Rune vs Lakera Guard: AI Agent Security Compared
Two approaches to AI security — cloud-managed API vs framework-native runtime scanning
Lakera Guard and Rune both protect AI applications from prompt injection and other LLM attacks, but they take fundamentally different approaches. Lakera Guard operates as a cloud API — you send text to their endpoint and get a risk classification back. Rune embeds directly into your agent framework as a middleware layer, scanning inputs, outputs, and tool calls inline without external API round-trips.
Lakera Guard was one of the first commercial prompt injection detectors and has a strong dataset built from their Gandalf challenge, which crowd-sourced thousands of real injection attempts. They were acquired by Palo Alto Networks in 2025, integrating their detection into Prisma Cloud.
Rune takes a different architectural bet: instead of an external API call, Rune's SDK wraps your existing agent client (OpenAI, Anthropic, LangChain, CrewAI, MCP) and intercepts every interaction at the framework level. This means lower latency, no data leaving your infrastructure unless you opt in, and the ability to scan tool calls and inter-agent communication — not just raw text.
Rune
Rune is a runtime security SDK that embeds directly into your AI agent's framework. Instead of calling an external API, Rune wraps your existing client (OpenAI, Anthropic) or hooks into middleware (LangChain, CrewAI) to scan every input, output, and tool call inline. It uses a multi-layer detection pipeline: regex pattern matching, semantic similarity analysis, and optional LLM-based judgment. Policies are defined in YAML and enforced locally. Events are shipped asynchronously to the Rune dashboard for monitoring and alerting.
Lakera Guard
Lakera Guard is a cloud-hosted API that classifies text for prompt injection, PII, toxic content, and other risks. You send a POST request with your text and receive a risk score. It supports both direct API integration and OpenAI-compatible proxy mode. Lakera built their detection models using data from the Gandalf game, which gathered 1M+ real-world injection attempts. After acquisition by Palo Alto Networks, Guard is being integrated into their broader cloud security platform.
Feature-by-Feature Comparison
Detection
| Feature | Rune | Lakera Guard |
|---|---|---|
| Prompt injection detection | Multi-layer: pattern + semantic + LLM judge | ML classifier trained on Gandalf dataset |
| PII/credential detection | Regex-based PII and secret scanning | PII detection via API |
| Tool call scanning | Scans tool names, parameters, and results | Text classification only — no tool awareness |
| Inter-agent communication scanning | Monitors data flow between agents in CrewAI | Not supported — single-request model |
| Behavioral anomaly detection | Baseline tracking for unusual patterns | Not available |
Performance
| Feature | Rune | Lakera Guard |
|---|---|---|
| Scanning latency | Local pattern + semantic scanning in <20ms | Cloud API round-trip, typically 50-200ms |
| Data residency | Scanning runs locally; events shipped async | All text sent to Lakera cloud for classification |
| Offline mode | L1/L2 scanning works without network | Requires API connectivity |
Framework Support
| Feature | Rune | Lakera Guard |
|---|---|---|
| LangChain integration | Native middleware — ShieldMiddleware | Manual API calls in chain steps |
| OpenAI SDK wrapper | Drop-in shield_client() wrapper | API proxy or manual integration |
| CrewAI multi-agent | shield_crew() with per-agent tool wrapping | No multi-agent support |
| MCP protocol | Full MCP security proxy (stdio + SSE) | Not supported |
Pricing
| Feature | Rune | Lakera Guard |
|---|---|---|
| Free tier | 10,000 events/month | Limited free tier available |
| Pricing model | Per-event pricing, scales linearly | Per-request API pricing |
| Self-hosted option | SDK runs locally; dashboard is cloud | Cloud-only API |
When to Choose Rune
Framework-native integration
Rune wraps your existing client or plugs into middleware — no separate API calls to manage. Your agent code stays clean and security happens transparently.
Tool call and agent workflow scanning
Rune scans tool calls, function parameters, and inter-agent communication. Lakera Guard only classifies raw text — it has no awareness of what your agent is actually doing.
Lower latency, local scanning
Pattern and semantic scanning run locally in your process. No cloud round-trip for every request. Events are shipped asynchronously for dashboard monitoring.
When to Choose Lakera Guard
Proven at scale with Palo Alto Networks backing
Lakera Guard has been in production longer, processes billions of requests, and now benefits from Palo Alto Networks' enterprise sales and support infrastructure. If you need a vendor with SOC 2 Type II and enterprise contracts today, Lakera has a head start.
Gandalf-trained detection model
Lakera's ML model was trained on over 1 million real injection attempts from their Gandalf challenge. This crowd-sourced dataset gives their classifier broad coverage of creative injection techniques.
Best For
Choose Rune if...
Teams building agents with tool access who need low-latency, framework-native scanning — especially multi-agent workflows, MCP servers, and environments where data can't leave the network.
Choose Lakera Guard if...
Enterprises that prefer a managed cloud API with established compliance certifications and don't need tool-call-level scanning.
How to Switch from Lakera Guard to Rune
- 1Install the Rune SDK: pip install runesec
- 2Replace Lakera Guard API calls with Rune's framework wrapper (e.g., shield_client() for OpenAI)
- 3Define your security policies in YAML — Rune supports the same detection categories plus tool-level rules
- 4Remove Lakera Guard API key and endpoint configuration
- 5Verify scanning works by running your agent with a test injection payload
- 6Set up the Rune dashboard to monitor events and configure alerts
Frequently Asked Questions
Can Rune detect the same attacks as Lakera Guard?
Yes. Rune's multi-layer detection covers prompt injection, PII exposure, and toxic content — the same core categories as Lakera Guard. Rune adds tool call scanning, inter-agent monitoring, and behavioral anomaly detection on top.
Is Lakera Guard faster since it's a dedicated ML classifier?
Lakera Guard's classifier is fast, but it requires a network round-trip to their cloud API (typically 50-200ms). Rune's L1 and L2 scanning layers run locally in your process with sub-20ms latency. The optional L3 LLM judge adds more latency but catches sophisticated attacks that classifiers miss.
Does Rune work if Lakera Guard is acquired or deprecated?
Yes. Rune is an independent product. Since it runs as an SDK in your codebase, you're not dependent on any external API availability. Your security policies and detection rules continue to work even offline.
Can I use both Rune and Lakera Guard together?
Technically yes — you could use Lakera Guard as an additional scanning layer alongside Rune. In practice, Rune's multi-layer detection covers the same threats with the advantage of tool-aware scanning, so most teams find Rune sufficient on its own.
How does pricing compare between Rune and Lakera Guard?
Both offer free tiers. Rune includes 10,000 events per month free with per-event pricing after that. Lakera Guard uses per-request API pricing. Since Rune scans tool calls and agent interactions (not just raw text), you get broader coverage per event.
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