- CVSS
- CRITICAL · 9.6v3.1CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
- Published
- 2024-05-14
- Weakness
- CWE-76
- Source
- nvd.nist.gov/vuln/detail/CVE-2024-34359
Description
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.
References
- https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df
- https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829
- https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df
- https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829
How GTK Cyber trains on this
AI security training at GTK Cyber covers the LLM and ML-pipeline vulnerability classes that vulnerabilities like CVE-2024-34359 fall into. Our hands-on courses are taught by Charles Givre and other practitioners who break and defend production AI systems.