MoorAI reviews prompts on the device — so content never leaves the machine, and it wraps the AI agents you already run: Claude Code, Codex, GitHub Copilot CLI. Every prompt is checked locally against policy before it reaches the agent, and security teams see only redacted, content-free signals.
Lakera Guard is a cloud/API AI-security service — prompts are sent to the service for analysis. This is an honest, architecture-level comparison: on-device review versus cloud analysis.
Lakera Guard and MoorAI solve guardrails at opposite ends of the stack. Lakera Guard is a cloud/API LLM-app firewall: your deployed application calls it to screen the prompts and responses passing through, wherever that app runs. MoorAI sits one layer earlier — on the developer's own machine — reviewing each prompt to a coding agent locally, before it is ever sent anywhere.
| MoorAI | Lakera Guard | |
|---|---|---|
| Where prompts are reviewed | On the device | In the cloud service |
| Prompt content leaves the machine | Never | Sent to the service |
| Deployment model | Self-hosted, on-device | Cloud / API service |
| Coding-agent-native (wraps the CLI / PTY) | ✓ Claude Code · Codex · Copilot CLI | LLM-app / API security |
| Blocks secrets read into agent context | ✓ Claude Code hooks · Codex / Copilot CLI detect-only | App / API layer — not the endpoint agent |
| MCP tool-call interception (arguments) | ✓ Inspects mcp__* call arguments | Not stated at the endpoint agent layer |
| MCP allow-list enforced at call time | ✓ Non-allow-listed servers blocked | — |
| Reviews AI output, not just prompts | ✓ Output-stage detectors + CLI redaction | Yes — screens responses in-service |
| Runs fully on-device (no egress) | ✓ Always | Cloud / API service |
| Content-free telemetry | ✓ Category, risk level, one-way hash | Prompts analyzed in-service |
| AIBOM export (AI bill of materials) | ✓ HTML / JSON / CSV, CycloneDX-loose | — |
| Signals to security team | Redacted, content-free | Cloud-analyzed |
| Licensing | Open source (AGPL-3.0) | Proprietary |
| Account required to start | No (community agent) | Yes |
The honest take. Lakera Guard is genuinely strong at catching prompt-injection and app-layer attacks across production LLM apps, with detections that improve centrally. MoorAI solves a different problem — governing the coding agents your developers run, on-device, so prompt content never leaves the machine.
Note: Lakera was acquired by Check Point Software Technologies in September 2025; Lakera Guard is now part of Check Point's portfolio. Comparison is architecture-level and reflects the products' stated deployment models. MoorAI keeps prompt content on the device; Lakera Guard analyzes prompts in its cloud service. Any capability figures are approximate — verify current specifics against each vendor's docs. A “—” cell means we could not confirm the capability either way from published material; it is not a claim that the capability is absent.
Recently shipped in MoorAI — all on-device and content-free: a lethal-trifecta detector, rules-file poisoning detection (CLAUDE.md / .cursorrules), a capture-tier toggle (content-free by default), per-tool MCP argument rules, a per-agent assurance score, a data-lineage / Event Flow view, on-device model escalation, and cryptographically signed agency decisions — mapped across OWASP LLM Top 10, NIST CSF, NIST AI RMF, SOC 2, ISO 27001/42001, and the EU AI Act.