The Agent-Aware Pangea AI Guard Alternative for AI Security
Pangea bundles AI scanning into a broad security platform. Rune is purpose-built for the specific threats AI agents face.
Why Teams Look for Pangea AI Guard Alternatives
Bundled pricing — you pay for the full security suite
Pangea's AI Guard is one module within their broader security platform (SecureAudit, AuthN, Embargo, Redact, etc.). Pricing is suite-level, not à la carte. You typically buy the full platform to get AI scanning — paying for capabilities you don't need to get the one you do.
Shallow prompt injection detection
Pangea's AI Guard focuses on content safety (toxicity, PII redaction, malicious URLs) more than adversarial prompt attacks. Its injection detection is basic pattern matching — it doesn't use multi-layer detection with semantic analysis or LLM-based judgment. Purpose-built injection tools catch significantly more attack variants.
No agent framework awareness or tool call scanning
Pangea treats AI scanning like any other API content check. It doesn't understand agent frameworks, tool call arguments, inter-agent delegation, or multi-step workflows. When an attacker injects through a tool's return value or exploits inter-agent communication, Pangea can't see the context.
Cloud API adds latency and data residency complexity
Every scan requires sending text to Pangea's cloud API. This adds latency per call and means your prompts traverse external infrastructure. For teams with GDPR, HIPAA, or data residency requirements, this creates a data processing relationship requiring DPAs and compliance review.
Strong at redaction, weaker at detection
Pangea's real strength is PII redaction — actually removing or masking sensitive data before it reaches the model. That's valuable. But detection of adversarial attacks (injection, exfiltration, escalation) is a different problem, and Pangea's approach treats it as a content safety problem rather than a security problem.
How Rune Solves These Problems
Purpose-built for agent security threats
Every feature in Rune targets the specific attack patterns agents face: prompt injection (multi-layer detection), data exfiltration (encoded data in URLs, tool args), PII detection (SSN, credit cards, emails in outputs), secret exposure (API keys, JWTs), and privilege escalation through tool abuse. Not a content safety filter — a security platform.
Native framework integration for 6 agent frameworks
Drop-in middleware for LangChain, OpenAI, Anthropic, CrewAI, MCP, and OpenClaw. Scans tool arguments before execution, tool return values for exfiltration, and inter-agent messages for injection — attack surfaces that Pangea's content scanning API can't see.
Standalone pricing — no platform bundle required
Free tier with 10K events/month, usage-based pricing at $0.05/1K scans after that. No bundled security suite, no feature gating behind higher tiers. You pay for agent security, not a dozen other security modules you don't need.
Local-first — raw content never leaves your infrastructure
All scanning runs in your application process using local pattern databases and embeddings. Only structured metadata (event type, threat category, scan result) reaches the dashboard. No DPA required, no data residency concerns — compare to Pangea where all text is sent to their cloud API.
4-8ms median overhead vs. cloud API round-trips
Layer 1 (regex): <3ms. Layer 2 (vector similarity): 5-10ms. Layer 3 (LLM judge): only for ambiguous cases (~5% of traffic). Median total: 4-8ms — no network round-trip, no cloud dependency, no latency variance by region.
Quick Comparison
| Feature | Rune | Pangea AI Guard |
|---|---|---|
| Product focus | Purpose-built for AI agent security threats | AI scanning module within broader security platform |
| Prompt injection detection | Multi-layer (regex + vector similarity + LLM judge) | Basic pattern matching and content safety rules |
| Agent framework support | 6 frameworks with tool call scanning | Generic content API — no framework awareness |
| Pricing model | Standalone: free tier + $0.05/1K scans | Bundled with Pangea security suite |
| Data privacy | Local-first — metadata-only telemetry | Cloud API — full text sent for processing |
| Data exfiltration detection | Dedicated scanner for encoded data, URL params, tool args | Limited to malicious URL detection |
| PII handling | Detection + alerting (not redaction) | Detection + active redaction (Pangea Redact) |
| Latency overhead | 4-8ms median (local scanning) | 50-200ms (cloud API round-trip) |
You Should Switch If...
- You want agent-specific security without buying a full security platform
- You need deeper prompt injection detection than basic pattern matching
- You're building with agent frameworks and need native tool call scanning
- You want standalone pricing with a free tier
- You need local-first scanning for data privacy compliance
How to Switch from Pangea AI Guard to Rune
- 1Install the Rune SDK: pip install runesec
- 2Initialize Shield as middleware on your agent client
- 3Configure security policies in YAML (default policies cover common threats)
- 4If using Pangea for PII redaction only, you can keep it alongside Rune
- 5Remove Pangea AI Guard scanning calls from your LLM pipeline
- 6Verify detection with test attack payloads
Frequently Asked Questions
Can I use Rune and Pangea AI Guard together?
Yes — and this is a common pattern. Pangea excels at PII redaction (actually removing/masking sensitive data before it reaches the model) and malware scanning on file uploads. Rune excels at agent security: prompt injection detection, data exfiltration through tool calls, secret exposure, and real-time threat monitoring. Use Pangea Redact in your data pipeline, Rune Shield in your agent pipeline.
Does Rune do PII redaction like Pangea?
No — Rune detects PII in model outputs and tool arguments and alerts you, but doesn't actively redact/mask data. If you need active PII redaction (replacing SSNs with [REDACTED] before the model sees them), Pangea Redact is genuinely the better tool for that specific job. Rune catches PII that leaks through despite your redaction layer.
Why not just use Pangea for everything?
Pangea approaches AI security as a content safety problem — scanning text for bad patterns. That works for toxicity and PII, but agent threats like indirect injection through tool returns, data exfiltration via encoded URL parameters, and privilege escalation through multi-step tool abuse require agent-level awareness that content scanning can't provide. Rune sees the agent context (tool calls, framework state, inter-agent messages), not just the text.
What's the honest case for staying with Pangea?
If your primary concern is PII redaction and content safety (toxicity, malicious URLs), and you're already on the Pangea platform for other security modules (AuthN, SecureAudit, Embargo), AI Guard is a natural add-on with zero additional vendor relationships. The case for adding or switching to Rune: you have tool-calling agents, need deeper injection detection, want agent-level visibility, or don't want to buy the full platform for one feature.
Other Alternatives
Lakera Guard Alternative
Lakera Guard was acquired by Palo Alto Networks and shifted enterprise. Rune is the independent, developer-first alternative.
Arthur Shield Alternative
Arthur Shield is enterprise-only with heavy integration overhead. Rune gives you production-grade security in 3 lines of code.
LLM Guard Alternative
LLM Guard is a solid open-source starting point. Rune is what you upgrade to for production agent security.
Related Resources
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