Vulnerability in Abetlen Llama-Cpp-Python

CVE-2024-34359

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.

EPSS: 0.284 (98.0th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 9.6 (Critical). Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H.

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2024-34359?
CVE-2024-34359 is a critical-severity vulnerability in Abetlen Llama-Cpp-Python, classified under CWE-76. CVSS score: 9.6/10. Published 2024-05-14.
How severe is CVE-2024-34359?
Critical severity. CVSS v3 base score is 9.6 out of 10.
Is CVE-2024-34359 known to be exploited?
2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.