CVE-2024-4343

{"id": "CVE-2024-4343", "cveTags": [], "metrics": {"cvssMetricV30": [{"type": "Secondary", "source": "security@huntr.dev", "cvssData": {"scope": "UNCHANGED", "version": "3.0", "baseScore": 9.8, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H", "integrityImpact": "HIGH", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "HIGH"}, "impactScore": 5.9, "exploitabilityScore": 3.9}], "cvssMetricV31": [{"type": "Secondary", "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "cvssData": {"scope": "UNCHANGED", "version": "3.1", "baseScore": 9.8, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H", "integrityImpact": "HIGH", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "HIGH"}, "impactScore": 5.9, "exploitabilityScore": 3.9}]}, "published": "2024-11-14T18:15:19.687", "references": [{"url": "https://github.com/imartinez/privategpt/commit/86368c61760c9cee5d977131d23ad2a3e063cbe9", "source": "security@huntr.dev"}, {"url": "https://huntr.com/bounties/1d1e8f06-ec45-4b17-ae24-b83a41304c15", "source": "security@huntr.dev"}], "vulnStatus": "Awaiting Analysis", "weaknesses": [{"type": "Primary", "source": "security@huntr.dev", "description": [{"lang": "en", "value": "CWE-78"}]}], "descriptions": [{"lang": "en", "value": "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."}, {"lang": "es", "value": "Existe una vulnerabilidad de inyecci\u00f3n de comandos de Python en el m\u00e9todo `complete()` de la clase `SagemakerLLM` dentro de `./private_gpt/components/llm/custom/sagemaker.py` de la aplicaci\u00f3n imartinez/privategpt, versiones hasta la 0.3.0 incluida. La vulnerabilidad surge debido al uso de la funci\u00f3n `eval()` para analizar una cadena recibida desde un punto de conexi\u00f3n remoto de AWS SageMaker LLM en un diccionario. Este m\u00e9todo de an\u00e1lisis no es seguro ya que puede ejecutar c\u00f3digo Python arbitrario contenido en la respuesta. Un atacante puede explotar esta vulnerabilidad manipulando la respuesta del punto de conexi\u00f3n de AWS SageMaker LLM para incluir c\u00f3digo Python malicioso, lo que lleva a la posible ejecuci\u00f3n de comandos arbitrarios en el sistema que aloja la aplicaci\u00f3n. El problema se solucion\u00f3 en la versi\u00f3n 0.6.0."}], "lastModified": "2024-11-18T21:35:08.590", "sourceIdentifier": "security@huntr.dev"}