CVE-2022-35972
Vulnerability from cvelistv5
Published
2022-09-16 21:00
Modified
2024-08-03 09:51
Severity ?
EPSS score ?
Summary
TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
References
▼ | URL | Tags | |
---|---|---|---|
security-advisories@github.com | https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0 | Patch, Third Party Advisory | |
security-advisories@github.com | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9 | Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0 | Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9 | Patch, Third Party Advisory |
Impacted products
Vendor | Product | Version | |
---|---|---|---|
▼ | tensorflow | tensorflow |
Version: < 2.7.2 Version: >= 2.8.0, < 2.8.1 Version: >= 2.9.0, < 2.9.1 |
|
{ "containers": { "adp": [ { "providerMetadata": { "dateUpdated": "2024-08-03T09:51:59.305Z", "orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE" }, "references": [ { "tags": [ "x_refsource_MISC", "x_transferred" ], "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0" }, { "tags": [ "x_refsource_CONFIRM", "x_transferred" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9" } ], "title": "CVE Program Container" } ], "cna": { "affected": [ { "product": "tensorflow", "vendor": "tensorflow", "versions": [ { "status": "affected", "version": "\u003c 2.7.2" }, { "status": "affected", "version": "\u003e= 2.8.0, \u003c 2.8.1" }, { "status": "affected", "version": "\u003e= 2.9.0, \u003c 2.9.1" } ] } ], "descriptions": [ { "lang": "en", "value": "TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue." } ], "metrics": [ { "cvssV3_1": { "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 5.9, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H", "version": "3.1" } } ], "problemTypes": [ { "descriptions": [ { "cweId": "CWE-20", "description": "CWE-20: Improper Input Validation", "lang": "en", "type": "CWE" } ] } ], "providerMetadata": { "dateUpdated": "2022-09-16T21:00:19", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M" }, "references": [ { "tags": [ "x_refsource_MISC" ], "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0" }, { "tags": [ "x_refsource_CONFIRM" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9" } ], "source": { "advisory": "GHSA-4pc4-m9mj-v2r9", "discovery": "UNKNOWN" }, "title": "Segfault in `QuantizedBiasAdd` in TensorFlow", "x_legacyV4Record": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2022-35972", "STATE": "PUBLIC", "TITLE": "Segfault in `QuantizedBiasAdd` in TensorFlow" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003c 2.7.2" }, { "version_value": "\u003e= 2.8.0, \u003c 2.8.1" }, { "version_value": "\u003e= 2.9.0, \u003c 2.9.1" } ] } } ] }, "vendor_name": "tensorflow" } ] } }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "eng", "value": "TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue." } ] }, "impact": { "cvss": { "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 5.9, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "NONE", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H", "version": "3.1" } }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "eng", "value": "CWE-20: Improper Input Validation" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0" }, { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9" } ] }, "source": { "advisory": "GHSA-4pc4-m9mj-v2r9", "discovery": "UNKNOWN" } } } }, "cveMetadata": { "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2022-35972", "datePublished": "2022-09-16T21:00:19", "dateReserved": "2022-07-15T00:00:00", "dateUpdated": "2024-08-03T09:51:59.305Z", "state": "PUBLISHED" }, "dataType": "CVE_RECORD", "dataVersion": "5.1", "meta": { "nvd": "{\"cve\":{\"id\":\"CVE-2022-35972\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2022-09-16T21:15:09.427\",\"lastModified\":\"2024-11-21T07:12:05.080\",\"vulnStatus\":\"Modified\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.\"},{\"lang\":\"es\",\"value\":\"TensorFlow es una plataforma de c\u00f3digo abierto para el aprendizaje autom\u00e1tico. Si a \\\"QuantizedBiasAdd\\\" le son dados los tensores \\\"min_input\\\", \\\"max_input\\\", \\\"min_bias\\\", \\\"max_bias\\\" de un rango distinto de cero, resulta en un segfault que puede usarse para desencadenar un ataque de denegaci\u00f3n de servicio. Hemos parcheado el problema en el commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0 de GitHub. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.10.0. Tambi\u00e9n seleccionaremos este compromiso en TensorFlow versi\u00f3n 2.9.1, TensorFlow versi\u00f3n 2.8.1, y TensorFlow versi\u00f3n 2.7.2, ya que estos tambi\u00e9n est\u00e1n afectados y todav\u00eda est\u00e1n en el rango admitido. No se presentan mitigaciones conocidas para este problema\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H\",\"baseScore\":5.9,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"HIGH\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":2.2,\"impactScore\":3.6},{\"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:N/I:N/A:H\",\"baseScore\":7.5,\"baseSeverity\":\"HIGH\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":3.9,\"impactScore\":3.6}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-20\"}]},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"NVD-CWE-noinfo\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.7.0\",\"versionEndExcluding\":\"2.7.2\",\"matchCriteriaId\":\"C4DFBF2D-5283-42F6-8800-D653BFA5CE82\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.8.0\",\"versionEndExcluding\":\"2.8.1\",\"matchCriteriaId\":\"0F9D273D-02DC-441E-AA91-EAC8DEAA4B44\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.9.0\",\"versionEndExcluding\":\"2.9.1\",\"matchCriteriaId\":\"FE4F8A81-6CC2-4F7F-9602-C170FDD926E7\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:*\",\"matchCriteriaId\":\"1DBFBCE2-0A01-4575-BE45-6775ABFB8B28\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:*\",\"matchCriteriaId\":\"89806CF9-E423-4CA6-A01A-8175C260CB24\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:2.10:rc2:*:*:*:*:*:*\",\"matchCriteriaId\":\"F2B80690-A257-4E16-BD27-9AE045BC56ED\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:2.10:rc3:*:*:*:*:*:*\",\"matchCriteriaId\":\"F335F9A4-5AB8-4E53-BC18-E01F7C653E5E\"}]}]}],\"references\":[{\"url\":\"https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]}]}}" } }
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.