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AWS Bedrock Knowledge Base or RAG Data Source Tampering
Oct 1, 2026 · Domain: Cloud Domain: GenAI Data Source: AWS Data Source: AWS CloudTrail Data Source: Amazon Web Services Data Source: AWS Bedrock Data Source: Amazon Bedrock Use Case: Threat Detection Resources: Investigation Guide Tactic: Impact Noise: Low Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: New Terms Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0070 Mitre Atlas: AML.T0059 ·Detects control-plane mutations to AWS Bedrock knowledge bases and their backing RAG data sources via CloudTrail. An adversary with access to Bedrock Agent APIs can poison the corpus that RAG-enabled models treat as authoritative by ingesting attacker-controlled documents (IngestKnowledgeBaseDocuments, StartIngestionJob), deleting legitimate documents (DeleteKnowledgeBaseDocuments), or repointing/altering the data source itself (CreateDataSource, UpdateDataSource, DeleteDataSource, UpdateKnowledgeBase). Because downstream applications and users trust model answers grounded in this stored data, tampering with the corpus is a stored data manipulation that can drive misinformation, fraud, or manipulated decisions at inference time. This is a New Terms rule that looks for the first time a given identity ARN performs one of these knowledge base or data source mutations within the history window.
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AWS Bedrock Third-Party or External Knowledge Base Associated to Agent
Oct 1, 2026 · Domain: Cloud Domain: GenAI Data Source: Amazon Web Services Data Source: AWS Data Source: AWS CloudTrail Use Case: Threat Detection Resources: Investigation Guide Tactic: Persistence Noise: Unknown Performance: Fast Profile: Recommended Threat: Unauthorized AI Usage Rule Type: New Terms Platform: AWS Service: AWS Bedrock Mitre Atlas: AML.T0070 Mitre Atlas: AML.T0010 ·Detects when an Amazon Bedrock agent is associated with, or updated to use, a knowledge base via the AssociateAgentKnowledgeBase, or UpdateAgentKnowledgeBase API actions. Bedrock agents consume knowledge base (RAG) content as trusted context for the model. By wiring an agent to an externally controlled or third-party knowledge base, or by swapping in an attacker-controlled knowledge base, an adversary can redraw the agent's trust boundary toward an untrusted source. This is a software-supply-chain compromise and an indirect prompt-injection delivery vector: poisoned or adversarial content served from the associated knowledge base is treated as authoritative by the agent. Validate that the associated knowledge base, and any underlying data source, is owned and controlled by your organization.
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