Alternatives
Each entry names the thing people usually leave for, then names the case Rune is actually a better fit. Click through for migration steps, a feature-by-feature comparison, and the full evaluation.
Why teams leave: Enterprise pricing after the Check Point acquisition. Since Check Point completed the ~$187M acquisition in October 2025, Lakera Guard has been folded into Check Point's enterprise AI security platform with enterprise-only pricing.
When Rune fits: If you want developer pricing, framework-native integration, and no external API round-trip.
Why teams leave: Steep Colang learning curve. NeMo Guardrails requires writing rules in Colang 2.0, NVIDIA's custom modeling language with its own syntax for flows, actions, and guards.
When Rune fits: If you want runtime threat detection rather than scripted conversation flow.
Why teams leave: Output validation ≠ security. Guardrails AI excels at validating LLM output format and quality but doesn't focus on security threats like prompt injection, data exfiltration, or privilege escalation..
When Rune fits: If you need input scanning and tool-call awareness, not just output validation.
Why teams leave: Slowing maintenance — last PyPI release months ago. LLM Guard's GitHub activity and PyPI release cadence have slowed significantly since mid-2025.
When Rune fits: If you want a managed dashboard without running your own scanner infrastructure.
Why teams leave: Narrow scope — prompt injection only. Prompt Armor focuses exclusively on classifying text as injection or not.
When Rune fits: If you need a full agent runtime (policies, tool scanning, dashboard) — not just an injection filter.
Why teams leave: Enterprise-only pricing — five-figure annual minimums. Arthur Shield requires custom enterprise contracts with multi-month procurement cycles.
When Rune fits: If you don’t have an enterprise procurement team and want to ship this week.
Why teams leave: Effectively abandoned — last meaningful commit in 2023. Rebuff's GitHub repository has had no significant updates since late 2023.
When Rune fits: If you need a platform that still ships, not an abandoned research project.
Why teams leave: 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.).
When Rune fits: If you don’t want to pay for a full security suite to get AI coverage.
Why teams leave: Static audits miss runtime attacks. SecureClaw runs 55 OWASP-based checks against your OpenClaw configuration at deploy time.
Five things matter most: detection accuracy (low false positives, catches novel attacks), latency (under 20ms for real-time blocking), framework support (native integration, not API wrappers), policy enforcement (block vs. alert vs. redact per rule), and observability (per-agent risk scores, alert routing, event timeline). Evaluate each tool against these criteria for your specific use case.
Open-source tools like LLM Guard and Rebuff give you full control and zero cost, but require self-hosting, maintenance, and building your own monitoring dashboard. Commercial tools like Rune and Lakera Guard provide managed infrastructure, real-time dashboards, and dedicated detection model updates. Most teams start with a commercial tool for speed, then evaluate open-source for specific compliance or customization needs.
Yes, and some teams do — for example, using Rune for runtime scanning and NeMo Guardrails for conversation flow control. However, multiple tools add latency and complexity. Rune's multi-layer detection (pattern + semantic + LLM judge) is designed to be comprehensive enough as a single solution.
The best comparison is hands-on.
Install Rune, wrap your agent, see what it catches.