CVE-2025-32434 (GCVE-0-2025-32434)
Vulnerability from cvelistv5
Published
2025-04-18 15:48
Modified
2025-04-18 16:06
Severity ?
VLAI Severity ?
EPSS score ?
CWE
- CWE-502 - Deserialization of Untrusted Data
Summary
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
References
► | URL | Tags | |
---|---|---|---|
{ "containers": { "adp": [ { "metrics": [ { "other": { "content": { "id": "CVE-2025-32434", "options": [ { "Exploitation": "none" }, { "Automatable": "yes" }, { "Technical Impact": "total" } ], "role": "CISA Coordinator", "timestamp": "2025-04-18T16:06:40.000632Z", "version": "2.0.3" }, "type": "ssvc" } } ], "providerMetadata": { "dateUpdated": "2025-04-18T16:06:51.966Z", "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "shortName": "CISA-ADP" }, "title": "CISA ADP Vulnrichment" } ], "cna": { "affected": [ { "product": "pytorch", "vendor": "pytorch", "versions": [ { "status": "affected", "version": "\u003c 2.6.0" } ] } ], "descriptions": [ { "lang": "en", "value": "PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0." } ], "metrics": [ { "cvssV4_0": { "attackComplexity": "LOW", "attackRequirements": "NONE", "attackVector": "NETWORK", "baseScore": 9.3, "baseSeverity": "CRITICAL", "privilegesRequired": "NONE", "subAvailabilityImpact": "NONE", "subConfidentialityImpact": "NONE", "subIntegrityImpact": "NONE", "userInteraction": "NONE", "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N", "version": "4.0", "vulnAvailabilityImpact": "HIGH", "vulnConfidentialityImpact": "HIGH", "vulnIntegrityImpact": "HIGH" } } ], "problemTypes": [ { "descriptions": [ { "cweId": "CWE-502", "description": "CWE-502: Deserialization of Untrusted Data", "lang": "en", "type": "CWE" } ] } ], "providerMetadata": { "dateUpdated": "2025-04-18T15:48:18.851Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M" }, "references": [ { "name": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6", "tags": [ "x_refsource_CONFIRM" ], "url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6" } ], "source": { "advisory": "GHSA-53q9-r3pm-6pq6", "discovery": "UNKNOWN" }, "title": "PyTorch: `torch.load` with `weights_only=True` leads to remote code execution" } }, "cveMetadata": { "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2025-32434", "datePublished": "2025-04-18T15:48:18.851Z", "dateReserved": "2025-04-08T10:54:58.368Z", "dateUpdated": "2025-04-18T16:06:51.966Z", "state": "PUBLISHED" }, "dataType": "CVE_RECORD", "dataVersion": "5.1", "vulnerability-lookup:meta": { "nvd": "{\"cve\":{\"id\":\"CVE-2025-32434\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2025-04-18T16:15:23.183\",\"lastModified\":\"2025-05-28T13:14:20.750\",\"vulnStatus\":\"Analyzed\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.\"},{\"lang\":\"es\",\"value\":\"PyTorch es un paquete de Python que proporciona computaci\u00f3n tensorial con una potente aceleraci\u00f3n de GPU y redes neuronales profundas basadas en un sistema de autogradaci\u00f3n basado en cinta. En la versi\u00f3n 2.5.1 y anteriores, exist\u00eda una vulnerabilidad de ejecuci\u00f3n remota de comandos (RCE) en PyTorch al cargar un modelo usando torch.load con weights_only=True. Este problema se ha corregido en la versi\u00f3n 2.6.0.\"}],\"metrics\":{\"cvssMetricV40\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"4.0\",\"vectorString\":\"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X\",\"baseScore\":9.3,\"baseSeverity\":\"CRITICAL\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"LOW\",\"attackRequirements\":\"NONE\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"vulnConfidentialityImpact\":\"HIGH\",\"vulnIntegrityImpact\":\"HIGH\",\"vulnAvailabilityImpact\":\"HIGH\",\"subConfidentialityImpact\":\"NONE\",\"subIntegrityImpact\":\"NONE\",\"subAvailabilityImpact\":\"NONE\",\"exploitMaturity\":\"NOT_DEFINED\",\"confidentialityRequirement\":\"NOT_DEFINED\",\"integrityRequirement\":\"NOT_DEFINED\",\"availabilityRequirement\":\"NOT_DEFINED\",\"modifiedAttackVector\":\"NOT_DEFINED\",\"modifiedAttackComplexity\":\"NOT_DEFINED\",\"modifiedAttackRequirements\":\"NOT_DEFINED\",\"modifiedPrivilegesRequired\":\"NOT_DEFINED\",\"modifiedUserInteraction\":\"NOT_DEFINED\",\"modifiedVulnConfidentialityImpact\":\"NOT_DEFINED\",\"modifiedVulnIntegrityImpact\":\"NOT_DEFINED\",\"modifiedVulnAvailabilityImpact\":\"NOT_DEFINED\",\"modifiedSubConfidentialityImpact\":\"NOT_DEFINED\",\"modifiedSubIntegrityImpact\":\"NOT_DEFINED\",\"modifiedSubAvailabilityImpact\":\"NOT_DEFINED\",\"Safety\":\"NOT_DEFINED\",\"Automatable\":\"NOT_DEFINED\",\"Recovery\":\"NOT_DEFINED\",\"valueDensity\":\"NOT_DEFINED\",\"vulnerabilityResponseEffort\":\"NOT_DEFINED\",\"providerUrgency\":\"NOT_DEFINED\"}}],\"cvssMetricV31\":[{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H\",\"baseScore\":9.8,\"baseSeverity\":\"CRITICAL\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"HIGH\",\"integrityImpact\":\"HIGH\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":3.9,\"impactScore\":5.9}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-502\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:linuxfoundation:pytorch:*:*:*:*:*:python:*:*\",\"versionEndExcluding\":\"2.6.0\",\"matchCriteriaId\":\"F694B541-FC4E-4A7D-8A1A-0DA11BEC83CD\"}]}]}],\"references\":[{\"url\":\"https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Vendor Advisory\"]}]}}", "vulnrichment": { "containers": "{\"adp\": [{\"title\": \"CISA ADP Vulnrichment\", \"metrics\": [{\"other\": {\"type\": \"ssvc\", \"content\": {\"id\": \"CVE-2025-32434\", \"role\": \"CISA Coordinator\", \"options\": [{\"Exploitation\": \"none\"}, {\"Automatable\": \"yes\"}, {\"Technical Impact\": \"total\"}], \"version\": \"2.0.3\", \"timestamp\": \"2025-04-18T16:06:40.000632Z\"}}}], \"providerMetadata\": {\"orgId\": \"134c704f-9b21-4f2e-91b3-4a467353bcc0\", \"shortName\": \"CISA-ADP\", \"dateUpdated\": \"2025-04-18T16:06:43.402Z\"}}], \"cna\": {\"title\": \"PyTorch: `torch.load` with `weights_only=True` leads to remote code execution\", \"source\": {\"advisory\": \"GHSA-53q9-r3pm-6pq6\", \"discovery\": \"UNKNOWN\"}, \"metrics\": [{\"cvssV4_0\": {\"version\": \"4.0\", \"baseScore\": 9.3, \"attackVector\": \"NETWORK\", \"baseSeverity\": \"CRITICAL\", \"vectorString\": \"CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N\", \"userInteraction\": \"NONE\", \"attackComplexity\": \"LOW\", \"attackRequirements\": \"NONE\", \"privilegesRequired\": \"NONE\", \"subIntegrityImpact\": \"NONE\", \"vulnIntegrityImpact\": \"HIGH\", \"subAvailabilityImpact\": \"NONE\", \"vulnAvailabilityImpact\": \"HIGH\", \"subConfidentialityImpact\": \"NONE\", \"vulnConfidentialityImpact\": \"HIGH\"}}], \"affected\": [{\"vendor\": \"pytorch\", \"product\": \"pytorch\", \"versions\": [{\"status\": \"affected\", \"version\": \"\u003c 2.6.0\"}]}], \"references\": [{\"url\": \"https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6\", \"name\": \"https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6\", \"tags\": [\"x_refsource_CONFIRM\"]}], \"descriptions\": [{\"lang\": \"en\", \"value\": \"PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.\"}], \"problemTypes\": [{\"descriptions\": [{\"lang\": \"en\", \"type\": \"CWE\", \"cweId\": \"CWE-502\", \"description\": \"CWE-502: Deserialization of Untrusted Data\"}]}], \"providerMetadata\": {\"orgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"shortName\": \"GitHub_M\", \"dateUpdated\": \"2025-04-18T15:48:18.851Z\"}}}", "cveMetadata": "{\"cveId\": \"CVE-2025-32434\", \"state\": \"PUBLISHED\", \"dateUpdated\": \"2025-04-18T16:06:51.966Z\", \"dateReserved\": \"2025-04-08T10:54:58.368Z\", \"assignerOrgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"datePublished\": \"2025-04-18T15:48:18.851Z\", \"assignerShortName\": \"GitHub_M\"}", "dataType": "CVE_RECORD", "dataVersion": "5.1" } } }
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…