Vulnerability in Agpt Autogpt Classic

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.

Published · last modified .

CVSS v3 metric

CVSS v3 base score 3.1 (Low). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:N/I:L/A:N.

EPSS exploit prediction

EPSS: 0.004 (35.5th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 35th percentile — 35.5% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.

EPSS trend (30 days)EPSS over the last 30 days for CVE-2023-37275: held from 0.004 to 0.004.

EPSS over last 30 days · oldest: 0.004 · newest: 0.004 · change: 0.000

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2023-37275?
CVE-2023-37275 is a low-severity vulnerability in Agpt Autogpt Classic, classified under Improper Output Neutralization for Logs. CVSS score: 3.1/10. Published 2023-07-13.
How severe is CVE-2023-37275?
Low severity. CVSS v3 base score is 3.1 out of 10.
Is CVE-2023-37275 known to be exploited?
1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.