GenAI Fixes, On-Prem Control

At CodeThreat, we understand the critical need for robust, on-premise code security solutions that align with the unique infrastructure and operational dynamics of each enterprise.

With this understanding, we are excited to introduce the GenAI-based Fix Suggestions within On-Prem Environments.

GenAI Based SAST Fix Suggestions

Identifying vulnerabilities is only the beginning. The real value lies in what happens next. Our GenAI-powered fix suggestion ensures that every identified issue is accompanied by clear, practical guidance on how to address it, transforming insights into actions.

Users often face challenges in determining whether an issue warrants action, deciding on the appropriate response, or understanding the potential trade-offs associated with addressing a particular problem.

Why?

The decision to integrate GenAI with SAST in an on-premise environment is grounded in a deep understanding of the current application security ecosystem and the unique demands of maintaining in-house data control.

1. Relevant Fix Suggestion: By integrating GenAI within the SAST process, we’re providing context-rich, precise insights that are directly applicable to your specific environment, enhancing the relevance and impact of every analysis.
   Empowerment Through Understanding: Actionability is not just about providing a list of steps; it’s about ensuring that every stakeholder understands the ‘why’ and the ‘how’ behind each action. This understanding empowers teams, fostering a proactive security culture.

2. Control and Compliance: For enterprises operating on-premise, data control and compliance are non-negotiable. This integration ensures that while you leverage the advanced capabilities of GenAI, your data remains within the secure perimeter of your infrastructure.

Currently, we offer options for Ollama, Azure OpenAI, OpenAI, and Anthropic.

CodeThreat SAST GenAI Integration settings allows users to choose whether they want to utilize an on-premise model within their own controlled infrastructure or opt for a different setup, providing flexibility and control over their AI integration.

1. Custom Configuration: We begin by tailoring the GenAI model to your specific operational context. This ensures that the insights provided are not just accurate but also highly relevant to your unique environment.
   
   Conclusion

   As organizations navigate through the integration of GenAI applications within their security pipelines, the inclusion of CodeThreat’s LLM options within our application emerges as a significant and innovative step. We recognize the importance of this journey and view it as a collaborative exploration, where each phase brings us closer to realizing the full potential of GenAI in enhancing static analysis results