Runtime Security for AI Applications and Agents
Secure every AI interaction your team builds and deploys: from prompts to outputs to agent actions. Inline enforcement, without retraining models or rewriting prompts.
AI Agent Security Datasheet
Security Built for How AI Actually Works
AI systems behave probabilistically, act autonomously, and communicate in natural language. Securing them requires controls designed specifically for those properties.
- Deploy Without Friction No architecture rebuild. No model retraining. Security enforced at every interaction, invisibly.
- Catch AI-Native Attacks Catches prompt injection, jailbreaks, and indirect attacks that bypass traditional controls.
- Control Agent Actions Agents act, not just respond. AI Agent Security intercepts tool calls before unsafe actions execute.
What AI Agent Security Enforces
Purpose-built controls that operate inline at every AI interaction, inspecting inputs, governing outputs, and controlling agent behavior in real time.
Inline Prompt & Response Inspection
Inspects every prompt and model response in real time, detecting prompt injection, jailbreaks, and adversarial instructions before they reach the model or user, without requiring changes to prompts or applications.
Real-Time Data Protection
Applies policy-based detection and redaction across prompts and responses, preventing sensitive data exposure without interrupting user workflows.
Dynamic Policy Enforcement
Enforces customizable security and governance policies at runtime, with updates applied instantly across all AI interactions without redeployment.
Agent Action Control
Intercepts and evaluates agent tool calls before execution, allowing organizations to approve, block, or modify actions based on context and policy.
External Content & MCP Inspection
Evaluates content flowing through external sources including files, APIs, and MCP-connected systems before it influences model behavior or agent decisions.
Model-Agnostic Runtime Layer
Deploys across any model or provider with consistent enforcement, supporting cloud, on-prem, and hybrid environments with sub-50ms latency and global language coverage.
What We Protect Against
AI Agent Security stops adversarial attacks before they reach the model, prevents sensitive data exposure and misuse, and ensures AI behaves within defined boundaries.
- Prompt injection, jailbreaks, and adversarial instructions – blocked before they reach the model.
- Sensitive data exposure in prompts and responses, unauthorized agent access, and gaps in AI interaction visibility.
- Harmful or non-compliant outputs, agents taking unsafe or unauthorized actions, and policy misuse.
Trusted by Teams Building AI at Scale
“The Lakera team has accelerated our GenAI journey, allowing us to create secure GenAI experiences at scale.”
-Adrian Wood
Security Engineer,
Dropbox
“This partnership enables us to safely innovate with AI in money transfers, financial services, and customer support.”
-Dave Hannigan
CISO,
Nubank
