Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
Low
Attack Vector
Local
0

CVE-2023-37274

Disclosure Date: July 13, 2023
Add MITRE ATT&CK tactics and techniques that apply to this CVE.

Description

Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. When Auto-GPT is executed directly on the host system via the provided run.sh or run.bat files, custom Python code execution is sandboxed using a temporary dedicated docker container which should not have access to any files outside of the Auto-GPT workspace directory.
Before v0.4.3, the execute_python_code command (introduced in v0.4.1) does not sanitize the basename arg before writing LLM-supplied code to a file with an LLM-supplied name. This allows for a path traversal attack that can overwrite any .py file outside the workspace directory by specifying a basename such as ../../../main.py. This can further be abused to achieve arbitrary code execution on the host running Auto-GPT by e.g. overwriting autogpt/main.py which will be executed outside of the docker environment meant to sandbox custom python code execution the next time Auto-GPT is started. The issue has been patched in version 0.4.3. As a workaround, the risk introduced by this vulnerability can be remediated by running Auto-GPT in a virtual machine, or another environment in which damage to files or corruption of the program is not a critical problem.

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CVSS V3 Severity and Metrics
Base Score:
7.8 High
Impact Score:
5.9
Exploitability Score:
1.8
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Attack Vector (AV):
Local
Attack Complexity (AC):
Low
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
High
Integrity (I):
High
Availability (A):
High

General Information

Vendors

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Weaknesses

Additional Info

Technical Analysis