooda, Ashish
Jha, Somesh
Rehberger, Johann
Chaudhuri, Kamalika
Fu, Xiaohan
Shams, Khawaja
Amir, Guy
Choi, Jihye
Choudhary, Sarthak
Palumbo, Nils
Labunets, Andrey
Pandya, Nishit V.
contents In recent years, agentic artificial intelligence (AI) systems are becoming increasingly widespread. These systems allow agents to use various tools, such as web browsers, compilers, and more. However, despite their popularity, agentic AI systems also introduce a myriad of security concerns, due to their constant interaction with third-party servers. For example, a malicious adversary can cause data exfiltration by executing prompt injection attacks, as well as other unwarranted behavior. These security concerns have recently motivated researchers to improve the safety and reliability of agentic systems. However, most of the literature on this topic is from the AI standpoint and lacks the system-security perspective and guarantees. In this work, we begin bridging this gap and present an analysis through the lens of classic cybersecurity research. Specifically, motivated by decades of progress in this domain, we identify short- and long-term research problems in agentic AI safety by examining end-to-end security properties of entire systems, rather than standalone AI models running in isolation. Our key goal is to examine where research challenges arise when applying traditional security principles in the context of AI agents and, as a secondary goal, distill these ideas for AI practitioners. Furthermore, we extensively cover 11 case studies of real-world attacks on agentic systems, as well as define a series of new research problems that are specific to this important domain.
format Preprint
id arxiv_https___arxiv_org_abs_2512_01295
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Systems Security Foundations for Agentic Computing
Christodorescu, Mihai
Fernandes, Earlence
Hooda, Ashish
Jha, Somesh
Rehberger, Johann
Chaudhuri, Kamalika
Fu, Xiaohan
Shams, Khawaja
Amir, Guy
Choi, Jihye
Choudhary, Sarthak
Palumbo, Nils
Labunets, Andrey
Pandya, Nishit V.
Cryptography and Security
In recent years, agentic artificial intelligence (AI) systems are becoming increasingly widespread. These systems allow agents to use various tools, such as web browsers, compilers, and more. However, despite their popularity, agentic AI systems also introduce a myriad of security concerns, due to their constant interaction with third-party servers. For example, a malicious adversary can cause data exfiltration by executing prompt injection attacks, as well as other unwarranted behavior. These security concerns have recently motivated researchers to improve the safety and reliability of agentic systems. However, most of the literature on this topic is from the AI standpoint and lacks the system-security perspective and guarantees. In this work, we begin bridging this gap and present an analysis through the lens of classic cybersecurity research. Specifically, motivated by decades of progress in this domain, we identify short- and long-term research problems in agentic AI safety by examining end-to-end security properties of entire systems, rather than standalone AI models running in isolation. Our key goal is to examine where research challenges arise when applying traditional security principles in the context of AI agents and, as a secondary goal, distill these ideas for AI practitioners. Furthermore, we extensively cover 11 case studies of real-world attacks on agentic systems, as well as define a series of new research problems that are specific to this important domain.
title Systems Security Foundations for Agentic Computing
topic Cryptography and Security
url https://arxiv.org/abs/2512.01295