lakera.ai valid

Assess, monitor, protect and control your AI agents

One platform to discover, protect, and govern every AI interaction from employees to agents.

For agents: Lakera platform for securing and governing AI agents, employee AI use and applications, with AI agent security docs, red teaming and changelog.

ai agent securityai red teamingai governancellm guardrailschangelog

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-23T11:02:17.287Z. Cached copy · Source on lakera.ai

# Assess, monitor, protect and control your AI agents

One platform to discover, protect, and govern every AI interaction from employees to agents.

[Learn about AI Security](/introduction)

[Quickstart guide](/docs/quickstart)

[API Reference](/api-reference)

## Find what you need

#### For Security Leaders

Understand AI security risks and how Check Point protects your applications. Learn about threats, solutions, and business impact:

* [Check Point Introduction](/introduction)
* [AI Agent Security](/guard)
* [AI Red Teaming](/red)
* [Security Framework Coverage](/docs/agent-security/framework-mapping)

#### For Security Practioners

Understand how Check Point fits into your security workflows and operations. Explore important concepts and practical guidance:

* [Guardrails Overview](/docs/defenses)
* [Policies Overview](/docs/policies)
* [AI Guardrails Dashboard](/docs/platform)
* [Integration Guide](/docs/integration)

#### For Developers

Get up and running with our platform and APIs. Integration guides and technical documentation:

* [Quickstart](/docs/quickstart)
* [Integration Guide](/docs/integration)
* [Integration recommendations](/docs/integration#integration-recommendations)
* [API Reference](/api-reference)

#### For Evaluators

Benchmark performance and run a successful "proof-of-value". Evaluation frameworks and testing resources:

* [AI Agent Security Evaluation](/docs/agent-security-evaluation)
* [AI Guardrails Evaluation](/docs/evaluation-overview)
* [Quickstart](/docs/quickstart)
* [Datasets](/docs/datasets)

## Instructions for AI Agents

- For clean Markdown of any page, append `.md` to the page URL
- For section-specific indexes, append `/llms.txt` to any section URL
- For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.lakera.ai/_mcp/server

## Docs

- [](https://docs.lakera.ai/docs/landing.md)
- [The Check Point AI Defense Plane](https://docs.lakera.ai/introduction.md): A unified security model — powered by a real-time control plane for Employees, Applications and Agents
- [Introduction to AI Agent Security](https://docs.lakera.ai/guard.md)
- [Introduction to AI Red Teaming](https://docs.lakera.ai/red.md)
…

Related sites

Other listed sites in AI and machine learning. See the whole category →

Machine-readable: GET /v1/resolve?q=lakera.ai · GET /v1/domain/lakera.ai · this page as Accept: application/json or text/markdown · MCP lookup_domain

Automatically discovered from public files. Inclusion does not imply endorsement or publisher participation.

Claim my listing on Agent Web Map for lakera.ai:
1. POST https://agentwebmap.com/v1/sites/lakera.ai/claims and keep claim_id and claim_secret private.
2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://lakera.ai/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
3. POST https://agentwebmap.com/v1/sites/lakera.ai/verify with {"claim_id": "...", "claim_secret": "..."}.
4. Save the api_key from the answer; it manages the listing (PATCH https://agentwebmap.com/v1/sites/lakera.ai).
MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

Corrections or removal requests: contact the directory.