CVE-2021-29554
Vulnerability from cvelistv5
Published
2021-05-14 19:10
Modified
2024-08-03 22:11
Severity ?
EPSS score ?
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.
References
▼ | URL | Tags | |
---|---|---|---|
security-advisories@github.com | https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f | Patch, Third Party Advisory | |
security-advisories@github.com | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5 | Exploit, Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f | Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5 | Exploit, Patch, Third Party Advisory |
Impacted products
Vendor | Product | Version | |
---|---|---|---|
▼ | tensorflow | tensorflow |
Version: < 2.3.3 Version: >= 2.4.0, < 2.4.2 |
|
{ "containers": { "adp": [ { "providerMetadata": { "dateUpdated": "2024-08-03T22:11:06.254Z", "orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE" }, "references": [ { "tags": [ "x_refsource_CONFIRM", "x_transferred" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5" }, { "tags": [ "x_refsource_MISC", "x_transferred" ], "url": "https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f" } ], "title": "CVE Program Container" } ], "cna": { "affected": [ { "product": "tensorflow", "vendor": "tensorflow", "versions": [ { "status": "affected", "version": "\u003c 2.3.3" }, { "status": "affected", "version": "\u003e= 2.4.0, \u003c 2.4.2" } ] } ], "descriptions": [ { "lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected." } ], "metrics": [ { "cvssV3_1": { "attackComplexity": "HIGH", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 2.5, "baseSeverity": "LOW", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "version": "3.1" } } ], "problemTypes": [ { "descriptions": [ { "cweId": "CWE-369", "description": "CWE-369: Divide By Zero", "lang": "en", "type": "CWE" } ] } ], "providerMetadata": { "dateUpdated": "2021-05-14T19:10:15", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M" }, "references": [ { "tags": [ "x_refsource_CONFIRM" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5" }, { "tags": [ "x_refsource_MISC" ], "url": "https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f" } ], "source": { "advisory": "GHSA-qg48-85hg-mqc5", "discovery": "UNKNOWN" }, "title": "Division by 0 in `DenseCountSparseOutput`", "x_legacyV4Record": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-29554", "STATE": "PUBLIC", "TITLE": "Division by 0 in `DenseCountSparseOutput`" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003c 2.3.3" }, { "version_value": "\u003e= 2.4.0, \u003c 2.4.2" } ] } } ] }, "vendor_name": "tensorflow" } ] } }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "eng", "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected." } ] }, "impact": { "cvss": { "attackComplexity": "HIGH", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 2.5, "baseSeverity": "LOW", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "version": "3.1" } }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "eng", "value": "CWE-369: Divide By Zero" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5" }, { "name": "https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f" } ] }, "source": { "advisory": "GHSA-qg48-85hg-mqc5", "discovery": "UNKNOWN" } } } }, "cveMetadata": { "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-29554", "datePublished": "2021-05-14T19:10:15", "dateReserved": "2021-03-30T00:00:00", "dateUpdated": "2024-08-03T22:11:06.254Z", "state": "PUBLISHED" }, "dataType": "CVE_RECORD", "dataVersion": "5.1", "meta": { "nvd": "{\"cve\":{\"id\":\"CVE-2021-29554\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2021-05-14T19:15:07.800\",\"lastModified\":\"2024-11-21T06:01:22.210\",\"vulnStatus\":\"Modified\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.\"},{\"lang\":\"es\",\"value\":\"TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico.\u0026#xa0;Un atacante puede causar una denegaci\u00f3n de servicio por medio de un error de tiempo de ejecuci\u00f3n de FPE en \\\"tf.raw_ops.DenseCountSparseOutput\\\".\u0026#xa0;Esto es debido a que la implementaci\u00f3n (https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) calcula un valor divisor a partir de los datos del usuario pero no comprueba que el resultado es 0 antes de hacer la divisi\u00f3n.\u0026#xa0;Dado que \\\"data\\\" viene dado por el argumento \\\"values\\\", \\\"num_batch_elements\\\" es 0. La correcci\u00f3n ser\u00e1 inclu\u00edda en TensorFlow versi\u00f3n 2.5.0.\u0026#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.4.2 y TensorFlow versi\u00f3n 2.3.3, ya que estos tambi\u00e9n est\u00e1n afectados\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L\",\"baseScore\":2.5,\"baseSeverity\":\"LOW\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"HIGH\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"LOW\"},\"exploitabilityScore\":1.0,\"impactScore\":1.4},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H\",\"baseScore\":5.5,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":1.8,\"impactScore\":3.6}],\"cvssMetricV2\":[{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"2.0\",\"vectorString\":\"AV:L/AC:L/Au:N/C:N/I:N/A:P\",\"baseScore\":2.1,\"accessVector\":\"LOCAL\",\"accessComplexity\":\"LOW\",\"authentication\":\"NONE\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"PARTIAL\"},\"baseSeverity\":\"LOW\",\"exploitabilityScore\":3.9,\"impactScore\":2.9,\"acInsufInfo\":false,\"obtainAllPrivilege\":false,\"obtainUserPrivilege\":false,\"obtainOtherPrivilege\":false,\"userInteractionRequired\":false}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-369\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionEndExcluding\":\"2.1.4\",\"matchCriteriaId\":\"323ABCCE-24EB-47CC-87F6-48C101477587\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.2.0\",\"versionEndExcluding\":\"2.2.3\",\"matchCriteriaId\":\"64ABA90C-0649-4BB0-89C9-83C14BBDCC0F\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.3.0\",\"versionEndExcluding\":\"2.3.3\",\"matchCriteriaId\":\"0F83E0CF-CBF6-4C24-8683-3E7A5DC95BA9\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.4.0\",\"versionEndExcluding\":\"2.4.2\",\"matchCriteriaId\":\"8259531B-A8AC-4F8B-B60F-B69DE4767C03\"}]}]}],\"references\":[{\"url\":\"https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Exploit\",\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Exploit\",\"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.