Trussed vs. Lakera
Specialized Attack Detection vs. Full MCP Governance. Lakera, now operating as Check Point AI Guardrails following its September 2025 acquisition, is a specialized AI security API built around deep detection of prompt attacks, jailbreaks, and indirect injection. Trussed is a broader production AI control plane that includes prompt injection detection alongside data protection, code artifact security, system prompt leakage detection, advanced adversarial controls, and governance infrastructure.
The prompt injection problem in MCP environments
Prompt injection became the most significant AI security risk in the 2025 OWASP Top 10 for LLMs. In MCP-enabled environments, the attack surface expands considerably: a compromised tool response, a poisoned document retrieved by the agent, a malicious instruction in an MCP tool's description, all can deliver prompt injection without any visible user action.
Capability comparison
| Capability | Trussed | Lakera | Notes |
|---|---|---|---|
| Prompt injection | ✓ | ✓ | Lakera 95%+ accuracy on PINT benchmark (vendor figure); Trussed via inline proxy |
| Jailbreak detection | ✓ | ✓ | Both confirmed; Lakera continuously updated for new techniques |
| Indirect prompt injection | ✓ | ✓ | Both confirmed; Lakera screens tool descriptions, inputs, and outputs |
| PII detection | ✓ | — | Trussed confirmed; Lakera focused on attack detection, not data classification |
| PHI detection | ✓ | — | Trussed confirmed for regulated industries; Lakera not confirmed |
| System prompt leakage | ✓ | ◐ | Trussed confirmed; Lakera coverage via attack detection, discrete capability requires verification |
| Code secret detection | ✓ | — | Trussed detects API keys in code artifacts; Lakera not confirmed |
| Source code provenance | ✓ | — | Trussed-unique; Lakera not confirmed |
| Unicode manipulation | ✓ | ◐ | Trussed confirmed; Lakera partial per research |
| Language authenticity | ✓ | — | Trussed-unique adversarial evasion capability |
| Content moderation | ✓ | ✓ | Both confirmed; Lakera primary focus is adversarial attack detection |
| Sensitive topic controls | ✓ | — | Trussed supports org-specific topic restrictions; Lakera not a primary focus |
| Audit logging | ✓ | ◐ | Trussed generates compliance-grade evidence; Lakera provides security event logs |
| Cross-model support | ✓ | ✓ | Both model-agnostic via API integration |
| Multilingual detection | ✓ | ✓ | Lakera confirmed 100+ languages; strong for global deployments |
| Self-hosted deployment | ◐ | — | Trussed may offer on-premises options; Lakera SaaS only, self-hosted not confirmed |
Assessment
For regulated enterprises requiring a unified control plane across data protection, MCP security, and compliance audit infrastructure, Trussed covers significantly more of the required control surface. Lakera's adversarial detection depth is a genuine advantage in its specific area, and the two platforms are complementary rather than interchangeable.
Where Trussed goes further
- Full data protection layer. PII and PHI detection, code secret detection, and source code provenance address the data and code dimensions of MCP security that fall outside Lakera's primary scope.
- Advanced adversarial controls beyond injection. Language authenticity analysis and unicode manipulation detection address attack patterns designed specifically to evade conventional classifiers.
- Governance and audit infrastructure. Compliance-grade audit records for every governed interaction, supporting HIPAA, the EU AI Act, and other regulations.
- System prompt leakage detection. A confirmed discrete capability protecting business logic and tool authorization boundaries encoded in system prompts.
Where Lakera has specific strengths
- Specialized adversarial detection depth. Classification models trained on an exceptionally large corpus of adversarial prompts, including data generated through the Gandalf challenge played by over 1 million users.
- Indirect injection screening across MCP interaction points. Lakera explicitly documents detection across tool descriptions, inputs, and outputs.
- Real-time low-latency detection. Sub-50ms detection latency (vendor figure) and support for 100+ languages.
- Check Point ecosystem integration. Capabilities are being integrated into Check Point's broader AI security platform.
When to choose each platform
Choose Lakera when
- Deep adversarial detection with a continuous training loop is the primary requirement
- Detection latency is a hard constraint
- The deployment spans many languages
- PII, PHI, code security, and audit trails are handled elsewhere
Choose Trussed when
- A unified control plane for prompt security, data protection, and audit logging is needed
- PII/PHI, code secrets, or source code provenance are in scope
- Compliance-grade audit trails are required
- Unicode manipulation or language authenticity controls address adversarial evasion
Frequently Asked Questions
Related resources
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