{"dataType": "CVE_RECORD", "dataVersion": "5.1", "cveMetadata": {"cveId": "CVE-2024-34359", "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "state": "PUBLISHED", "assignerShortName": "GitHub_M", "dateReserved": "2024-05-02T06:36:32.439Z", "datePublished": "2024-05-10T17:07:18.850Z", "dateUpdated": "2024-08-02T02:51:10.739Z"}, "containers": {"cna": {"title": "llama-cpp-python vulnerable to Remote Code Execution by Server-Side Template Injection in Model Metadata", "problemTypes": [{"descriptions": [{"cweId": "CWE-76", "lang": "en", "description": "CWE-76: Improper Neutralization of Equivalent Special Elements", "type": "CWE"}]}], "metrics": [{"cvssV3_1": {"attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 9.7, "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"}}], "references": [{"name": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "tags": ["x_refsource_CONFIRM"], "url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829"}, {"name": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "tags": ["x_refsource_MISC"], "url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df"}], "affected": [{"vendor": "abetlen", "product": "llama-cpp-python", "versions": [{"version": ">= 0.2.30, <= 0.2.71", "status": "affected"}]}], "providerMetadata": {"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M", "dateUpdated": "2024-05-10T17:07:18.850Z"}, "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` '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."}], "source": {"advisory": "GHSA-56xg-wfcc-g829", "discovery": "UNKNOWN"}}, "adp": [{"affected": [{"vendor": "abetlen", "product": "llama-cpp-python", "cpes": ["cpe:2.3:a:abetlen:llama-cpp-python:*:*:*:*:*:*:*:*"], "defaultStatus": "unknown", "versions": [{"version": "0.2.30", "status": "affected", "lessThanOrEqual": "0.2.71", "versionType": "custom"}]}], "metrics": [{"other": {"type": "ssvc", "content": {"timestamp": "2024-05-15T19:35:24.408358Z", "id": "CVE-2024-34359", "options": [{"Exploitation": "poc"}, {"Automatable": "no"}, {"Technical Impact": "total"}], "role": "CISA Coordinator", "version": "2.0.3"}}}], "title": "CISA ADP Vulnrichment", "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2024-06-06T18:29:15.313Z"}}, {"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-02T02:51:10.739Z"}, "title": "CVE Program Container", "references": [{"name": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829"}, {"name": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df"}]}]}}

{"dataType": "CVE_RECORD", "containers": {"adp": [{"title": "CVE Program Container", "references": [{"url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "name": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "tags": ["x_refsource_CONFIRM", "x_transferred"]}, {"url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "name": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "tags": ["x_refsource_MISC", "x_transferred"]}], "providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-02T02:51:10.739Z"}}, {"title": "CISA ADP Vulnrichment", "metrics": [{"other": {"type": "ssvc", "content": {"id": "CVE-2024-34359", "role": "CISA Coordinator", "options": [{"Exploitation": "poc"}, {"Automatable": "no"}, {"Technical Impact": "total"}], "version": "2.0.3", "timestamp": "2024-05-15T19:35:24.408358Z"}}}], "affected": [{"cpes": ["cpe:2.3:a:abetlen:llama-cpp-python:*:*:*:*:*:*:*:*"], "vendor": "abetlen", "product": "llama-cpp-python", "versions": [{"status": "affected", "version": "0.2.30", "versionType": "custom", "lessThanOrEqual": "0.2.71"}], "defaultStatus": "unknown"}], "providerMetadata": {"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP", "dateUpdated": "2024-05-15T19:53:45.656Z"}}], "cna": {"title": "llama-cpp-python vulnerable to Remote Code Execution by Server-Side Template Injection in Model Metadata", "source": {"advisory": "GHSA-56xg-wfcc-g829", "discovery": "UNKNOWN"}, "metrics": [{"cvssV3_1": {"scope": "CHANGED", "version": "3.1", "baseScore": 9.7, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H", "integrityImpact": "HIGH", "userInteraction": "REQUIRED", "attackComplexity": "LOW", "availabilityImpact": "HIGH", "privilegesRequired": "NONE", "confidentialityImpact": "HIGH"}}], "affected": [{"vendor": "abetlen", "product": "llama-cpp-python", "versions": [{"status": "affected", "version": ">= 0.2.30, <= 0.2.71"}]}], "references": [{"url": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "name": "https://github.com/abetlen/llama-cpp-python/security/advisories/GHSA-56xg-wfcc-g829", "tags": ["x_refsource_CONFIRM"]}, {"url": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "name": "https://github.com/abetlen/llama-cpp-python/commit/b454f40a9a1787b2b5659cd2cb00819d983185df", "tags": ["x_refsource_MISC"]}], "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` '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."}], "problemTypes": [{"descriptions": [{"lang": "en", "type": "CWE", "cweId": "CWE-76", "description": "CWE-76: Improper Neutralization of Equivalent Special Elements"}]}], "providerMetadata": {"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M", "dateUpdated": "2024-05-10T17:07:18.850Z"}}}, "cveMetadata": {"cveId": "CVE-2024-34359", "state": "PUBLISHED", "dateUpdated": "2024-08-02T02:51:10.739Z", "dateReserved": "2024-05-02T06:36:32.439Z", "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "datePublished": "2024-05-10T17:07:18.850Z", "assignerShortName": "GitHub_M"}, "dataVersion": "5.1"}

{"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` '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."}, {"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"}]}

{}