Best Data Security Software for Visual Studio Code

Find and compare the best Data Security software for Visual Studio Code in 2025

Use the comparison tool below to compare the top Data Security software for Visual Studio Code on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Jit Reviews
    Jit's DevSecOps Orchestration Platform allows high-velocity Engineering teams to own product security while increasing dev velocity. With a unified and friendly developer experience, we envision a world where every cloud application is born with Minimal Viable Security (MVS) embedded and iteratively improves by adding Continuous Security into CI/CD/CS.
  • 2
    Noma Reviews
    Transitioning from development to production, as well as from traditional data engineering to artificial intelligence, requires securing the various environments, pipelines, tools, and open-source components integral to your data and AI supply chain. It is essential to continuously identify, prevent, and rectify security and compliance vulnerabilities in AI before they reach production. In addition, monitoring AI applications in real-time allows for the detection and mitigation of adversarial AI attacks while enforcing specific application guardrails. Noma integrates smoothly across your data and AI supply chain and applications, providing a detailed map of all data pipelines, notebooks, MLOps tools, open-source AI elements, and both first- and third-party models along with datasets, thereby automatically generating a thorough AI/ML bill of materials (BOM). Additionally, Noma constantly identifies and offers actionable solutions for security issues, including misconfigurations, AI-related vulnerabilities, and non-compliant training data usage throughout your data and AI supply chain. This proactive approach enables organizations to enhance their AI security posture effectively, ensuring that potential threats are addressed before they can impact production. Ultimately, adopting such measures not only fortifies security but also boosts overall confidence in AI systems.
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