CVE-2024-4343
Essential information
- Published
- 14/11/2024 18:15
- Modified
- 18/11/2024 21:35
- Author
- —
- Creator
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- CVSS
- 9.8 CRITICAL (v3.1)
- CISA KEV
- No
- CWE
- —
- CVSS vector
-
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CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H—
CVSS metrics
- Access vector
- —
- Access complexity
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- Authentication
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- Confidentiality impact
- —
- Integrity impact
- —
- Availability impact
- —
- Exploitability
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- Remediation level
- —
- Report confidence
- —
- Temporal score
- —
- Attack vector
- NETWORK
- Attack complexity
- LOW
- Privileges required
- NONE
- User interaction
- NONE
- Scope
- UNCHANGED
- Confidentiality impact
- HIGH
- Integrity impact
- HIGH
- Availability impact
- HIGH
- Exploit code maturity
- —
- Remediation level
- —
- Report confidence
- —
- Temporal score
- —
- Attack vector
- —
- Attack complexity
- —
- Attack requirements
- —
- Privileges required
- —
- User interaction
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- Confidentiality (V)
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- Confidentiality (S)
- —
- Integrity (V)
- —
- Integrity (S)
- —
- Availability (V)
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- Availability (S)
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- Exploit maturity
- —
Description
A Python command injection vulnerability exists in the `SagemakerLLM` class's `complete()` method within `./private_gpt/components/llm/custom/sagemaker.py` of the imartinez/privategpt application, versions up to and including 0.3.0. The vulnerability arises due to the use of the `eval()` function to parse a string received from a remote AWS SageMaker LLM endpoint into a dictionary. This method of parsing is unsafe as it can execute arbitrary Python code contained within the response. An attacker can exploit this vulnerability by manipulating the response from the AWS SageMaker LLM endpoint to include malicious Python code, leading to potential execution of arbitrary commands on the system hosting the application. The issue is fixed in version 0.6.0.
NVD status
- Status
- Awaiting Analysis — CVE has been recently published to the CVE List and has been received by the NVD.
- Source
- [email protected]
- NVD
- View on NVD