210 lines
10 KiB
JSON
210 lines
10 KiB
JSON
{
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"containers": {
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"cna": {
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"affected": [
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{
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"product": "tensorflow",
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"vendor": "tensorflow",
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"versions": [
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{
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"status": "affected",
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"version": "< 2.3.3"
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},
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{
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"status": "affected",
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"version": ">= 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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"descriptions": [
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{
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"lang": "en",
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"value": "TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3."
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}
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],
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"metrics": [
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{
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"cvssV3_1": {
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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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],
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"problemTypes": [
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{
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"descriptions": [
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{
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"cweId": "CWE-131",
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"description": "CWE-131: Incorrect Calculation of Buffer Size",
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"lang": "en",
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"type": "CWE"
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}
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]
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}
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],
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"providerMetadata": {
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"dateUpdated": "2021-05-14T19:35:49.000Z",
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"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
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"shortName": "GitHub_M"
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},
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"references": [
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{
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"tags": [
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"x_refsource_CONFIRM"
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],
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"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"
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},
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{
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"tags": [
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"x_refsource_MISC"
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],
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"url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"
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}
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],
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"source": {
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"advisory": "GHSA-hr84-fqvp-48mm",
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"discovery": "UNKNOWN"
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},
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"title": "Segfault in SparseCountSparseOutput",
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"x_legacyV4Record": {
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"CVE_data_meta": {
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"ASSIGNER": "security-advisories@github.com",
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"ID": "CVE-2021-29521",
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"STATE": "PUBLIC",
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"TITLE": "Segfault in SparseCountSparseOutput"
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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": "< 2.3.3"
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{
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"version_value": ">= 2.4.0, < 2.4.2"
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"vendor_name": "tensorflow"
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"data_format": "MITRE",
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"lang": "eng",
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"value": "TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3."
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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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"description": [
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{
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"lang": "eng",
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"value": "CWE-131: Incorrect Calculation of Buffer Size"
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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-hr84-fqvp-48mm",
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"refsource": "CONFIRM",
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"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"
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},
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{
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"name": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5",
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"refsource": "MISC",
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"url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"
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}
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]
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"source": {
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"advisory": "GHSA-hr84-fqvp-48mm",
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"discovery": "UNKNOWN"
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}
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"adp": [
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{
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"shortName": "CVE",
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"dateUpdated": "2024-08-03T22:11:05.725Z"
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},
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"title": "CVE Program Container",
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"references": [
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{
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"tags": [
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"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"
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},
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{
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"tags": [
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"url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"
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"cveId": "CVE-2021-29521",
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