Vulnerability Monitor

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CVE-2023-37275


Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. The Auto-GPT command line UI makes heavy use of color-coded print statements to signify different types of system messages to the user, including messages that are crucial for the user to review and control which commands should be executed. Before v0.4.3, it was possible for a malicious external resource (such as a website browsed by Auto-GPT) to cause misleading messages to be printed to the console by getting the LLM to regurgitate JSON encoded ANSI escape sequences (`\u001b[`). These escape sequences were JSON decoded and printed to the console as part of the model's "thinking process". The issue has been patched in release version 0.4.3.


Security Impact Summary

This vulnerability carries a LOW severity rating with a CVSS v3.1 score of 3.1, indicating it can be exploited remotely over the network but requires specific conditions to be met though user interaction is required and does not require pre-existing privileges . The vulnerability impacts limited integrity, for affected systems. Impacting 1 product from agpt organizations running these solutions should prioritize assessment and patching.

Historical Context

Reported in 2023, this vulnerability emerged during an era marked by increased sophistication in supply chain attacks, cloud infrastructure vulnerabilities, and software-as-a-service (SaaS) security challenges. Security practices during this period emphasized zero-trust architectures, container security, and API protection.


Published

2023-07-13T23:15:10.890

Last Modified

2026-02-24T19:26:13.200

Status

Analyzed

Source

[email protected]

Severity

CVSSv3.1: 3.1 (LOW)

Weaknesses
  • Type: Secondary
    CWE-117

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application agpt autogpt_classic < 0.4.3 Yes

References

How SecUtils Interprets This CVE

SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For agpt's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.