What is the CVSS score of CVE-2024-34359?

CVE-2024-34359 has a CVSS 3.1 base score of 9.6 (Critical). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H. EPSS exploitation probability: 28.4%.

Is there a patch available for CVE-2024-34359?

Yes, a patch is available for CVE-2024-34359. Update the affected software to the latest version immediately.

Python CVE-2024-34359

CRITICAL

Improper Neutralization of Equivalent Special Elements (CWE-76)

2024-05-14 security-advisories@github.com

RCE Python

9.6

CVSS 3.1 · Vendor: github

Severity by source

Vendor (github) PRIMARY

9.6 CRITICAL

AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H

Primary rating from Vendor (github) · only source for this CVE.

CVSS VectorVendor: github

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

Required

Scope

Changed

Confidentiality

High

Integrity

High

Availability

High

Lifecycle Timeline

CVE Published

May 14, 2024 - 15:38 cve.org

CRITICAL 9.6

DescriptionCVE.org

llama-cpp-python is the Python bindings for llama.cpp. llama-cpp-python depends on class Llama in llama.py to load .gguf llama.cpp or Latency Machine Learning Models. The __init__ constructor built in the Llama takes several parameters to configure the loading and running of the model. Other than NUMA, LoRa settings, loading tokenizers, and hardware settings, __init__ also loads the chat template from targeted .gguf 's Metadata and furtherly parses it to llama_chat_format.Jinja2ChatFormatter.to_chat_handler() to construct the self.chat_handler for this model. Nevertheless, Jinja2ChatFormatter parse the chat template within the Metadate with sandbox-less jinja2.Environment, which is furthermore rendered in __call__ to construct the prompt of interaction. This allows jinja2 Server Side Template Injection which leads to remote code execution by a carefully constructed payload.

AnalysisAI

llama-cpp-python is the Python bindings for llama.cpp. Rated critical severity (CVSS 9.6), this vulnerability is remotely exploitable, no authentication required, low attack complexity. No vendor patch available.

Technical ContextAI

This vulnerability is classified under CWE-76. llama-cpp-python is the Python bindings for llama.cpp. llama-cpp-python depends on class Llama in llama.py to load .gguf llama.cpp or Latency Machine Learning Models. The __init__ constructor built in the Llama takes several parameters to configure the loading and running of the model. Other than NUMA, LoRa settings, loading tokenizers, and hardware settings, __init__ also loads the chat template from targeted .gguf 's Metadata and furtherly parses it to llama_chat_format.Jinja2ChatFormatter.to_chat_handler() to construct the self.chat_handler for this model. Nevertheless, Jinja2ChatFormatter parse the chat template within the Metadate with sandbox-less jinja2.Environment, which is furthermore rendered in __call__ to construct the prompt of interaction. This allows jinja2 Server Side Template Injection which leads to remote code execution by a carefully constructed payload.

Affected ProductsAI

See vendor advisory for affected versions.

RemediationAI

No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.