AI Integration Security
Assessing whether SaaS applications are safe for use with Claude Code, GitHub Copilot, and Cursor. Our 9th security dimension evaluates AI agent access controls to prevent data exfiltration at machine scale.
The Problem
AI agents can exfiltrate data at machine scale.
When developers use Claude Code, Copilot, or Cursor with your SaaS stack, those AI agents have programmatic access to your data. Without proper controls, a compromised or misconfigured AI agent could extract sensitive information far faster than any human threat.
Claude Code
Anthropic MCP integration
GitHub Copilot
AI-powered coding assistant
Cursor
AI-first code editor
Why AI Security Matters
⚠️ The Scale Problem
A human attacker might exfiltrate data over hours or days. An AI agent with API access can process thousands of records per second. When Claude Code reads your CRM, every customer record is potentially exposed.
🔓 Permission Creep
Developers often grant OAuth tokens with broad scopes for convenience. AI agents inherit these over-privileged tokens, gaining access to data far beyond what they need for their specific task.
👁️ No Audit Trail
Many SaaS applications cannot distinguish between human and AI agent actions. When an incident occurs, security teams cannot determine what the AI accessed or modified.
🔗 Supply Chain Risk
MCP servers are often community-built. Using an unvetted MCP server is like running untrusted code with access to all your integrations. Server trust verification is critical.
Dual Scoring Model
AI Integration Security is split 50/50 between readiness (can AI integrate?) and security (is AI access safe?). Both are equally important.
AI Readiness
Can AI agents effectively integrate with this application?
- ✓MCP server availability
- ✓Developer experience quality
- ✓Documentation completeness
- ✓API design clarity
AI Security
Is AI agent access properly secured and monitored?
- 🔒OAuth scope granularity
- 🔒Data privacy controls
- 🔒Server trust verification
- 🔒Audit logging for AI actions
What We Assess
AI Integration Security5%NEW - 9th Dimension
Assesses whether the application is safe for AI agent integration using Anthropic's MCP standard. Dual scoring: AI Readiness (50%) evaluates integration capability, AI Security (50%) evaluates safety and data protection.
Evaluation Criteria:
- ✓MCP server availability (official/community)
- ✓OAuth 2.0 support and scope-based permissions
- ✓API documentation quality and code examples
- ✓Data privacy policies for API calls
- ✓Observability and monitoring capabilities
- ✓Rate limiting and anomaly detection
- ✓Audit logging for AI agent actions
Scoring Methodology
Dual scoring: AI Readiness (50%) + AI Security (50%). Official vendor MCP servers score highest. OAuth 2.0 with granular scopes is critical. Comprehensive API docs reduce integration risks.
Example: CRM Data Exposure
Scenario
A developer uses Cursor or Claude Code to query your CRM via its API to help with a sales report.
Risk
The AI agent can access and process every customer record, contact history, and deal value in seconds. Unlike a human analyst who would view records one at a time, the AI has programmatic access to bulk export data.
Key Questions We Assess
- Does the CRM support read-only API tokens?
- Can you limit AI access to specific record types?
- Are API calls logged with agent identification?
- Can you set rate limits specifically for AI agents?
Questions We Answer
Security Teams
"Is it safe to let developers use Claude Code with our SaaS stack?"
IT Administrators
"Which applications have MCP servers we can trust?"
Compliance Officers
"Will AI agent access create audit or compliance gaps?"
Developers
"Which tools have the best AI integration with proper security?"
Protect Against AI Data Exfiltration
When developers use AI coding assistants with your SaaS stack,
are your applications properly secured against machine-scale data access?