ShadowAI is designed with security as its primary goal. Every design decision focuses on reducing the risk of sensitive information being exposed while keeping the user experience simple and uninterrupted.
ShadowAI follows a "secure by default" approach. Instead of reacting after sensitive information has already been shared, the system identifies potential risks before a prompt reaches an external AI platform. This proactive approach helps organizations adopt AI tools confidently while reducing the chances of accidental data exposure.
Protecting user privacy was one of the main considerations while designing ShadowAI. Only the information required for security analysis is processed, and sensitive prompts are handled over encrypted connections. Security events are logged for auditing purposes, but organizations can configure what information should be stored based on their internal policies.
Access to backend services is protected using JWT-based authentication, ensuring that only authenticated users and trusted browser extensions can communicate with the system. Administrative features such as policy management and analytics are further protected using role-based access control to prevent unauthorized access.
All communication between system components is performed over HTTPS, protecting prompts and metadata from interception during transmission. Encrypted communication ensures that requests remain confidential and are not modified while travelling between the browser extension and backend services.
Rather than relying on a single detection technique, ShadowAI combines multiple methods to improve accuracy.
| Detection Method | Purpose |
|---|---|
| Regular Expressions | Detect API keys, tokens, and credentials |
| Microsoft Presidio | Identify sensitive and personal information |
| spaCy NER | Recognize names, organizations, and locations |
| Custom Risk Engine | Calculate the overall security risk |
This layered approach helps reduce false positives while improving the reliability of prompt analysis.
Every security decision is recorded with relevant metadata, including the detected risk level, action taken, and timestamp. These audit records help administrators monitor AI usage, investigate incidents, and identify recurring security risks across the organization.
ShadowAI is designed with common security and privacy practices in mind. Features such as audit logging, policy-based controls, and controlled access support organizations working towards standards like GDPR, HIPAA, and ISO 27001. While compliance depends on deployment and organizational policies, the platform provides the necessary technical foundation.