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October 24, 2026

Breaking the Vault: Bypassing Chatbot Limits via Race Conditions & Response Manipulation

In modern fintech and digital platforms, features like AI-powered chatbots aren’t just cool perks — they are massive cost drivers…

By Ahmed 3zzazy

4 min read

In modern fintech and digital platforms, features like AI-powered chatbots aren't just cool perks — they are massive cost drivers. Leveraging Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) means every single prompt processed by the backend burns valuable API tokens and compute resources.

To keep operational costs in check, applications implement strict limits — such as a maximum of 5 active chatbot conversations per user.

This write-up explores how an attacker can completely obliterate this business logic limit by chaining three distinct vulnerabilities: a Race Condition, a Frontend Logic Bypass, and a Backend Logic Bypass. The result? Infinite chat sessions, completely bypassed tier limitations, and a severe Denial of Wallet (DoW) vector.

🔍 The Anatomy of the Vulnerability

The application's limitation enforcement relies on two pillars:

  1. Frontend State: The UI counts conversations via a GET /conversations endpoint and locks the "New Conversation" button if the array length reaches 5.
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2. Backend Validation: The /init endpoint checks the database count before allowing a new conversation. If a user tries to force it, the backend responds with an HTTP 429 Too Many Requests.

By combining concurrency with client-side trust, an attacker can bypass both layers entirely.

🛠️ Step-by-Step Exploitation

Part 1: Generating Valid IDs via Race Condition 🏎️

When a user has already created 4 conversations and attempts to create the 5th, normal sequential requests are safely blocked. However, computers operate on milliseconds.

  1. The attacker creates 4 chats normally.

  2. They intercept the request to create the 5th conversation using Burp Suite:

POST /redacted/api/v1/chatbot/conversations/init HTTP/2
Host: redacted.com
Authorization: Bearer eyJhbGci…[TRUNCATED]
Content-Type: application/json

{"platform":"website"}
  1. Using Turbo Intruder or Burp Repeater's "Send group in parallel" feature, the attacker fires multiple concurrent requests (3–5 requests simultaneously) right before hitting the hard limit.
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4. The Flaw: Due to a lack of proper database locking or atomic operations on the count check, the server races past the check and returns 200 OK for multiple concurrent requests, generating several valid conversation_id tokens in the database. The attacker saves one of these hidden IDs.

Part 2: Bypassing Frontend Enforcement 🖥️

With the database now holding more than 5 conversations, the frontend naturally locks down the UI because its state reflects reality. Time to trick the client.

  1. The attacker navigates back to the chat dashboard, triggering a GET request to fetch the conversation list:
GET /redacted/api/v1/chatbot/conversations HTTP/2
Host: redacted.com
Authorization: Bearer eyJhbGci…[TRUNCATED]
  1. The server responds with the true list of 5 active chats:
{
 “conversations”: [
 {“id”:”97f242…”},
 {“id”:”74ec92…”},
 {“id”:”bd5887…”},
 {“id”:”943598…”},
 {“id”:”cc278a…”}
 ]
}
  1. Response Manipulation 1: The attacker intercepts this response in Burp Suite and deletes one JSON object from the array before forwarding it.

4. The Result: The frontend believes only 4 chats exist, instantly re-enabling the "New Conversation" button.

Part 3: Bypassing Backend Enforcement 🛡️

Now that the UI is unlocked, the attacker attempts to start a brand new conversation.

  1. Clicking "New Conversation" sends a standard POST /init request.
  2. Because the backend database knows the user actually has 5+ chats, it correctly rejects the attempt:
HTTP/2 429 Too Many Requests
Content-Type: application/json

{"detail":"You have reached the limit of active conversations. Please delete one of your previous conversations to start a new one."}

3. Response Manipulation 2: Instead of accepting defeat, the attacker intercepts this error response, changes the status code from 429 Too Many Requests to 200 OK, and hot-swaps the body with a success message injecting the pre-harvested conversation_id from Part 1:

{
 “status”: “success”,
 “conversation_id”: “[INSERT_RACE_CONDITION_ID_HERE]”,
 “platform”: “dashboard”,
 “message”: “User registered and initial conversation created.”
}
  1. The Result: The frontend happily accepts the payload. The attacker can now seamlessly chat in this new session. All subsequent message requests using this ID are processed normally by the backend, completely bypassing the limit!
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Impact Analysis

This multi-stage chain is far more than a simple UI glitch; it introduces serious business risks:

  • 🔥 Financial Exhaustion (Denial of Wallet): RAG systems lean heavily on expensive LLM tokens (e.g., OpenAI, Anthropic APIs) per query. An attacker can script this bypass to spin up thousands of parallel conversations, flooding the backend with endless prompts and driving up massive cloud/API bills.
  • 📉 Degradation of Critical Banking Services: As a fintech and wallet application, uptime and fast customer support are paramount. Flooding the RAG infrastructure with unauthorized queries drains database and retrieval resources, slowing down or crashing support bots for legitimate customers who urgently need help with transactions.
  • 🚪 Total Subversion of Business Tiering: In modern SaaS and fintech ecosystems, AI capabilities are often tiered (e.g., restricted to premium users or rate-limited to control operational overhead). This flaw allows any basic or malicious user to abuse unlimited enterprise-grade resources for free.

Final Status & Outcome

  • Status: Accepted & Resolved
  • Severity: Low (CVSS 3.1)
  • Bounty Awarded: $50 💰

The report was triaged and accepted as Low Severity (CVSS 3.1) with a $50 bounty, acknowledging the valid logic flaw and concurrency issue in backend validation.

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