CVE-2022-23591 (GCVE-0-2022-23591)
Vulnerability from cvelistv5 – Published: 2022-02-04 22:32 – Updated: 2025-04-23 19:08
VLAI
EPSS
VEX
Title
Stack overflow in Tensorflow
Summary
Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-04-23 15:57 UTC
CWE
- CWE-400 - Uncontrolled Resource Consumption
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/4… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| tensorflow | tensorflow |
Affected:
>= 2.7.0, < 2.7.1
Affected: >= 2.6.0, < 2.6.3 Affected: < 2.5.3 |
guessed |
{
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-03T03:43:46.959Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
],
"title": "CVE Program Container"
},
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2022-23591",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-23T15:57:48.274385Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-04-23T19:08:10.411Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
"status": "affected",
"version": "\u003e= 2.6.0, \u003c 2.6.3"
},
{
"status": "affected",
"version": "\u003c 2.5.3"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-400",
"description": "CWE-400: Uncontrolled Resource Consumption",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2022-02-04T22:32:09.000Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
],
"source": {
"advisory": "GHSA-247x-2f9f-5wp7",
"discovery": "UNKNOWN"
},
"title": "Stack overflow in Tensorflow",
"x_legacyV4Record": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2022-23591",
"STATE": "PUBLIC",
"TITLE": "Stack overflow in Tensorflow"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
"version_data": [
{
"version_value": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
"version_value": "\u003e= 2.6.0, \u003c 2.6.3"
},
{
"version_value": "\u003c 2.5.3"
}
]
}
}
]
},
"vendor_name": "tensorflow"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "eng",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-400: Uncontrolled Resource Consumption"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
]
},
"source": {
"advisory": "GHSA-247x-2f9f-5wp7",
"discovery": "UNKNOWN"
}
}
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2022-23591",
"datePublished": "2022-02-04T22:32:09.000Z",
"dateReserved": "2022-01-19T00:00:00.000Z",
"dateUpdated": "2025-04-23T19:08:10.411Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1",
"vulnerability-lookup:meta": {
"epss": {
"cve": "CVE-2022-23591",
"date": "2026-09-28",
"epss": "0.00795",
"percentile": "0.54676"
},
"fkie_nvd": {
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"matchCriteriaId": "688150BF-477C-48FC-9AEF-A79AC57A6DDC",
"versionEndIncluding": "2.5.2",
"vulnerable": true
},
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"matchCriteriaId": "C9E69B60-8C97-47E2-9027-9598B8392E5D",
"versionEndIncluding": "2.6.2",
"versionStartIncluding": "2.6.0",
"vulnerable": true
},
{
"criteria": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
"matchCriteriaId": "2EDFAAB8-799C-4259-9102-944D4760DA2C",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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 Autom\u00e1tico de C\u00f3digo Abierto. El formato \"GraphDef\" en TensorFlow no permite funciones auto recursivas. El tiempo de ejecuci\u00f3n asume que este invariante es satisfecho. Sin embargo, un \"GraphDef\" que contiene un fragmento como el siguiente puede ser consumido cuando es cargado un \"SavedModel\". Esto resultar\u00eda en un desbordamiento de pila durante la ejecuci\u00f3n, ya que resolver cada \"NodeDef\" significa resolver la propia funci\u00f3n y sus nodos. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.8.0. Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.7.1, TensorFlow versi\u00f3n 2.6.3, y TensorFlow versi\u00f3n 2.5.3, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan est\u00e1n en el rango admitido"
}
],
"id": "CVE-2022-23591",
"lastModified": "2024-11-21T06:48:52.990",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2022-02-04T23:15:15.253",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-674"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"nvd": {
"cve": {
"affected": [
{
"affectedData": [
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
"status": "affected",
"version": "\u003e= 2.6.0, \u003c 2.6.3"
},
{
"status": "affected",
"version": "\u003c 2.5.3"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"matchCriteriaId": "688150BF-477C-48FC-9AEF-A79AC57A6DDC",
"versionEndIncluding": "2.5.2",
"vulnerable": true
},
{
"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
"matchCriteriaId": "C9E69B60-8C97-47E2-9027-9598B8392E5D",
"versionEndIncluding": "2.6.2",
"versionStartIncluding": "2.6.0",
"vulnerable": true
},
{
"criteria": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
"matchCriteriaId": "2EDFAAB8-799C-4259-9102-944D4760DA2C",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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 Autom\u00e1tico de C\u00f3digo Abierto. El formato \"GraphDef\" en TensorFlow no permite funciones auto recursivas. El tiempo de ejecuci\u00f3n asume que este invariante es satisfecho. Sin embargo, un \"GraphDef\" que contiene un fragmento como el siguiente puede ser consumido cuando es cargado un \"SavedModel\". Esto resultar\u00eda en un desbordamiento de pila durante la ejecuci\u00f3n, ya que resolver cada \"NodeDef\" significa resolver la propia funci\u00f3n y sus nodos. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.8.0. Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.7.1, TensorFlow versi\u00f3n 2.6.3, y TensorFlow versi\u00f3n 2.5.3, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan est\u00e1n en el rango admitido"
}
],
"id": "CVE-2022-23591",
"lastModified": "2026-06-17T04:30:25.837",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-23591",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-23T15:57:48.274385Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-02-04T23:15:15.253",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-674"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"current_release_date": "2026-01-09T08:44:09+00:00",
"cve": "CVE-2022-23591",
"id": "CVE-2022-23591",
"initial_release_date": "2022-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "Stack overflow in Tensorflow",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2022/cve-2022-23591.json",
"version": "3"
},
"suse_vex": {
"aggregate_severity": "critical",
"current_release_date": "2025-03-15T07:43:35Z",
"cve": "CVE-2022-23591",
"id": "CVE-2022-23591",
"initial_release_date": "2023-02-15T03:28:06Z",
"product_status:recommended": "2",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2022-23591",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2022-23591.json",
"version": "6"
},
"vulnrichment": {
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-03T03:43:46.959Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
],
"title": "CVE Program Container"
},
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2022-23591",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-23T15:57:48.274385Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2025-04-23T15:57:49.916Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
"status": "affected",
"version": "\u003e= 2.6.0, \u003c 2.6.3"
},
{
"status": "affected",
"version": "\u003c 2.5.3"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-400",
"description": "CWE-400: Uncontrolled Resource Consumption",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2022-02-04T22:32:09.000Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
],
"source": {
"advisory": "GHSA-247x-2f9f-5wp7",
"discovery": "UNKNOWN"
},
"title": "Stack overflow in Tensorflow",
"x_legacyV4Record": {
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2022-23591",
"STATE": "PUBLIC",
"TITLE": "Stack overflow in Tensorflow"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
"version_data": [
{
"version_value": "\u003e= 2.7.0, \u003c 2.7.1"
},
{
"version_value": "\u003e= 2.6.0, \u003c 2.6.3"
},
{
"version_value": "\u003c 2.5.3"
}
]
}
}
]
},
"vendor_name": "tensorflow"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "eng",
"value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-400: Uncontrolled Resource Consumption"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
},
{
"name": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
}
]
},
"source": {
"advisory": "GHSA-247x-2f9f-5wp7",
"discovery": "UNKNOWN"
}
}
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2022-23591",
"datePublished": "2022-02-04T22:32:09.000Z",
"dateReserved": "2022-01-19T00:00:00.000Z",
"dateUpdated": "2025-04-23T19:08:10.411Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
Loading…
Loading…
Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Loading…
Loading…
The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
Loading…
Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
Loading…