CVE-2020-15206
Vulnerability from cvelistv5
Published
2020-09-25 18:45
Modified
2024-08-04 13:08
Severity ?
EPSS score ?
Summary
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
References
Impacted products
Vendor | Product | Version | |
---|---|---|---|
▼ | tensorflow | tensorflow |
Version: < 1.15.4 Version: >= 2.0.0, < 2.0.3 Version: >= 2.1.0, < 2.1.2 Version: >= 2.2.0, < 2.2.1 Version: >= 2.3.0, < 2.3.1 |
|
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This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1." } ], "metrics": [ { "cvssV3_1": { "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 9, "baseSeverity": "CRITICAL", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "NONE", "scope": "CHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H", "version": "3.1" } } ], "problemTypes": [ { "descriptions": [ { "cweId": "CWE-20", "description": "{\"CWE-20\":\"Improper Input Validation\"}", "lang": "en", "type": "CWE" } ] } ], "providerMetadata": { "dateUpdated": "2020-10-29T15:06:15", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M" }, "references": [ { "tags": [ "x_refsource_MISC" ], "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1" }, { "tags": [ "x_refsource_CONFIRM" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g" }, { "tags": [ "x_refsource_MISC" ], "url": "https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6" }, { "name": "openSUSE-SU-2020:1766", "tags": [ "vendor-advisory", "x_refsource_SUSE" ], "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html" } ], "source": { "advisory": "GHSA-w5gh-2wr2-pm6g", "discovery": "UNKNOWN" }, "title": "Denial of Service in Tensorflow", "x_legacyV4Record": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2020-15206", "STATE": "PUBLIC", "TITLE": "Denial of Service in Tensorflow" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003c 1.15.4" }, { "version_value": "\u003e= 2.0.0, \u003c 2.0.3" }, { "version_value": "\u003e= 2.1.0, \u003c 2.1.2" }, { "version_value": "\u003e= 2.2.0, \u003c 2.2.1" }, { "version_value": "\u003e= 2.3.0, \u003c 2.3.1" } ] } } ] }, "vendor_name": "tensorflow" } ] } }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "eng", "value": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow\u0027s `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1." } ] }, "impact": { "cvss": { "attackComplexity": "HIGH", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 9, "baseSeverity": "CRITICAL", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "NONE", "scope": "CHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/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/releases/tag/v2.3.1", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1" }, { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g" }, { "name": "https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6" }, { "name": "openSUSE-SU-2020:1766", "refsource": "SUSE", "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html" } ] }, "source": { "advisory": "GHSA-w5gh-2wr2-pm6g", "discovery": "UNKNOWN" } } } }, "cveMetadata": { "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2020-15206", "datePublished": "2020-09-25T18:45:51", "dateReserved": "2020-06-25T00:00:00", "dateUpdated": "2024-08-04T13:08:22.955Z", "state": "PUBLISHED" }, "dataType": "CVE_RECORD", "dataVersion": "5.1", "meta": { "nvd": "{\"cve\":{\"id\":\"CVE-2020-15206\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2020-09-25T19:15:15.917\",\"lastModified\":\"2024-11-21T05:05:05.090\",\"vulnStatus\":\"Modified\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow\u0027s `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\"},{\"lang\":\"es\",\"value\":\"En Tensorflow versiones anteriores a 1.15.4, 2.0.3, 2.1.2, 2.2.1 y 2.3.1, cambiar el b\u00fafer del protocolo \\\"SavedModel\\\" de TensorFlow y alterar el nombre de las claves requeridas resulta en fallos de segmentaci\u00f3n y una corrupci\u00f3n de los datos mientras se carga el modelo.\u0026#xa0;Esto puede causar una denegaci\u00f3n de servicio en productos que usan \\\"tensorflow-serve\\\" u otras cuotas de inferencia como un servicio.\u0026#xa0;Los arreglos se agregaron en las commits f760f88b4267d981e13f4b302c437ae800445968 y fcfef195637c6e365577829c4d67681695956e7d (ambas en TensorFlow versiones 2.2.0 y 2.3.0 pero a\u00fan no se han actualizado a versiones anteriores).\u0026#xa0;Sin embargo, esto no fue suficiente, ya que #41097 reporta un modo de fallo diferente.\u0026#xa0;El problema es parcheado 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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.