Bully Chatbot – Business Logic Abuse in Automated Support Chat

Abstract

This penetration test was conducted in a controlled laboratory environment using the OWASP Juice Shop application.
The objective of this challenge was to obtain a discount coupon code from the integrated support chatbot.

By repeatedly sending the same request to the chatbot, a coupon code was automatically disclosed after a predefined number of interactions. The chatbot does not implement any form of artificial intelligence, large language model (LLM), or contextual reasoning. Instead, it follows a static, rule-based conversation flow with insufficient abuse protection.

This challenge demonstrates a classic business logic flaw, where functional requirements are met, but misuse scenarios are not adequately considered.

Preparation Documentation

Identified Vulnerability / Vulnerabilities and Risk Assessment

• Identified Vulnerability: Business Logic Abuse in Automated Chatbot
• Category: Improper Business Logic / Missing Abuse Controls
• OWASP Top 10 Mapping: A04: Insecure Design
• Risk Assessment: Low
• Potential Impact:
  • Unauthorized distribution of discount codes
  • Financial loss through abuse of promotions
  • Reputation damage due to predictable automation behavior

Known Exploits

• No specific CVE is associated with this issue.
• This weakness class is commonly described in:
  • OWASP Top 10 – A04: Insecure Design
  • OWASP Juice Shop business logic challenges
• Typical exploit pattern:
  • Repeated interaction triggering hardcoded reward logic
  • Lack of rate limiting or state validation

Execution of the Penetration Test

• Affected Component: Support Chat (juicy-chat-bot)

• Access Path:

  /#/chatbot
  

• Tools Used:

  • Web browser
  • Manual interaction (no automation)

• Testing Method:

  • Repeated input submission
  • Observation of chatbot responses

• Assumptions and Constraints:

  • Test performed on a local OWASP Juice Shop instance
  • No authentication required
  • Scope limited to chatbot interaction

Results Documentation

Accessible Information

• Chatbot responses are fully deterministic
• No personalization, context awareness, or AI-driven behavior observed
• Coupon code disclosed directly in chat output

No sensitive backend data, credentials, or configuration details were exposed.

Exploitation Depth

• Abuse limited to chatbot interaction
• No access to internal systems or APIs
• No privilege escalation or lateral movement possible
• Exploitation purely at the business logic level

Discovery Process

• Manual interaction with the chatbot
• Observation that repeated identical messages were accepted
• Hypothesis that chatbot follows a fixed response counter

Exploitation Process

1. Navigated to the Support Chat page.
2. Sent a request asking for a discount code.
3. Repeated the same request a second time.
4. After the second repeated request, the chatbot disclosed a coupon code.
5. The challenge was marked as completed.

The chatbot behavior was static and predictable and did not involve any intelligent decision-making.

Outcome

• A valid discount coupon code was successfully obtained.
• The challenge “Bully Chatbot” was completed.
• Demonstrated abuse of deterministic chatbot logic.
• Confirmed absence of AI, LLM, or adaptive chatbot mechanisms.

Mitigation Measures

• Implement rate limiting on chatbot interactions.
• Add stateful validation (e.g. per-user or per-session limits).
• Require authentication or verification before issuing discount codes.
• Introduce server-side checks for repeated or abusive requests.

Recommendations and Prioritization

• Priority: Low
• Review all promotional and reward-related logic for abuse scenarios.
• Treat chatbots as public-facing APIs, not as trusted interfaces.
• Include business logic abuse cases in threat modeling exercises.