> For the complete documentation index, see [llms.txt](https://docs.snyk.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.snyk.io/scan-fix-and-prevent/scan-with-snyk/snyk-api-web/managing-account/enhancing-your-security-with-ai.md). # Enhancing your security with AI How Snyk API & Web uses AI and machine learning to enhance security scanning Leveraging advanced machine learning to improve your application security posture. To help you stay ahead of an ever-evolving threat landscape, Snyk API & Web incorporates advanced AI models in its scanning process. By using AI, Snyk provides a more intelligent, faster, and more comprehensive security experience. ## Key benefits of AI-driven scanning Integrating AI into your security workflow transforms how Snyk detects and manages vulnerabilities. Accounts with AI features enabled can expect improvements in the efficiency of the Snyk crawler and scanner. ## Default settings and account types AI Powered capabilities are governed by the following default settings: * **Trials and paid accounts:** AI-driven scanning is **enabled by default**. This ensures you immediately benefit from higher accuracy and better coverage during your evaluation or subscription. * **Free accounts:** AI-driven scanning is **disabled by default**. To opt out of AI-powered scans for your organization, contact **Snyk Support** to request a change. ## Data privacy and security Snyk prioritizes your privacy and the security of your data. When AI features are active for Snyk API & Web, Snyk handles data as follows: * **What is sent:** Snyk sends specific components of web communications, such as portions of HTTP requests and responses, to the AI model for real-time analysis. * **No training on your data:** Snyk does **not** use your proprietary code or sensitive request data to train, optimize, or fine-tune its AI models. * **Secure infrastructure**: Snyk uses a combination of proprietary models and secure third-party LLMs. For third-party models, Snyk never uses your data for model training and retains it for no more than eight hours. For a comprehensive breakdown of Snyk AI governance and legal commitments, visit [How Snyk incorporates generative AI into the platform](https://docs.snyk.io/working-with-snyk/how-snyk-incorporates-generative-ai-into-the-platform). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.snyk.io/scan-fix-and-prevent/scan-with-snyk/snyk-api-web/managing-account/enhancing-your-security-with-ai.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.