Securing GenAI in the Enterprise
ChatGPT, Claude, Gemini, Copilot, DeepSeek and more — control, visibility and protection over AI usage and Shadow AI.
As AI tools like ChatGPT, Claude, Gemini, Copilot, GitHub Copilot, and DeepSeek become integrated into every corner of the organization, alongside established systems such as Salesforce, Jira, and Box, a critical need arises: comprehensive control, visibility, and protection over AI usage.
Controlling Shadow AI and Generative AI
Users often engage with dozens of services, sometimes without proper oversight. A Cloud Access Security Broker (CASB) operating inline already provides:
- Visibility into tool usage
- Control over data
Layered on top of this, AI Guardrails add:
- Real-time protection
- Blocking of prompt injection attacks
- Prevention of information leakage
- Enforcement of ethical and approved usage
Agentic AI and MCP Broker
With the advent of intelligent agents like Cursor, Claude Code, and Visual Studio with MCP (Microsoft Copilot), managing these new entities is essential.
The solution involves:
- Monitoring MCP traffic
- Assigning risk scores
- Controlling access to public servers
- Identifying and managing access to MCP Servers
Key capabilities include:
- Real-time monitoring
- Analysis of clients and servers
- Tracking tool and prompt usage
AI Gateway: The Central Protection Layer
The AI Gateway secures the connection between applications and AI models such as ChatGPT, Claude, and Gemini. It includes:
- DLP (Data Loss Prevention) to prevent information leakage
- Guardrails for protection against dangerous content
- Authentication for controlled access
- Rate Limiting to prevent overuse
It provides a unified API for all models and supports AWS, Azure, GCP, and on-premise deployments.
AI Red Teaming
Penetration testing for AI models involves:
- Attack simulations (Jailbreak, Injection)
- Identification of model vulnerabilities
- Mitigation of risks (data leaks, problematic content)
This service works with OpenAI, Azure OpenAI, Amazon Bedrock, and private models.
Summary
To effectively secure AI within an organization, a combination of solutions is necessary:
- Visibility and Control: CASB + MCP Broker
- Protection: AI Gateway + Guardrails + DLP
- Testing: AI Red Teaming
Want to discuss this in your environment?
TALK TO OUR EXPERTS →