Secuarden is an AI-driven security tool designed to safeguard GitHub repositories by performing deep, intelligent scans. Leveraging advanced Large Language Model capabilities, it identifies security flaws, hidden secrets, and injection vulnerabilities both in source code and within embedded AI prompts, making it a modern security solution for developers using AI-powered codebases. ((
Performance Score
A
Content/Output Quality
High
Interface
User-Friendly
AI Technology
Advanced LLM Integration
Purpose of Tool
Enhance Code Security
Compatibility
GitHub Repositories
Pricing
Free Tier Available
Who is Best for Using Secuarden?
- Development Teams: Enhance code security in GitHub repositories.
- DevSecOps Professionals: Implement smarter vulnerability detection processes.
- Startups and Enterprises: Prioritize early-stage code security to prevent breaches.
- Engineers: Safeguard against hardcoded secrets and prompt injections.
LLM-Powered Security Scans
Secret Detection
Prompt Injection Protection
Real-Time Alerts
CI/CD Integration
Context Confidence Rating
Continuous Learning
Actionable Insights
Is Secuarden Free?
Secuarden offers a free tier with limited scans per month, providing basic vulnerability and secret detection capabilities. This allows users to assess the tool's effectiveness before considering paid plans. ((
Pricing Plans
- Free Tier: Limited scans per month; basic vulnerability and secret detection.
- Pro Plan – Contact for Pricing: Unlimited scans; advanced LLM prompt injection analysis; priority support and integration assistance.
- Enterprise Plan: Custom solutions for large teams; dedicated onboarding and compliance reporting; API access and private instance deployment.
Pros & Cons
Uses contextual understanding for smarter security analysis.
Protects both traditional code and modern AI prompts.
Supports automation through seamless GitHub integration.
Ideal for teams adopting LLMs and AI-powered applications.
Reduces false positives, enhancing developer efficiency.
Primarily focused on GitHub; may not support other platforms.
Might require tuning to reduce false positives in large codebases.
Limited utility for non-AI-focused projects.
Advanced features may require higher-tier plans.
Integration setup may require initial configuration effort.
