Runtime Protection
Runtime protection refers to security controls that detect and respond to threats while applications, workloads, or AI systems are actively operating.
ON THIS PAGE
What Runtime Protection Is and How It Works in Practice
Traditional security approaches frequently analyze software before execution. Runtime security complements those controls by observing what actually happens when applications and systems interact with users, data, tools, and infrastructure.
This becomes particularly important for AI agents, where risk can depend heavily on the context and intent of a specific session.
Runtime protection operates within or alongside active applications and workloads.
Instead of relying exclusively on what software might do based on code or configuration, runtime security monitoring provides visibility into what it is actually doing.
Depending on the environment, runtime controls may observe:
Application behavior
User activity
Process execution
Network connections
Data access
Tool invocation
Permission usage
Changes in behavior or context
For AI agents, runtime visibility can also help determine whether an agent’s actions remain aligned with the user’s intended task.
This makes runtime an important enforcement point when static rules alone cannot capture the context of every interaction.
Key Benefits of Runtime Protection
Runtime protection can provide several advantages.
Real-time visibility: Security teams can observe behavior as it occurs.
Context-aware detection: Decisions can incorporate current users, resources, sessions, and actions.
Protection against unknown threats: Runtime behavior may reveal suspicious activity even when a specific vulnerability or attack technique was not previously identified.
Faster response: Security controls can potentially block or contain dangerous activity during execution.
Detailed auditability: Runtime telemetry provides evidence of what occurred during an application or AI session.
Modern runtime application protection can therefore complement preventative security controls with direct visibility into active behavior.
Related approaches include RASP security, or Runtime Application Self-Protection, in which security capabilities operate within or closely alongside the application itself.
This type of application self-protection can allow security decisions to incorporate application context that external controls may not have.
Runtime Protection vs. Static Analysis: Knowing Which Approach Fits
Static analysis examines software without executing it.
It can identify insecure code patterns, vulnerabilities, misconfigurations, and other issues early in the development lifecycle.
Runtime protection addresses a different problem.
It evaluates behavior during execution, when the application is interacting with real users, systems, data, and infrastructure.
Organizations generally should not view these approaches as alternatives.
Static analysis can help answer:
“Is there something potentially dangerous in this software?”
Runtime protection can help answer:
“Is something dangerous happening right now?”
For AI agents, this distinction becomes especially important because behavior may change based on dynamic context, prompts, external data, available tools, and user intent.
Frequently asked questions
What is the difference between runtime protection and endpoint detection and response (EDR)?
EDR primarily monitors endpoint activity such as processes, files, and system behavior. Runtime protection can operate closer to the application or AI execution layer and incorporate application-specific context. The technologies can therefore provide complementary visibility.
Does runtime protection replace the need for static or dynamic application testing?
No. Runtime protection complements rather than replaces pre-production testing and vulnerability management. Different controls address different stages of the application lifecycle.
How does runtime protection handle zero-day vulnerabilities in production?
Behavior-focused runtime controls may identify or block suspicious activity associated with an unknown vulnerability even before a specific signature exists. Effectiveness depends on the protection technology and attack technique.
What performance overhead should teams expect from runtime protection tools?
Overhead varies significantly depending on implementation, architecture, telemetry collection, and the depth of inspection being performed. Organizations should evaluate performance as part of deployment testing.
Related terms
See what your agents are actually doing.
Dash discovers every AI agent, tool, and MCP server across your estate, understands session and intent, and enforces policy at runtime.