Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning
We define Oracle Poisoning, an attack class in which an adversary corrupts a structured knowledge graph that AI agents query at runtime via tool-use protocols, causing incorrect conclusions through correct reasoning. Unlike prompt injection, Oracle Poisoning manipulates the data agents reason over, not their instructions. We demonstrate six attack scenarios against a production 42-million-node code knowledge graph, providing the first empirical demonstration of knowledge graph poisoning against a production-scale agentic system, distinct from CTI embedding poisoning. Primary evaluation uses real SDK tool-use across nine models from three providers (N=30 per model), where models autonomous...
| Authors | Ben Kereopa-Yorke, Guillermo Diaz, Holly Wright et al. |
|---|---|
| Primary category | cs.CR |
| Published | 10 May 2026 |
| Last updated at source | 10 May 2026 |
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