Securing Enterprise AI Assistants
Enterprise chatbots powered by LLMs have access to internal data, APIs, and business processes. Without proper security controls, they become a vector for data leakage, unauthorized actions, and social engineering.
Risk Categories
Data Leakage
- Employees asking chatbots about sensitive topics, with responses stored in third-party systems
- Chatbot retrieving and displaying classified information to unauthorized users
- Training data containing proprietary information being reproduced
Prompt Injection
- Users manipulating the chatbot to bypass access controls
- Indirect injection through documents the chatbot processes
- Jailbreaking to access restricted functionality
Unauthorized Actions
- Chatbot executing API calls beyond user's authorization level
- Automated workflows triggered by manipulated chatbot output
- Tool-use capabilities exploited for lateral movement
Security Controls
Input Guards
def sanitize_input(user_prompt):
# Check for known injection patterns
if detect_injection(user_prompt):
return "I cannot process that request."
# Check for sensitive data in prompt
if contains_pii(user_prompt):
return "Please do not include personal data in your queries."
return process_safely(user_prompt)
Output Guards
- Filter responses for sensitive data patterns (PII, credentials)
- Apply data classification checks before displaying results
- Redact classified information based on user's clearance level
Access Control
- Integrate chatbot with existing IAM systems
- Apply user's permissions to chatbot's data access
- Audit all chatbot interactions
- Rate limiting per user and per topic
Data Loss Prevention
- Monitor chatbot conversations for data leakage
- Prevent copy/paste of sensitive chatbot responses
- Log and alert on sensitive data retrieval patterns
- Block external sharing of chatbot conversations
Deployment Best Practices
- Host LLM within your infrastructure (or use enterprise agreements with data protection)
- Implement conversation retention policies
- Regular security testing of chatbot capabilities
- Employee training on appropriate chatbot usage
Where SuperClue Fits
SuperClue's LLM modules send a small set of prompt injection and jailbreak probes to chat endpoints they find on your site, such as /api/chat, and flag replies that reveal system instructions or follow an override. These are spot checks, not a full prompt injection assessment. Its DAST scanner also tests the web application and API that host your chatbot for standard web vulnerabilities.