CVE-2022-21731
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank.
Leer descripción completaMostrar menos
However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
CVSS
- Versión: 3.1
- Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Puntuación base: 6.5
Probabilidad de explotación (EPSS)
- Probabilidad de explotación en los próximos 30 días: 0.85%
- Percentil entre todas las CVEs puntuadas: 57
- Fecha de la puntuación: 7/10/2026
EPSS (Exploit Prediction Scoring System, de FIRST) estima la probabilidad de que una vulnerabilidad sea explotada en 30 días. Complementa a CVSS (impacto) y a CISA KEV (explotación confirmada).
Tecnologías afectadas (1)
CWE
- CWE-843
- CWE-843
Referencias
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358
- https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358
- https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353
JSON original (NVD)
Mostrar
{
"id": "CVE-2022-21731",
"cveTags": [],
"metrics": {
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-21731",
"role": "CISA Coordinator",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"version": "2.0.3",
"timestamp": "2025-04-25T15:47:26.571505Z"
}
}
],
"cvssMetricV2": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"version": "2.0",
"baseScore": 4,
"accessVector": "NETWORK",
"vectorString": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
"authentication": "SINGLE",
"integrityImpact": "NONE",
"accessComplexity": "LOW",
"availabilityImpact": "PARTIAL",
"confidentialityImpact": "NONE"
},
"acInsufInfo": false,
"impactScore": 2.9,
"baseSeverity": "MEDIUM",
"obtainAllPrivilege": false,
"exploitabilityScore": 8,
"obtainUserPrivilege": false,
"obtainOtherPrivilege": false,
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"type": "Secondary",
"source": "security-advisories@github.com",
"cvssData": {
"scope": "UNCHANGED",
"version": "3.1",
"baseScore": 6.5,
"attackVector": "NETWORK",
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"integrityImpact": "NONE",
"userInteraction": "NONE",
"attackComplexity": "LOW",
"availabilityImpact": "HIGH",
"privilegesRequired": "LOW",
"confidentialityImpact": "NONE"
},
"impactScore": 3.6,
"exploitabilityScore": 2.8
},
{
"type": "Primary",
"source": "nvd@nist.gov",
"cvssData": {
"scope": "UNCHANGED",
"version": "3.1",
"baseScore": 6.5,
"attackVector": "NETWORK",
"baseSeverity": "MEDIUM",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"integrityImpact": "NONE",
"userInteraction": "NONE",
"attackComplexity": "LOW",
"availabilityImpact": "HIGH",
"privilegesRequired": "LOW",
"confidentialityImpact": "NONE"
},
"impactScore": 3.6,
"exploitabilityScore": 2.8
}
]
},
"affected": [
{
"source": "security-advisories@github.com",
"affectedData": [
{
"vendor": "n/a",
"product": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
]
}
],
"published": "2022-02-03T12:15:07.873",
"references": [
{
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059",
"tags": [
"Exploit",
"Third Party Advisory"
],
"source": "security-advisories@github.com"
},
{
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358",
"tags": [
"Exploit",
"Third Party Advisory"
],
"source": "security-advisories@github.com"
},
{
"url": "https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022",
"tags": [
"Patch",
"Third Party Advisory"
],
"source": "security-advisories@github.com"
},
{
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353",
"tags": [
"Patch",
"Third Party Advisory"
],
"source": "security-advisories@github.com"
},
{
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059",
"tags": [
"Exploit",
"Third Party Advisory"
],
"source": "af854a3a-2127-422b-91ae-364da2661108"
},
{
"url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358",
"tags": [
"Exploit",
"Third Party Advisory"
],
"source": "af854a3a-2127-422b-91ae-364da2661108"
},
{
"url": "https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022",
"tags": [
"Patch",
"Third Party Advisory"
],
"source": "af854a3a-2127-422b-91ae-364da2661108"
},
{
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353",
"tags": [
"Patch",
"Third Party Advisory"
],
"source": "af854a3a-2127-422b-91ae-364da2661108"
}
],
"vulnStatus": "Modified",
"weaknesses": [
{
"type": "Primary",
"source": "nvd@nist.gov",
"description": [
{
"lang": "en",
"value": "CWE-843"
}
]
},
{
"type": "Secondary",
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"description": [
{
"lang": "en",
"value": "CWE-843"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range."
},
{
"lang": "es",
"value": "Tensorflow es un marco de aprendizaje automático de código abierto. La implementación de la inferencia de formas para \"ConcatV2\" puede ser usada para desencadenar un ataque de denegación de servicio por medio de un segfault causado por una confusión de tipos. El argumento \"axis\" es traducido en \"concat_dim\" en la función de ayuda \"ConcatShapeHelper\". A continuación, es calculado un valor para \"min_rank\" basado en \"concat_dim\". Este valor es usado para comprender que el tensor \"values\" presenta al menos el rango requerido. Sin embargo, \"WithRankAtLeast\" recibe el límite inferior como un valor de 64 bits y luego lo compara con el valor entero máximo de 32 bits que podría representarse. Debido a que \"min_rank\" es un valor de 32 bits y el valor de \"axis\", el argumento \"rank\" es un valor negativo, por lo que la comprobación del error es omitida. La corrección será incluida en TensorFlow versión 2.8.0. También seleccionaremos este commit en TensorFlow versión 2.7.1, TensorFlow versión 2.6.3, y TensorFlow versión 2.5.3, ya que estos también están afectados y aún están en el rango admitido"
}
],
"lastModified": "2026-06-17T04:26:52.640",
"configurations": [
{
"nodes": [
{
"negate": false,
"cpeMatch": [
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"vulnerable": true,
"matchCriteriaId": "688150BF-477C-48FC-9AEF-A79AC57A6DDC",
"versionEndIncluding": "2.5.2"
},
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"vulnerable": true,
"matchCriteriaId": "C9E69B60-8C97-47E2-9027-9598B8392E5D",
"versionEndIncluding": "2.6.2",
"versionStartIncluding": "2.6.0"
},
{
"criteria": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
"vulnerable": true,
"matchCriteriaId": "2EDFAAB8-799C-4259-9102-944D4760DA2C"
}
],
"operator": "OR"
}
]
}
],
"sourceIdentifier": "security-advisories@github.com"
}