gsd-2021-41228
Vulnerability from gsd
Modified
2023-12-13 01:23
Details
TensorFlow is an open source platform for machine learning. In affected versions TensorFlow's `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-41228",
"description": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow\u0027s `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"id": "GSD-2021-41228",
"references": [
"https://www.suse.com/security/cve/CVE-2021-41228.html",
"https://security.archlinux.org/CVE-2021-41228"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
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],
"details": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow\u0027s `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
"id": "GSD-2021-41228",
"modified": "2023-12-13T01:23:27.417831Z",
"schema_version": "1.4.0"
}
},
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"ID": "CVE-2021-41228",
"STATE": "PUBLIC",
"TITLE": "Code injection in `saved_model_cli`"
},
"affects": {
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"value": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow\u0027s `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range."
}
]
},
"impact": {
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"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "HIGH",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:H/UI:N/S:C/C:H/I:H/A:H",
"version": "3.1"
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"lang": "eng",
"value": "CWE-78: Improper Neutralization of Special Elements used in an OS Command (\u0027OS Command Injection\u0027)"
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}
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"package_slug": "pypi/tensorflow-cpu",
"pubdate": "2021-11-10",
"solution": "Upgrade to versions 2.5.2, 2.6.1 or above.",
"title": "Improper Control of Generation of Code ",
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"description": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow\u0027s `saved_model_cli` tool is vulnerable to a code injection as it calls `eval` on user supplied strings. This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
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"package_slug": "pypi/tensorflow-gpu",
"pubdate": "2021-11-10",
"solution": "Upgrade to versions 2.5.2, 2.6.1 or above.",
"title": "Improper Control of Generation of Code ",
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"affected_versions": "All versions starting from 2.4.0 before 2.4.4, all versions starting from 2.5.0 before 2.5.2, all versions starting from 2.6.0 before 2.6.1, version 2.7.0",
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"description": "TensorFlow is an open source platform for machine learning.This can be used by attackers to run arbitrary code on the plaform where the CLI tool runs. However, given that the tool is always run manually, the impact of this is not severe. We have patched this by adding a `safe` flag which defaults to `True` and an explicit warning for users.",
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"package_slug": "pypi/tensorflow",
"pubdate": "2021-11-05",
"solution": "Upgrade to versions 2.4.4, 2.5.2, 2.6.1, 2.7.1 or above.",
"title": "Improper Control of Generation of Code (\u0027Code Injection\u0027)",
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"impact": {
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"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.6,
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"integrityImpact": "PARTIAL",
"vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
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"impactScore": 5.9
}
},
"lastModifiedDate": "2022-10-20T21:25Z",
"publishedDate": "2021-11-05T23:15Z"
}
}
}
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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.