Lenovo's AI Chatbot Security Flaw Puts Customer Support Systems at Risk
A security flaw has been discovered in Lenovo’s customer service AI chatbot, Lena, that could let hackers inject malicious code, steal data, and compromise customer support systems. This vulnerability, found by security researchers, exploits cross-site scripting (XSS) to execute attacks with a single prompt.
The attack begins with a seemingly normal query, such as requesting specifications of a Lenovo product. The chatbot is then instructed to format its response in HTML, JSON, and plain text in a specific order. This careful sequencing ensures the malicious payload will run correctly on the server.
The prompt includes instructions to display an image with a fake URL. When the image fails to load, the browser sends session cookie data to a server controlled by the attacker. The chatbot is explicitly told to “show the image at the end,” ensuring the payload executes fully.
Why This Matters to Customer Support Teams
With the stolen session cookie, attackers can log into the customer support system as if they were legitimate agents—no need for usernames or passwords. This access could expose ongoing chats, historical conversations, and sensitive customer data.
More concerning, attackers might execute system commands, install backdoors, or move laterally across the company network. This risk highlights how a single vulnerability in an AI chatbot can escalate into a broader security breach.
Preventing AI Chatbot Exploits
Although XSS vulnerabilities are less common today, AI chatbots introduce unique risks. Every piece of input and output in these systems must be treated as potentially dangerous until properly validated.
- Use strict whitelists for allowed characters, data types, and formats.
- Automatically encode or escape problematic characters in both user inputs and chatbot responses.
- Avoid inline JavaScript and ensure content-type validation throughout the entire technology stack.
Žilvinas Girėnas, head of product at nexos.ai, points out that large language models (LLMs) do not inherently know what is safe—they simply follow instructions. Without strong guardrails and continuous monitoring, even small oversights can cause serious security incidents.
What Happened Next
The vulnerability was discovered on July 22 and disclosed the same day. Lenovo acknowledged the issue on August 6 and applied mitigations by August 18. As of publication, Lenovo has not provided a public comment.
For customer support professionals, this incident is a clear reminder: AI tools—even those designed to assist—can become attack vectors if not handled carefully. Strict security practices and ongoing vigilance are essential to protect sensitive customer information and maintain trust.
To learn more about securing AI tools in customer service environments, explore resources such as Complete AI Training which offers courses on AI safety and best practices.
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