rainbutterfly/cve_corpus huggingface dataset:
CVE-2022-35972 Segfault in `QuantizedBiasAdd` in TensorFlow
TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:00:19.000Z
CVE-2022-35973 Segfault in `QuantizedMatMul` in TensorFlow
TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:00:14.000Z
CVE-2022-35974 Segfault in `QuantizeDownAndShrinkRange` in TensorFlow
TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:05:12.000Z
CVE-2022-35975 Improper object validation allows for arbitrary code execution in GitOps Tools Extension for VSCode
The GitOps Tools Extension for VSCode can make it easier to manage Flux objects. A specially crafted Flux object may allow for remote code execution in the machine running the extension, in the context of the user that is running VSCode. Users using the VSCode extension to manage clusters that are shared amongst other users are affected by this issue. The only safe mitigation is to update to the latest version of the extension.
Problem types: cwe_id: CWE-78
description: CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Affected products: vendor: weaveworks
product: vscode-gitops-tools
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 9
baseSeverity: CRITICAL
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: CHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H
version: 3.1
Published: 2022-08-18T17:55:08.000Z
CVE-2022-35976 Improper KubeConfig handling allows arbitrary code execution
The GitOps Tools Extension for VSCode relies on kubeconfigs in order to communicate with Kubernetes clusters. A specially crafted kubeconfig leads to arbitrary code execution on behalf of the user running VSCode. Users relying on kubeconfigs that are generated or altered by other processes or users are affected by this issue. Please note that the vulnerability is specific to this extension, and the same kubeconfig would not result in arbitrary code execution when used with kubectl. Using only trust-worthy kubeconfigs is a safe mitigation. However, updating to the latest version of the extension is still highly recommended.
Problem types: cwe_id: CWE-78
description: CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Affected products: vendor: weaveworks
product: vscode-gitops-tools
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: LOW
baseScore: 5.2
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: HIGH
scope: CHANGED
userInteraction: REQUIRED
vectorString: CVSS:3.1/AV:L/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L
version: 3.1
Published: 2022-08-18T18:50:08.000Z
CVE-2022-35977 Integer overflow in certain command arguments can drive Redis to OOM panic
Redis is an in-memory database that persists on disk. Authenticated users issuing specially crafted `SETRANGE` and `SORT(_RO)` commands can trigger an integer overflow, resulting with Redis attempting to allocate impossible amounts of memory and abort with an out-of-memory (OOM) panic. The problem is fixed in Redis versions 7.0.8, 6.2.9 and 6.0.17. Users are advised to upgrade. There are no known workarounds for this vulnerability.
Problem types: cwe_id: CWE-190
description: CWE-190: Integer Overflow or Wraparound
Affected products: vendor: redis
product: redis
CVSS v3.1: attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 5.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2023-01-20T18:19:27.692Z
CVE-2022-35978 Lua sandbox escape from mod in Minetest
Minetest is a free open-source voxel game engine with easy modding and game creation. In **single player**, a mod can set a global setting that controls the Lua script loaded to display the main menu. The script is then loaded as soon as the game session is exited. The Lua environment the menu runs in is not sandboxed and can directly interfere with the user's system. There are currently no known workarounds.
Problem types: cwe_id: CWE-693
description: CWE-693: Protection Mechanism Failure
Affected products: vendor: minetest
product: minetest
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: LOW
baseScore: 7.7
baseSeverity: HIGH
confidentialityImpact: LOW
integrityImpact: HIGH
privilegesRequired: LOW
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:L/I:H/A:L
version: 3.1
Published: 2022-08-15T19:05:11.000Z
CVE-2022-35979 Segfault in `QuantizedRelu` and `QuantizedRelu6`
TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:10:10.000Z
CVE-2022-35980 OpenSearch vulnerable to Improper Authorization of Index Containing Sensitive Information
OpenSearch Security is a plugin for OpenSearch that offers encryption, authentication and authorization. Versions 2.0.0.0 and 2.1.0.0 of the security plugin are affected by an information disclosure vulnerability. Requests to an OpenSearch cluster configured with advanced access control features document level security (DLS), field level security (FLS), and/or field masking will not be filtered when the query's search pattern matches an aliased index. OpenSearch Dashboards creates an alias to `.kibana` by default, so filters with the index pattern of `*` to restrict access to documents or fields will not be applied. This issue allows requests to access sensitive information when customer have acted to restrict access that specific information. OpenSearch 2.2.0, which is compatible with OpenSearch Security 2.2.0.0, contains the fix for this issue. There is no recommended work around.
Problem types: cwe_id: CWE-612
description: CWE-612: Improper Authorization of Index Containing Sensitive Information
Affected products: vendor: opensearch-project
product: security
CVSS v3.1: attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 7.5
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
version: 3.1
Published: 2022-08-12T17:40:09.000Z
CVE-2022-35981 `CHECK` fail in `FractionalMaxPoolGrad` in TensorFlow
TensorFlow is an open source platform for machine learning. `FractionalMaxPoolGrad` validates its inputs with `CHECK` failures instead of with returning errors. If it gets incorrectly sized inputs, the `CHECK` failure can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 8741e57d163a079db05a7107a7609af70931def4. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:15:12.000Z
CVE-2022-35982 Segfault in `SparseBincount` in TensorFlow
TensorFlow is an open source platform for machine learning. If `SparseBincount` is given inputs for `indices`, `values`, and `dense_shape` that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:30:13.000Z
CVE-2022-35983 `CHECK` fail in `Save` and `SaveSlices` in TensorFlow
TensorFlow is an open source platform for machine learning. If `Save` or `SaveSlices` is run over tensors of an unsupported `dtype`, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:40:10.000Z
CVE-2022-35984 `CHECK` fail in `ParameterizedTruncatedNormal` in TensorFlow
TensorFlow is an open source platform for machine learning. `ParameterizedTruncatedNormal` assumes `shape` is of type `int32`. A valid `shape` of type `int64` results in a mismatched type `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 72180be03447a10810edca700cbc9af690dfeb51. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:40:14.000Z
CVE-2022-35985 `CHECK` fail in `LRNGrad` in TensorFlow
TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:40:20.000Z
CVE-2022-35986 Segfault in `RaggedBincount` in TensorFlow
TensorFlow is an open source platform for machine learning. If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7a4591fd4f065f4fa903593bc39b2f79530a74b8. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-20
description: CWE-20: Improper Input Validation
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:45:13.000Z
CVE-2022-35987 `CHECK` fail in `DenseBincount` in TensorFlow
TensorFlow is an open source platform for machine learning. `DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:40:24.000Z
CVE-2022-35988 `CHECK` fail in `tf.linalg.matrix_rank` in TensorFlow
TensorFlow is an open source platform for machine learning. When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:35:10.000Z
CVE-2022-35989 `CHECK` fail in `MaxPool` in TensorFlow
TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T21:35:15.000Z
CVE-2022-35990 `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannelGradient` in TensorFlow
TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:00:12.000Z
CVE-2022-35991 `CHECK` fail in `TensorListScatter` and `TensorListScatterV2` in TensorFlow
TensorFlow is an open source platform for machine learning. When `TensorListScatter` and `TensorListScatterV2` receive an `element_shape` of a rank greater than one, they give a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:20:16.000Z
CVE-2022-35992 `CHECK` fail in `TensorListFromTensor` in TensorFlow
TensorFlow is an open source platform for machine learning. When `TensorListFromTensor` receives an `element_shape` of a rank greater than one, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 3db59a042a38f4338aa207922fa2f476e000a6ee. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Problem types: cwe_id: CWE-617
description: CWE-617: Reachable Assertion
Affected products: vendor: tensorflow
product: tensorflow
CVSS v3.1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
Published: 2022-09-16T22:20:21.000Z