Users frequently entrust AI assistants with highly sensitive information, including medical records, financial documents, and proprietary business code. Check Point researchers have disclosed a critical vulnerability in ChatGPT's architecture that enables attackers to extract user data covertly. A flaw in ChatGPT's code execution environment demonstrated how a single malicious prompt could quietly exfiltrate sensitive user data without warning or user approval.[1]
The Vulnerability - OpenAI designed the data analysis environment as a secure sandboxed process, intentionally blocking direct outbound HTTP requests to prevent data leakage. Legitimate external API calls, known as GPT Actions, require explicit user consent through visible approval dialogues. However, researchers discovered a significant oversight: whilst conventional internet access was blocked, the container environment still permitted standard DNS resolution.
Exploitation Method - Attackers exploited this oversight by encoding sensitive user data into DNS subdomain labels. Instead of using DNS solely for IP address resolution, the exploit fragments data such as parsed medical diagnoses or financial summaries into manageable portions.
When the runtime performs a recursive lookup, the resolver chain carries the encoded data directly to an attacker-controlled external server. Because the system failed to recognize DNS traffic as an external data transfer, it bypassed all user consent mechanisms.
Attack Vectors - The attack requires minimal user interaction and initiates with a single malicious prompt. Threat actors can distribute these payloads across public forums or social media platforms, disguising them as productivity enhancements to unlock premium ChatGPT capabilities. Once a user inputs the prompt into their chat session, the conversation becomes a covert data-collection channel.
Alternatively, attackers can embed malicious logic directly into Custom GPTs. If users interact with a compromised GPT - such as a fraudulent "personal doctor" analyzing uploaded medical PDFs- the system secretly extracts valuable identifiers and assessments. Since GPT developers officially lack access to individual user chat logs, this side channel provides a stealthy mechanism to harvest private workflows. When questioned directly, the AI confidently denies sending data externally, maintaining a complete illusion of privacy.
Remote Command Execution - Threat actors can encode command fragments into DNS responses, sending instructions back into the isolated sandbox. A process running inside the container could reassemble these payloads and execute them, effectively granting the attacker access. This capability bypassed standard safety mechanisms, with commands and results remaining invisible in the chat interface, leaving users completely unaware of the compromise.
Resolution & Implications - OpenAI has successfully patched the vulnerability, closing the DNS tunnel. However, this incident highlights the expanding attack surface of modern AI assistants as they evolve into complex, multi-layered execution environments.
The incident demonstrates how overlooked components, such as DNS, can introduce security risks if not considered in comprehensive security models. As organizations increasingly rely on AI for critical workflows, improving visibility, strengthening isolation, and validating data flows will be essential to reducing exposure.
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[1] https://www.cybersecurityintelligence.com/blog/chatgpt-dns-exploit-exposed-9269.html
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