Application-Native vs Remote Security Policies: A Technical Guide
Compare application-native and code-native security rules with remote policies, including ownership, architecture, Arcjet, Datadog AI Guard, and Runlayer.
Read guideArcjet Learning Center
AI Security Guides
Identity, architecture, and runtime controls for agents that call tools, access data, and take actions.
What these guides cover
AI security protects systems in which models can call tools, access private data, and create real-world side effects. Model safeguards alone cannot determine whether a specific user may refund an invoice, whether retrieved content is trustworthy, or whether a sequence of individually permitted actions is safe. Production controls must preserve user and agent identity, validate untrusted model output, enforce policy immediately before consequential actions, constrain resource use, and record decisions for investigation. These guides focus on enforceable application boundaries: where a control has enough identity, workflow, resource, and business context to stop an unsafe operation before it completes. The result is layered protection tied to real application consequences.
Risks
- Unauthorized or manipulated tool calls
- Prompt injection through user or retrieved content
- Delegated authority used outside the user's intent
- Sensitive-data exposure and runaway resource use
Control priorities
- Action-level authorization inside the application
- Separate user, agent, workload, and client identities
- Prompt-injection, data, sequence, and budget checks
- Fail-safe enforcement with attributable audit evidence
Recommended reading order
Start with AI agent runtime security for the threat and control model. Use the architecture guide to choose enforcement points, then use the agentic identity guide to design delegation, workload identity, token exchange, and action-level authorization.
Guides in this collection
AI Agent Security Architecture: In-Code vs Proxy vs Gateway vs Security Agent
Compare in-code, proxy, AI gateway, and security-agent controls by visibility, enforcement, context, latency, failure modes, and threat coverage.
Read guideAI Agent Identity and On-Behalf-Of Authorization
AI agent on-behalf-of authorization: delegated identity, OAuth token exchange, actor claims, credential downscoping, runtime policy, and audit trails.
Read guideWhat Is AI Agent Runtime Security?
AI agent runtime security for unauthorized tool calls, prompt injection, sensitive data, automated abuse, action sequences, and production cost controls.
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