Salus vs Snyk (2026)
Updated March 27, 2026
Overview
Runtime guardrails API that validates AI agent actions against policies before execution, blocking incorrect actions with structured feedback.
Snyk is the developer-first security platform with deep AI security capabilities. Snyk for AI (evolved from DeepCode) scans code, dependencies, containers, and infrastructure-as-code for AI-specific vulnerabilities. Developers use Snyk to detect insecure model loading, prompt injection risks, and vulnerable ML library dependencies directly in their IDE and CI/CD pipelines. The most widely adopted security tool among AI developers.
Key features
Core capabilities each platform advertises.
- Runtime action validation
- Policy-based guardrails
- Pre-execution blocking
- Structured feedback for self-correction
- Agent action auditing
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Solves a critical problem — agents executing incorrect actions can cost enterprises thousands per incident
- Clean developer experience with Python SDK, decorator-based instrumentation, and framework-agnostic compatibility
- 58% self-recovery rate on blocked actions means agents keep working rather than failing hard
- Comprehensive approach combining runtime guardrails, observability, and pre-deployment adversarial evals
- Well-funded at .7M with strong Stanford CS founding team
Cons
- No public pricing creates friction for developer adoption in a space with transparent free tiers
- Very early stage (founded 2026) with a small team and limited enterprise track record
- Competes with Guardrails AI and built-in safety features from OpenAI and Anthropic
- Adding a validation layer introduces latency to every agent action
Pros
- Developer-friendly with seamless IDE and CI/CD integration for shift-left security
- Extensive and continuously updated vulnerability database ensures early threat detection
- Comprehensive coverage across code, containers, IaC, and open-source dependencies
- Strong AI security capabilities specifically designed for ML/AI development workflows
Cons
- Frequent false positives can create alert fatigue and slow down development
- Poor customer support with slow response times during critical security issues
- Scans can take several minutes for medium-sized repositories, slowing CI/CD pipelines
- Documentation quality inconsistent, making troubleshooting and configuration difficult
Salus or Snyk — which should you choose?
Choose Salus if you wantChoose if you want
- Agent safety enforcement
- Action policy compliance
- Runtime guardrails
- Agent audit trails
Choose Snyk if you wantChoose if you want
Compare Salus and Snyk on your own traffic
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