cve-2021-29614
Vulnerability from cvelistv5
Published
2021-05-14 19:20
Modified
2024-08-03 22:11
Severity ?
EPSS score ?
Summary
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
References
▼ | URL | Tags | |
---|---|---|---|
security-advisories@github.com | https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d | Patch, Third Party Advisory | |
security-advisories@github.com | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h | Exploit, Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d | Patch, Third Party Advisory | |
af854a3a-2127-422b-91ae-364da2661108 | https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h | Exploit, Patch, Third Party Advisory |
Impacted products
Vendor | Product | Version | |
---|---|---|---|
▼ | tensorflow | tensorflow |
Version: < 2.1.4 Version: >= 2.2.0, < 2.2.3 Version: >= 2.3.0, < 2.3.3 Version: >= 2.4.0, < 2.4.2 |
|
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The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range." } ], "metrics": [ { "cvssV3_1": { "attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.1, "baseSeverity": "HIGH", "confidentialityImpact": "NONE", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H", "version": "3.1" } } ], "problemTypes": [ { "descriptions": [ { "cweId": "CWE-665", "description": "CWE-665: Improper Initialization", "lang": "en", "type": "CWE" } ] } ], "providerMetadata": { "dateUpdated": "2021-05-14T19:20:28", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M" }, "references": [ { "tags": [ "x_refsource_CONFIRM" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h" }, { "tags": [ "x_refsource_MISC" ], "url": "https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d" } ], "source": { "advisory": "GHSA-8pmx-p244-g88h", "discovery": "UNKNOWN" }, "title": "Interpreter crash from `tf.io.decode_raw`", "x_legacyV4Record": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-29614", "STATE": "PUBLIC", "TITLE": "Interpreter crash from `tf.io.decode_raw`" }, "affects": { "vendor": { "vendor_data": [ { "product": { "product_data": [ { "product_name": "tensorflow", "version": { "version_data": [ { "version_value": "\u003c 2.1.4" }, { "version_value": "\u003e= 2.2.0, \u003c 2.2.3" }, { "version_value": "\u003e= 2.3.0, \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. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. 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The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.\"},{\"lang\":\"es\",\"value\":\"TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico.\u0026#xa0;La implementaci\u00f3n de \\\"tf.io.decode_raw\\\" produce resultados incorrectos y bloquea el int\u00e9rprete de Python al combinar \\\"fixed_length\\\" y tipos de datos m\u00e1s amplios.\u0026#xa0;La implementaci\u00f3n de la versi\u00f3n acolchada (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) presenta errores debido a una confusi\u00f3n acerca de las reglas aritm\u00e9ticas de punteros.\u0026#xa0;Primero, el c\u00f3digo calcula (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) el ancho de cada elemento de salida dividiendo el valor de la longitud fija del tipo argumento.\u0026#xa0;El argumento \\\"fixed_length\\\" tambi\u00e9n es usado para determinar el tama\u00f1o necesario para el tensor de salida (https: //github.\u0026#xa0;com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79).\u0026#xa0;A continuaci\u00f3n, se vuelve a codificar el c\u00f3digo (https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94).\u0026#xa0;El c\u00f3digo err\u00f3neo es la \u00faltima l\u00ednea de arriba: est\u00e1 moviendo el puntero \\\"out_data\\\" en bytes de \\\"fixed_length * sizeof(T)\\\" mientras que s\u00f3lo copi\u00f3 como m\u00e1ximo los bytes de \\\"fixed_length\\\" de la entrada.\u0026#xa0;Esto resulta en que partes de la entrada no se descodifiquen en una salida.\u0026#xa0;Adem\u00e1s, debido a que el avance del puntero es mucho m\u00e1s amplio de lo deseado, esto conlleva r\u00e1pidamente a escribir fuera de l\u00edmites de los datos de respaldo.\u0026#xa0;Esta escritura OOB provoca un bloqueo del int\u00e9rprete en el reproductor mencionado aqu\u00ed, pero tambi\u00e9n puede ser montar ataques m\u00e1s severos,\u0026#xa0;dado que este gadget permite escribir en ubicaciones colocadas peri\u00f3dicamente en una memoria.\u0026#xa0;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, TensorFlow versi\u00f3n 2.3.3, TensorFlow versi\u00f3n 2.2.3 y TensorFlow versi\u00f3n 2.1.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan est\u00e1n en el rango compatible\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H\",\"baseScore\":7.1,\"baseSeverity\":\"HIGH\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"HIGH\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":1.8,\"impactScore\":5.2},{\"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:H/I:H/A:H\",\"baseScore\":7.8,\"baseSeverity\":\"HIGH\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"HIGH\",\"integrityImpact\":\"HIGH\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":1.8,\"impactScore\":5.9}],\"cvssMetricV2\":[{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"2.0\",\"vectorString\":\"AV:L/AC:L/Au:N/C:P/I:P/A:P\",\"baseScore\":4.6,\"accessVector\":\"LOCAL\",\"accessComplexity\":\"LOW\",\"authentication\":\"NONE\",\"confidentialityImpact\":\"PARTIAL\",\"integrityImpact\":\"PARTIAL\",\"availabilityImpact\":\"PARTIAL\"},\"baseSeverity\":\"MEDIUM\",\"exploitabilityScore\":3.9,\"impactScore\":6.4,\"acInsufInfo\":false,\"obtainAllPrivilege\":false,\"obtainUserPrivilege\":false,\"obtainOtherPrivilege\":false,\"userInteractionRequired\":false}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-665\"}]},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-787\"}]}],\"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/698e01511f62a3c185754db78ebce0eee1f0184d\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Exploit\",\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Exploit\",\"Patch\",\"Third Party Advisory\"]}]}}" } }
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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.