FlowSteer is a prompt-only attack that biases multi-agent LLM workflow planning to propagate malicious signals, raising success rates by up to 55%, with FlowGuard as an input-side defense reducing it by up to 34%.
Ip leakage attacks targeting llm-based multi-agent systems
4 Pith papers cite this work. Polarity classification is still indexing.
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SeqWM embeds watermarks into history-conditioned action transitions in LLM agent trajectories and verifies them position-agnostically, achieving robust detection under perturbations where prior per-step methods fail.
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
A topology-aware attack propagates adversarial contamination across LLM multi-agent systems to achieve 40-85% success rates on frameworks and real applications, revealing overlooked vulnerabilities.
citing papers explorer
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FlowSteer: Prompt-Only Workflow Steering Exposes Planning-Time Vulnerabilities in Multi-Agent LLM Systems
FlowSteer is a prompt-only attack that biases multi-agent LLM workflow planning to propagate malicious signals, raising success rates by up to 55%, with FlowGuard as an input-side defense reducing it by up to 34%.
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Sequential Behavioral Watermarking for LLM Agents
SeqWM embeds watermarks into history-conditioned action transitions in LLM agent trajectories and verifies them position-agnostically, achieving robust detection under perturbations where prior per-step methods fail.
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Security Considerations for Multi-agent Systems
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
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Don't Trust Your Upstream: Exploiting LLM Multi-Agent System via Topology-Guided Adversarial Propagation
A topology-aware attack propagates adversarial contamination across LLM multi-agent systems to achieve 40-85% success rates on frameworks and real applications, revealing overlooked vulnerabilities.