garak vs Superagent
Side-by-side comparison of two AI agent tools
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garakopen-source
the LLM vulnerability scanner
Superagentopen-source
Superagent protects your AI applications against prompt injections, data leaks, and harmful outputs. Embed safety directly into your app and prove compliance to your customers.
Metrics
| garak | Superagent | |
|---|---|---|
| Stars | 9.4k | 6.8k |
| Star velocity /mo | 782.8333333333334 | 42.19251336898396 |
| Commits (90d) | 225 | 8 |
| Releases (6m) | 4 | 0 |
| Overall score | 0.6430029939451773 | 0.37608835871610674 |
Pros
- +Comprehensive AI security coverage with multiple protection layers including prompt injection detection, PII redaction, and repository scanning
- +Production-ready SDK with dual language support (TypeScript and Python) and straightforward API integration
- +Open-source with strong community backing (6,500+ GitHub stars) and Y Combinator validation
Cons
- -Requires API key and external service dependency, potentially adding latency to AI application workflows
- -Red team testing feature is still in development (marked as 'coming soon')
- -May introduce additional complexity and cost considerations for high-volume AI applications
Use Cases
- •Protecting customer-facing chatbots from prompt injection attacks that could expose system prompts or cause harmful outputs
- •Sanitizing AI-processed documents and conversations to automatically redact sensitive information like SSNs, emails, and medical data for compliance
- •Securing AI development pipelines by scanning code repositories for malicious instructions or AI agent poisoning attempts
FAQ
- Which is more popular, garak or Superagent?
- garak has more GitHub stars (9,394 vs 6,763).
- Which is more actively developed, garak or Superagent?
- garak had more commits in the last 90 days (225 vs 8).
- Should I use garak or Superagent?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.