GSD-2020-15208
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2020-15208",
"description": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
"id": "GSD-2020-15208",
"references": [
"https://www.suse.com/security/cve/CVE-2020-15208.html"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2020-15208"
],
"details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
"id": "GSD-2020-15208",
"modified": "2023-12-13T01:21:43.619786Z",
"schema_version": "1.4.0"
}
},
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"STATE": "PUBLIC",
"TITLE": "Data corruption in tensorflow-lite"
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"vendor": {
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"value": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, 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": "NONE",
"baseScore": 7.4,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N",
"version": "3.1"
}
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"value": "{\"CWE-125\":\"Out-of-bounds Read\"}"
}
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},
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"description": [
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"value": "{\"CWE-787\":\"Out-of-bounds Write\"}"
}
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}
]
},
"references": {
"reference_data": [
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"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-mxjj-953w-2c2v",
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},
{
"name": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
},
{
"name": "openSUSE-SU-2020:1766",
"refsource": "SUSE",
"url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
}
]
},
"source": {
"advisory": "GHSA-mxjj-953w-2c2v",
"discovery": "UNKNOWN"
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003c1.15.4||\u003e=2.0.0,\u003c2.0.3||\u003e=2.1.0,\u003c2.1.2||\u003e=2.2.0,\u003c2.2.1||\u003e=2.3.0,\u003c2.3.1",
"affected_versions": "All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1",
"cvss_v2": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-787",
"CWE-937"
],
"date": "2020-10-29",
"description": "In tensorflow-lite, when determining the common dimension size of two tensors, `TFLite` uses a `DCHECK` which is no-op outside debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside bounds since the interpreter will wrongly assume that there is enough data in both tensors.",
"fixed_versions": [
"2.1.2",
"2.2.1",
"2.3.1"
],
"identifier": "CVE-2020-15208",
"identifiers": [
"CVE-2020-15208",
"GHSA-mxjj-953w-2c2v"
],
"not_impacted": "All versions starting from 1.15.4 before 2.0.0, all versions starting from 2.0.3 before 2.1.0, all versions starting from 2.1.2 before 2.2.0, all versions starting from 2.2.1 before 2.3.0, all versions starting from 2.3.1",
"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2020-09-25",
"solution": "Upgrade to versions 2.1.2, 2.2.1, 2.3.1 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2020-15208"
],
"uuid": "241187dc-8fd1-4c40-a1d8-2cd5375e193c"
},
{
"affected_range": "\u003c1.15.4||\u003e=2.0.0,\u003c2.0.3||\u003e=2.1.0,\u003c2.1.2||\u003e=2.2.0,\u003c2.2.1||\u003e=2.3.0,\u003c2.3.1",
"affected_versions": "All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1",
"cvss_v2": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-787",
"CWE-937"
],
"date": "2020-10-29",
"description": "In tensorflow-lite, when determining the common dimension size of two tensors, `TFLite` uses a `DCHECK` which is no-op outside debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside bounds since the interpreter will wrongly assume that there is enough data in both tensors.",
"fixed_versions": [
"1.15.4",
"2.0.3",
"2.1.2",
"2.2.1",
"2.3.1"
],
"identifier": "CVE-2020-15208",
"identifiers": [
"CVE-2020-15208",
"GHSA-mxjj-953w-2c2v"
],
"not_impacted": "All versions starting from 1.15.4 before 2.0.0, all versions starting from 2.0.3 before 2.1.0, all versions starting from 2.1.2 before 2.2.0, all versions starting from 2.2.1 before 2.3.0, all versions starting from 2.3.1",
"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2020-09-25",
"solution": "Upgrade to versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2020-15208"
],
"uuid": "6fa5925e-af67-453c-90d2-1900e21f44ad"
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"affected_range": "\u003c1.15.4||\u003e=2.0.0,\u003c2.0.3||\u003e=2.1.0,\u003c2.1.2||\u003e=2.2.0,\u003c2.2.1||\u003e=2.3.0,\u003c2.3.1",
"affected_versions": "All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1",
"cvss_v2": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-125",
"CWE-787",
"CWE-937"
],
"date": "2021-09-16",
"description": "In tensorflow-lite, when determining the common dimension size of two tensors, `TFLite` uses a `DCHECK` which is no-op outside debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside bounds since the interpreter will wrongly assume that there is enough data in both tensors.",
"fixed_versions": [
"1.15.4",
"2.0.3",
"2.1.2",
"2.2.1",
"2.3.1"
],
"identifier": "CVE-2020-15208",
"identifiers": [
"CVE-2020-15208",
"GHSA-mxjj-953w-2c2v"
],
"not_impacted": "All versions starting from 1.15.4 before 2.0.0, all versions starting from 2.0.3 before 2.1.0, all versions starting from 2.1.2 before 2.2.0, all versions starting from 2.2.1 before 2.3.0, all versions starting from 2.3.1",
"package_slug": "pypi/tensorflow",
"pubdate": "2020-09-25",
"solution": "Upgrade to versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or above.",
"title": "Out-of-bounds Write",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2020-15208"
],
"uuid": "0bfd4be6-29f8-482c-83a3-6bd625d08dd3"
}
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"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9
}
},
"lastModifiedDate": "2021-09-16T15:45Z",
"publishedDate": "2020-09-25T19:15Z"
}
}
}
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Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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