gsd-2022-23561
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.
Aliases
Aliases
{ "GSD": { "alias": "CVE-2022-23561", "description": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.", "id": "GSD-2022-23561", "references": [ "https://www.suse.com/security/cve/CVE-2022-23561.html" ] }, "gsd": { "metadata": { "exploitCode": "unknown", "remediation": "unknown", "reportConfidence": "confirmed", "type": "vulnerability" }, "osvSchema": { "aliases": [ "CVE-2022-23561" ], "details": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.", "id": "GSD-2022-23561", "modified": "2023-12-13T01:19:35.047687Z", "schema_version": "1.4.0" } }, "namespaces": { "cve.org": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2022-23561", "STATE": "PUBLIC", "TITLE": "Out of bounds write in TFLite" }, "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. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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": 8.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.1" } }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "eng", "value": "CWE-787: Out-of-bounds Write" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq" }, { "name": "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6" } ] }, "source": { "advisory": "GHSA-9c78-vcq7-7vxq", "discovery": "UNKNOWN" } }, "gitlab.com": { "advisories": [ { "affected_range": "\u003c2.5.3||\u003e=2.6.0,\u003c2.6.3||==2.7.0", "affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0", "cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-787", "CWE-937" ], "date": "2022-02-11", "description": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.", "fixed_versions": [ "2.5.3", "2.6.3", "2.7.1" ], "identifier": "CVE-2022-23561", "identifiers": [ "GHSA-9c78-vcq7-7vxq", "CVE-2022-23561" ], "not_impacted": "All versions starting from 2.5.3 before 2.6.0, all versions starting from 2.6.3 before 2.7.0, all versions after 2.7.0", "package_slug": "pypi/tensorflow-cpu", "pubdate": "2022-02-09", "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.", "title": "Out-of-bounds Write", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq", "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6", "https://nvd.nist.gov/vuln/detail/CVE-2022-23561", "https://github.com/advisories/GHSA-9c78-vcq7-7vxq" ], "uuid": "2f940d96-a08d-4b5b-9d84-c9678eac4049" }, { "affected_range": "\u003c2.5.3||\u003e=2.6.0,\u003c2.6.3||==2.7.0", "affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0", "cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-787", "CWE-937" ], "date": "2022-02-11", "description": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.", "fixed_versions": [ "2.5.3", "2.6.3", "2.7.1" ], "identifier": "CVE-2022-23561", "identifiers": [ "GHSA-9c78-vcq7-7vxq", "CVE-2022-23561" ], "not_impacted": "All versions starting from 2.5.3 before 2.6.0, all versions starting from 2.6.3 before 2.7.0, all versions after 2.7.0", "package_slug": "pypi/tensorflow-gpu", "pubdate": "2022-02-09", "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.", "title": "Out-of-bounds Write", "urls": [ "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq", "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6", "https://nvd.nist.gov/vuln/detail/CVE-2022-23561", "https://github.com/advisories/GHSA-9c78-vcq7-7vxq" ], "uuid": "103553b2-13cf-40d2-8acc-5bf58a12c454" }, { "affected_range": "\u003c=2.5.2||\u003e=2.6.0,\u003c=2.6.2||==2.7.0", "affected_versions": "All versions up to 2.5.2, all versions starting from 2.6.0 up to 2.6.2, version 2.7.0", "cvss_v2": "AV:N/AC:L/Au:S/C:P/I:P/A:P", "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "cwe_ids": [ "CWE-1035", "CWE-787", "CWE-937" ], "date": "2022-02-09", "description": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow We will also cherrypick this commit on TensorFlow, TensorFlow, and TensorFlow, as these are also affected and still in supported range.", "fixed_versions": [ "2.5.3", "2.6.3", "2.7.1" ], "identifier": "CVE-2022-23561", "identifiers": [ "CVE-2022-23561", "GHSA-9c78-vcq7-7vxq" ], "not_impacted": "All versions after 2.5.2 before 2.6.0, all versions after 2.6.2 before 2.7.0, all versions after 2.7.0", "package_slug": "pypi/tensorflow", "pubdate": "2022-02-04", "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.", "title": "Out-of-bounds Write", "urls": [ "https://nvd.nist.gov/vuln/detail/CVE-2022-23561", "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq", "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6" ], "uuid": "87908392-c92f-4b7d-8da2-eced5b57df12" } ] }, "nvd.nist.gov": { "configurations": { "CVE_data_version": "4.0", "nodes": [ { "children": [], "cpe_match": [ { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndIncluding": "2.5.2", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "cpe_name": [], "versionEndIncluding": "2.6.2", "versionStartIncluding": "2.6.0", "vulnerable": true }, { "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*", "cpe_name": [], "vulnerable": true } ], "operator": "OR" } ] }, "cve": { "CVE_data_meta": { "ASSIGNER": "security-advisories@github.com", "ID": "CVE-2022-23561" }, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": { "description_data": [ { "lang": "en", "value": "Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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." } ] }, "problemtype": { "problemtype_data": [ { "description": [ { "lang": "en", "value": "CWE-787" } ] } ] }, "references": { "reference_data": [ { "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq", "refsource": "CONFIRM", "tags": [ "Patch", "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq" }, { "name": "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6", "refsource": "MISC", "tags": [ "Patch", "Third Party Advisory" ], "url": "https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6" } ] } }, "impact": { "baseMetricV2": { "acInsufInfo": false, "cvssV2": { "accessComplexity": "LOW", "accessVector": "NETWORK", "authentication": "SINGLE", "availabilityImpact": "PARTIAL", "baseScore": 6.5, "confidentialityImpact": "PARTIAL", "integrityImpact": "PARTIAL", "vectorString": "AV:N/AC:L/Au:S/C:P/I:P/A:P", "version": "2.0" }, "exploitabilityScore": 8.0, "impactScore": 6.4, "obtainAllPrivilege": false, "obtainOtherPrivilege": false, "obtainUserPrivilege": false, "severity": "MEDIUM", "userInteractionRequired": false }, "baseMetricV3": { "cvssV3": { "attackComplexity": "LOW", "attackVector": "NETWORK", "availabilityImpact": "HIGH", "baseScore": 8.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.1" }, "exploitabilityScore": 2.8, "impactScore": 5.9 } }, "lastModifiedDate": "2022-02-09T18:13Z", "publishedDate": "2022-02-04T23:15Z" } } }
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Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
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- 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.