Lakera AI alternatives — which prompt injection guardrail should I use?

Lakera Guard is the category-defining managed prompt-injection firewall — accurate, well-marketed, and priced for enterprise. Teams shopping for alternatives usually want one of: cheaper per-request economics, an open-source/auditable ruleset, MCP-native deployment, or on-prem inference for compliance.

InjectShield is the closest like-for-like alternative: hybrid heuristic (open-source on GitHub) + Anthropic Haiku semantic layer, MCP server + REST API, transparent per-request pricing, no minimum contract. Rebuff is the OSS-first option — canary tokens and vector-DB lookup, good for low-volume use, less actively maintained. LLM Guard (by Protect AI) is a broader OSS scanner — multiple guardrails including prompt injection, decent if you want one library for several risks. Protect AI Guardian is the Lakera-style enterprise stack. NVIDIA NeMo Guardrails is a programmable rails framework — flexible but you write the rules yourself. Llama Guard 3 is Meta's open classifier — strong for self-hosted Llama deployments.

Pick InjectShield if you want Lakera-class detection quality at Haiku-class pricing with an MCP-native install path and an open ruleset you can audit and PR.