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Jailbreaking attempts to override system behavior with adversarial prompts. That is useful for adversarial role spoofing defense, not source-origin prompt injection protection.

Tool results must not be promoted to authority over application actions. Its primary purpose is resistance to tool-output command injection, not source-origin prompt injection protection.

Observability must not unnecessarily expose credentials or sensitive content. It solves safe diagnostic prompt logging, not source-origin prompt injection protection.

Lineage documents provenance through data acquisition and transformation. It would support documented training data origin, not verifiable evidence references.

Generated citation-looking strings do not prove a document was accessed. That is useful for prevention of fabricated sourcing, not verifiable evidence references.

Content provenance is essential for lawful data governance. Its primary purpose is permitted use of source datasets, not verifiable evidence references.

Data integrity ensures the system processes the intended authentic content. That addresses trustworthy RAG source integrity, not trustworthy training inputs.

Data access control limits exposure of sensitive inputs and model assets. It would support least-privilege data engineering, not trustworthy training inputs.

Privacy-enhancing preparation lowers unneeded sensitive-data exposure. Its primary purpose is private data preparation for learning, not trustworthy training inputs.

External validation detects incorrect numeric outputs. It solves exact system-of-record transaction facts, not factual answers grounded in an official manual.

Bounded refusal is preferable to unsupported factual certainty. That addresses safe handling of missing grounding, not factual answers grounded in an official manual.

Toxicity controls target harmful wording beyond factual correctness. It would support safe customer-facing response content, not factual answers grounded in an official manual.

CloudTrail records supported AWS API and administrative activity. It solves attribution of permission changes, not inference performance observability.

Application logs capture contextual request-response relationships beyond infrastructure events. That addresses traceability of model interactions, not inference performance observability.

Config tracks supported resource configurations and compliance status. It would support resource configuration change monitoring, not inference performance observability.

Consequential transactions require authorization independent of model text. Its primary purpose is supervised refund execution, not least-authority agent lookup.

Retrieved text does not grant execution rights. It solves prevention of document-driven tool abuse, not least-authority agent lookup.

Identity propagation prevents an agent from accessing another user's resources. That addresses user-bound tool execution, not least-authority agent lookup.

Guardrails screen or filter configured unsafe categories. It would support enforcing safe topic boundaries, not protection of secret prompt content.

Model text must not be treated as trusted program control. That is useful for safe machine consumption of AI output, not protection of secret prompt content.

Data leakage prevention involves both retrieval authorization and output controls. It solves prevention of sensitive answer disclosure, not protection of secret prompt content.

Encryption at one layer does not prevent disclosure at another. That addresses secure end-to-end AI interaction logging, not confidential knowledge access boundaries.

Private networking is not equivalent to least-privilege API authorization. That is useful for layered IAM and network security, not confidential knowledge access boundaries.

User identity alone does not authorize every operation an agent may propose. Its primary purpose is controlled consequential operations, not confidential knowledge access boundaries.

Narrow IAM permissions limit what a workload can access. It solves minimal model API authorization, not secure workload access to model APIs.

Permissions analysis reveals who has authority over resources and actions. It would support review of AI resource access entitlements, not secure workload access to model APIs.

Short-lived access reduces risks associated with leaked persistent secrets. That is useful for reduction of long-lived secret exposure, not secure workload access to model APIs.

Agent identity controls can obtain or broker authorized access for tools. Its primary purpose is identity-aware access to external APIs, not agent action-level access control.

Identity provenance supports attribution of agent actions. That addresses auditable identity context across tools, not agent action-level access control.

Untrusted model text must not elevate execution rights. It would support preventing AI-driven privilege escalation, not agent action-level access control.

KMS supports governed use and management of cryptographic keys. Its primary purpose is controlled encryption key permissions, not protected data in network transit.

Secret-handling boundaries prevent inadvertent key disclosure to language models. It solves secure cryptographic secret management, not protected data in network transit.

At-rest encryption protects stored bytes using managed cryptographic keys. That addresses confidentiality of stored model data, not protected data in network transit.