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Add CVE-2021-29584 for GHSA-xvjm-fvxx-q3hv
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{
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"data_type": "CVE",
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"data_format": "MITRE",
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"data_version": "4.0",
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"CVE_data_meta": {
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"ASSIGNER": "security-advisories@github.com",
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"ID": "CVE-2021-29584",
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"ASSIGNER": "cve@mitre.org",
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"STATE": "RESERVED"
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"STATE": "PUBLIC",
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"TITLE": "CHECK-fail due to integer overflow"
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},
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"affects": {
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"vendor": {
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"vendor_data": [
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{
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"product": {
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"product_data": [
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{
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"product_name": "tensorflow",
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"version": {
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"version_data": [
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{
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"version_value": "< 2.1.4"
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},
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{
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"version_value": ">= 2.2.0, < 2.2.3"
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},
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{
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"version_value": ">= 2.3.0, < 2.3.3"
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},
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{
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"version_value": ">= 2.4.0, < 2.4.2"
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}
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]
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}
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}
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]
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},
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"vendor_name": "tensorflow"
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}
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]
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}
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},
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"data_format": "MITRE",
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"data_type": "CVE",
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"data_version": "4.0",
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"description": {
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"description_data": [
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{
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"lang": "eng",
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"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."
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"value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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."
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}
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]
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},
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"impact": {
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"cvss": {
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"attackComplexity": "HIGH",
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"attackVector": "LOCAL",
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"availabilityImpact": "LOW",
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"baseScore": 2.5,
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"baseSeverity": "LOW",
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"confidentialityImpact": "NONE",
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"integrityImpact": "NONE",
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"privilegesRequired": "LOW",
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"scope": "UNCHANGED",
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"userInteraction": "NONE",
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"vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
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"version": "3.1"
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}
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},
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"problemtype": {
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"problemtype_data": [
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{
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"description": [
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{
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"lang": "eng",
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"value": "CWE-190: Integer Overflow or Wraparound"
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}
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]
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}
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]
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},
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"references": {
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"reference_data": [
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{
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"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xvjm-fvxx-q3hv",
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"refsource": "CONFIRM",
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"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xvjm-fvxx-q3hv"
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},
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{
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"name": "https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60",
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"refsource": "MISC",
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"url": "https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60"
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}
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]
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},
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"source": {
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"advisory": "GHSA-xvjm-fvxx-q3hv",
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"discovery": "UNKNOWN"
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}
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}
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