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Auto-merge PR#4923

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Auto-merge PR#4923
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CVE Team 2020-09-25 14:55:30 -04:00 committed by GitHub
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2020/15xxx/CVE-2020-15212.json
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{
"data_type": "CVE",
"data_format": "MITRE",
"data_version": "4.0",
"CVE_data_meta": {
"ASSIGNER": "security-advisories@github.com",
"ID": "CVE-2020-15212",
"ASSIGNER": "cve@mitre.org",
"STATE": "RESERVED"
"STATE": "PUBLIC",
"TITLE": "Out of bounds access in tensorflow-lite"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "tensorflow",
"version": {
"version_data": [
{
"version_value": ">= 2.2.0, < 2.2.1"
},
{
"version_value": ">= 2.3.0, < 2.3.1"
}
]
}
}
]
},
"vendor_name": "tensorflow"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "eng",
"value": "** RESERVED ** This candidate has been reserved by an organization or individual that will use it when announcing a new security problem. When the candidate has been publicized, the details for this candidate will be provided."
"value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor.\n\nUsers having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer.\n\nThis might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits.\n\nThe issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1.\n\nA potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model.\n\nA similar validation could be done if the segment ids are generated at runtime between inference steps.\n\nIf the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code."
}
]
},
"impact": {
"cvss": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/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-hx2x-85gr-wrpq",
"refsource": "CONFIRM",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq"
},
{
"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/commit/204945b19e44b57906c9344c0d00120eeeae178a",
"refsource": "MISC",
"url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"
}
]
},
"source": {
"advisory": "GHSA-hx2x-85gr-wrpq",
"discovery": "UNKNOWN"
}
}