How do posture management and runtime security differ?
AI security posture management, often shortened to AI-SPM or AISPM, identifies AI assets and evaluates their configuration, permissions, and exposure. AI runtime security evaluates activity while an application or agent runs, and it can block an operation when enforcement sits before the effect. Posture asks what is exposed and needs remediation; runtime asks whether to permit this interaction or action. Zenity, Noma Security, Check Point AI Agent Security, Palo Alto Networks Prisma AIRS, and Microsoft Agent 365 document discovery or posture capabilities. Zenity, Noma Security, Check Point, and Prisma AIRS also document runtime protection, and Microsoft pairs Agent 365 with runtime protection in Defender for Endpoint. Arcjet focuses on runtime enforcement, in your code and in the hooks of Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code. Start with posture if you can't list your agents, their owners, or their credentials. Start with runtime enforcement if a known workflow can move money, expose private data, or run a destructive command.
Posture and runtime controls are both useful for AI agent security. An inventory can reveal that a support agent has a broad billing credential, and a runtime policy can stop that agent from refunding the wrong invoice. Removing the excess privilege reduces future risk; denying the specific action protects the current workflow.
Arcjet publishes this comparison and provides runtime policy enforcement. Competitor details come from each vendor's public documentation, reviewed on September 25, 2026. The page compares capabilities rather than scoring vendors, so verify product scope and integration requirements for your environment.
How do posture and runtime compare on inputs and evidence?
AI-SPM and AI runtime security differ in their input, their output, where they act, the evidence they produce, and the coverage gap to test. The following table compares the two categories on six dimensions.
| Dimension | AI security posture management | AI runtime security |
|---|---|---|
| Primary input | Asset inventory, configuration, permissions, relationships, and exposure | Prompts, retrieved content, tool arguments, identities, resource state, and activity |
| Typical finding or decision | An agent has access it does not need; an inference endpoint is exposed | A particular input is suspicious or a proposed action violates policy |
| Where it acts | Discovery integrations and configuration or permission management | An integrated request, model, tool, gateway, or execution boundary |
| Useful evidence | Which assets were discovered, scan recency, risk context, and remediation history | Which calls were checked, decision reason, enforcement result, and added latency |
| Coverage question | Which accounts, platforms, and agent types are missing from discovery? | Which actions can execute without reaching the enforcement point? |
| Failure to test | A newly deployed or changed agent is absent from the inventory | A denied action still executes through a retry or alternate path |
A posture product can operate continuously and trigger automated remediation, and a runtime product can be configured to observe without blocking. Neither label establishes whether a product prevents your specific failure, so inspect the integration and demonstrate the result.
How do posture and runtime controls apply to one support agent?
On a single support agent, a posture review removes privilege that the agent doesn't need, and a runtime check stops a specific misdirected send that the remaining privilege still allows. Consider an agent that reads support tickets, retrieves billing records, and sends replies.
A posture review finds that the agent's service account can export all customers and that nobody owns its Model Context Protocol (MCP) connection. The team removes the export permission, assigns an owner, and reviews the connected server.
Later, a ticket includes instructions to send a customer's invoice to a different email address. The remaining read and send permissions are legitimate for the support workflow, so the application still needs to bind the recipient to verified case data and authorize access to the invoice before the send occurs.
The posture fix and the runtime check address different parts of the same incident path. Content screening adds another signal, and recipient and resource checks must still apply when an instruction goes undetected. Use threat modeling to connect these controls to the consequences you need to prevent.
How do you read vendor claims about posture and runtime?
Read each vendor claim by the integration it names and whether that integration is generally available, because vendor products often span both categories. Don't treat a company as a single fixed layer, and don't assume that a product page means every integration has shipped.
- Check Point's AI Agent Security documentation, from its Lakera acquisition, describes an early-access offering with agent discovery, per-agent risk ratings, and runtime protection through the Guard API. Confirm the supported discovery connectors and how enforcement enters your execution path. For more information, see Arcjet vs Lakera.
- Palo Alto Networks' Prisma AIRS documentation lists AI inventory, supply chain scanning, red teaming, agent identity, an AI gateway, and runtime security at the network or code layer. Evaluate the particular deployment you intend to use. For more information, see Arcjet vs Prisma AIRS.
- Zenity's platform description spans inventory, posture, enforcement, and response, and its coding agent coverage uses native hooks and an MCP gateway. Verify the relevant agent platform and action coverage in a demonstration. For more information, see Arcjet vs Zenity.
- Noma Security combines continuous AI discovery, posture management, red teaming, and runtime protection. For more information, see Arcjet vs Noma Security.
- Microsoft Agent 365 provides an agent registry with Entra, Purview, and Defender controls for agents in the Microsoft ecosystem and connected platforms. Agent 365 has been generally available since May 1, 2026, with registry sync for AWS Bedrock and Google Cloud in preview. Defender for Endpoint also discovers local AI agents and adds runtime protection against prompt injection, in preview on Windows. For more information, see Arcjet vs Microsoft Agent 365.
- Arcjet enforces runtime policy in the path of the action: Guards in your code, and the hooks of Claude Code, GitHub Copilot, Cursor, OpenAI Codex, and Muse Code for coding agents. Arcjet discovers agents from the activity that those hooks, OpenTelemetry, and the Claude Compliance API report. Activity-based discovery isn't cloud-asset posture scanning or automatic coverage of every execution path.
These descriptions come from first-party documentation and aren't independent effectiveness benchmarks. For a broader shortlist, see AI agent security platforms.
Which questions do you test during a proof of concept?
A proof of concept for either category tests six things: discovery of a new agent, detection of a permission change, denial of an unauthorized action, coverage of alternate paths, behavior during an outage, and where data goes.
- Can the product find a new agent? Introduce a test agent on an in-scope platform. Measure when it appears, whether its owner is recorded, and whether tool and credential relationships are accurate.
- Can the product detect a permission change? Give a synthetic agent an unnecessary test permission. Check the resulting finding and whether remediation removes that permission without breaking its legitimate task.
- Can the product stop an unauthorized action? Use a synthetic cross-tenant record or disallowed recipient. Observe the downstream service to confirm that denial happens before the effect.
- Does enforcement survive alternate paths? Repeat through a background job, retry, and different tool that reaches the same service. Inventory and instrumentation coverage are separate measurements.
- What happens during an outage? Test a timeout at the discovery connector and at the inline policy service. Stale inventory and blocked execution have different operational consequences.
- Where does data go? Trace raw prompts, tool arguments, credentials, and telemetry separately. Ask about storage and retention as well as evaluation location.
Keep a record of product version, deployment mode, policy, tested framework, and observed outcome. A checkmark on a sales matrix can't replace that evidence.
Which control do you need first?
Prioritize discovery and posture when you can't identify the agents running in your environment, their owners, or the data and credentials they can reach. Prioritize runtime enforcement when you operate a known workflow that can move money, expose private data, or make destructive changes without a reliable action check.
Most production programs need both controls, plus application authorization, testing, and response. Arcjet is relevant when you need a policy decision on a tool call, command, or request with application context before it runs, including on coding agents where no application code is involved. Your team remains responsible for reaching every sensitive execution path and verifying the outcome.
Use the AI security checklist to assign ownership and the agent security testing guide to evaluate the controls before rollout.
Frequently asked questions
What is the difference between AI-SPM and AI runtime security?
AI-SPM evaluates assets, configuration, permissions, and exposure, while AI runtime security evaluates activity during execution and can block an operation when it's integrated before the effect. A posture finding drives remediation, such as removing an excess credential, and a runtime decision allows or denies a specific action. A single product can provide both.
Does AI security posture management stop prompt injection?
Not on its own. A posture finding can expose conditions that increase prompt injection risk, such as an agent with a broad credential, but preventing a particular interaction requires an enforcement control in that interaction's path. Verify the runtime capabilities of the specific product and deployment before you rely on them.
Do I need both posture management and runtime security?
Most production programs need both: inventory and configuration review, plus controls on consequential actions. Prioritize discovery when ownership and access are unknown. Prioritize runtime checks when a known workflow can move money, expose private data, or make destructive changes without a reliable action check.
Which vendors offer AI security posture management?
Zenity, Noma Security, Check Point AI Agent Security, Prisma AIRS, and Microsoft Agent 365 all document discovery or posture capabilities, and several add runtime controls. Arcjet focuses on runtime enforcement in code and in coding-agent hooks, and discovers agents from the activity those integrations report rather than by scanning cloud assets.
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Arcjet runs inside your application, where it can use runtime context to enforce agent actions and budgets, detect prompt injection, and protect sensitive information before a workflow acts.