ChainCaps uses monotonic capability attenuation via intersection of sink-specific budgets in a transparent proxy to reduce attack success on composed tool-using agents from 25-68% to 0-4.8% while keeping 96-100% benign task completion.
and Sands, David , year =
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Multi-agent AI creates an authorization propagation problem not solved by prompt injection defenses or classical access control, requiring identity governance as continuously enforced infrastructure.
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.
citing papers explorer
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ChainCaps: Composition-Safe Tool-Using Agents via Monotonic Capability Attenuation
ChainCaps uses monotonic capability attenuation via intersection of sink-specific budgets in a transparent proxy to reduce attack success on composed tool-using agents from 25-68% to 0-4.8% while keeping 96-100% benign task completion.
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Authorization Propagation in Multi-Agent AI Systems: Identity Governance as Infrastructure
Multi-agent AI creates an authorization propagation problem not solved by prompt injection defenses or classical access control, requiring identity governance as continuously enforced infrastructure.
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The Importance of Out-of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Plane
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.