fkie_cve-2024-34359
Vulnerability from fkie_nvd
Published
2024-05-14 15:38
Modified
2024-11-21 09:18
Severity ?
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.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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` \u0027s 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."
},
{
"lang": "es",
"value": "llama-cpp-python son los enlaces de Python para llama.cpp. `llama-cpp-python` depende de la clase `Llama` en `llama.py` para cargar `.gguf` llama.cpp o modelos de aprendizaje autom\u00e1tico de latencia. El constructor `__init__` integrado en `Llama` toma varios par\u00e1metros para configurar la carga y ejecuci\u00f3n del modelo. Adem\u00e1s de `NUMA, configuraci\u00f3n de LoRa`, `carga de tokenizadores` y `configuraci\u00f3n de hardware`, `__init__` tambi\u00e9n carga la `plantilla de chat` desde los metadatos `.gguf` espec\u00edficos y adem\u00e1s la analiza en `llama_chat_format.Jinja2ChatFormatter.to_chat_handler ()` para construir el `self.chat_handler` para este modelo. Sin embargo, `Jinja2ChatFormatter` analiza la `plantilla de chat` dentro del Metadate con `jinja2.Environment` sin zona de pruebas, que adem\u00e1s se representa en `__call__` para construir el `mensaje` de interacci\u00f3n. Esto permite la inyecci\u00f3n de plantilla del lado del servidor `jinja2`, lo que conduce a la ejecuci\u00f3n remota de c\u00f3digo mediante un payload cuidadosamente construida."
}
],
"id": "CVE-2024-34359",
"lastModified": "2024-11-21T09:18:30.130",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.6,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 6.0,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2024-05-14T15:38:45.093",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Awaiting Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-76"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
Loading…
Loading…
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.
Loading…
Loading…