CVE DATABASE / CVE-2024-34359
CVE-2024-34359
Summary
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.
CVSS 3.1 breakdown
| 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 |
| Attack vector | NETWORK |
| Attack complexity | LOW |
| Privileges required | NONE |
| User interaction | REQUIRED |
| Scope | CHANGED |
| Confidentiality | HIGH |
| Integrity | HIGH |
| Availability | HIGH |
Weakness type (CWE)
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References
- https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df
- https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829
Data: NIST NVD. NVD last modified 2026-04-15. Always verify against the vendor advisory before acting.