Smarter Saboteurs, Better Fixers: Scaling & Security in Linear Multi-Agent Workflows
As LLM-based multi-agent systems (MAS) are deployed in the wild, the resilience of their collaboration structures against adversarial compromise becomes a critical safety concern. Attackers may leverage prompt-injection or jailbreaking to sabotage individual agents within MAS workflows, but the interaction between model scaling and system-level resilience remains poorly understood. This paper investigates how model scale affects the security of linear multi-agent workflows. Our experiments across scales of two open-weight model families on the HumanEval benchmark reveal a compliance-correction symmetry: larger models are far more likely to faithfully execute malicious instructions, with t...
| Authors | Timothy McAllister, Sina Abdidizaji, Ivan Garibay et al. |
|---|---|
| Primary category | cs.MA |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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