From Monoliths to Swarms: A Study of Attack Surface Evolution in the Transition to Multi-Agent Web Systems

Computer Science > Cryptography and Security [Submitted on 31 Jul 2026] From Monoliths to Swarms: A Study of Attack Surface Evolution in the Transition to Multi-Agent Web Systems Yashaswi Malla, Sandra Siby Large Language Model (LLM)-based web agents are increasingly evolving from single-agent systems (SAS) to multi-agent systems (MAS). While MAS can lead to improved task performance by decomposing complex tasks across specialized sub-agents, such role decomposition introduces new structural attack surfaces that are absent in SAS. This expanded attack surface remains poorly understood and inadequately categorized. To address this, we propose a taxonomy to categorize attack vectors specific to web-based MAS, accounting for vulnerabilities introduced or amplified by the involvement of multiple agents. We further present a test-bed WebMASLab to analyze web agent security against a fully external, web-only adversary. To isolate the effect of architecture, we keep the user task, tool surface, and browser substrate fixed, and compare single- and multi-agent setups. We evaluate three adversarial scenarios, across three conditions (baseline, prompt-hardened, and reasoning-enabled), including a novel MAS-specific Telephone Loop attack that exploits cross-agent delegation to create cyclical task loops. The attack is inert against SAS but compromises MAS when powered by three of the four frontier models evaluated (Claude Sonnet 4.5, GPT-5.2, GPT-5.4), averaging 80% across them at baseline. Only the fourth model, Claude Sonnet 4.6, resists the attack with a 92% detection rate. For the rest, the detection is 0% at baseline, reaching 33% with prompt-hardening for one model. We also show that obvious defenses do not generalize; prompt-hardening collapses one model's ASR from 100% to 8% while providing only modest reduction to the others. Our findings demonstrate that the transition from single- to multi-agent web systems changes the security landscape. Role specialization may not only lead to performance optimization but also introduce new architectural risks that require further study and defenses. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2608.00202 [cs.CR]   (or arXiv:2608.00202v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2608.00202 Focus to learn more Submission history From: Yashaswi Malla [view email] [v1] Fri, 31 Jul 2026 18:27:12 UTC (5,659 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)