Evidence used
- No CISA KEV confirmation is currently recorded.
- Exploitation requires an existing local or physical foothold with privileges.
- EPSS is 0.36% for the current model date.
BlackTreeCVE IntelligenceSignificant-Gravitas · Auto-GPT
Official source article: GitHub GHSA-X5GJ-2CHR-4CH6 ↗. Check the applicable product and release in the original source.
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
High technical severity; prioritise exposed affected systems while verifying vendor guidance.
Patch availableAuto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom python code is executed via the `execute_python_file` and `execute_python_code` commands, it can overwrite the docker-compose.yml file and abuse it to gain control of the host system the next time Auto-GPT is started. The issue has been patched in version 0.4.3.
Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom python code is executed via the `execute_python_file` and `execute_python_code` commands, it can overwrite the docker-compose.yml file and abuse it to gain control of the host system the next time Auto-GPT is started. The issue has been patched in version 0.4.3.
Untrusted data can cross into a code-evaluation path and be interpreted as executable instructions.
An attacker operating through local access may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. Running Auto-GPT version prior to 0.4.3 by cloning the git repo and executing `docker compose run auto-gpt` in the repo root uses a different docker-compose.yml file from the one suggested in the official docker set up instructions. The docker-compose.yml file located in the repo root mounts itself into the docker container without write protection. This means that if malicious custom python code is executed via the `execute_python_file` and `execute_python_code` commands, it can overwrite the docker-compose.yml file and abuse it to gain control of the host system the next time Auto-GPT is started. The issue has been patched in version 0.4.3.
Untrusted data can cross into a code-evaluation path and be interpreted as executable instructions.
An attacker operating through local access may attempt exploitation with low privileges. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.
CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.
No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.
No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.
CWE-94: Improper Control of Generation of Code ('Code Injection'). The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:LCommon Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.
Operational remediation based on structured source evidence.
Published 13 Jul 2023 · Last source change 30 Oct 2024, 18:46 UTC · CWE-94 · Improper Control of Generation of Code ('Code Injection')
Core structured fields are present and their contributing authorities are shown above.
No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.