aiqbench analysis
This research addresses a critical vulnerability in multi-agent systems where malicious instructions can infiltrate inter-agent communications alongside legitimate task data. The proposed ESC-CR framework introduces a policy-backed mechanism that isolates unauthorized claims from trusted evidence, allowing for the regeneration of safe artifacts without discarding essential context. By enforcing boundaries at an external release point, this approach offers a robust defense against adaptive attacks while maintaining system utility.
Policy-Backed Selective Regeneration under Tainted Inter-Agent Communication
arXiv:2609.26072v1 Announce Type: cross Abstract: Inter-agent communication is essential to multi-agent language-model systems, yet a single message may combine task-critical information with instructions not authorized by the original request. Prompt-based defenses leave enforcement to models exposed to adversarial messages, while indiscriminate message removal discards useful information. We introduce Executable Semantic Commitments with Clean-Room Recovery (ESC-CR), a policy-backed framework for secure inter-agent code generation and recovery. It separates message claims from authorization, constructs executable commitments from trusted tasks, evidence, and policy, and enforces them at an external release boundary. Upon a violation, ESC-CR taints the responsible message and rejected artifact, reconstructs a clean context from evidence-backed task information, and regenerates under the same policy. We evaluate ESC-CR across communication-essential and standard code-generation benchmarks, multiple model families and communication topologies, and adaptive attacks spanning direct, obfuscated, and verifier-aware payloads. Results show that polluted-context retry frequently fails to remove unauthorized influence, while complete message removal can discard information required by communication-essential tasks. ESC-CR preserves evidence-backed claims while suppressing unauthorized releases under matched computational budgets, and the same design transfers to end-to-end agent trajectories.
Abstract:Inter-agent communication is essential to multi-agent language-model systems, yet a single message may combine task-critical information with instructions not authorized by the original request. Prompt-based defenses leave enforcement to models exposed to adversarial messages, while indiscriminate message removal discards useful information. We introduce Executable Semantic Commitments with Clean-Room Recovery (ESC-CR), a policy-backed framework for secure inter-agent code generation and recovery. It separates message claims from authorization, constructs executable commitments from trusted tasks, evidence, and policy, and enforces them at an external release boundary. Upon a violation, ESC-CR taints the responsible message and rejected artifact, reconstructs a clean context from evidence-backed task information, and regenerates under the same policy. We evaluate ESC-CR across communication-essential and standard code-generation benchmarks, multiple model families and communication topologies, and adaptive attacks spanning direct, obfuscated, and verifier-aware payloads. Results show that polluted-context retry frequently fails to remove unauthorized influence, while complete message removal can discard information required by communication-essential tasks. ESC-CR preserves evidence-backed claims while suppressing unauthorized releases under matched computational budgets, and the same design transfers to end-to-end agent trajectories.
Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)
arXiv:2609.26072 [cs.CR]
(or arXiv:2609.26072v1 [cs.CR] for this version)
https://doi.org/10.48550/arXiv.2609.26072 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 273 words
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