TensorFlow is an open source platform for machine learning. The reference kernel of the `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the number of input channels is different than the number of output channels, the wrong result will be returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a model with a specific number of input channels. It is then possible to write specific values through the bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel resolver is used in the interpreter. We have patched the issue in GitHub commit 72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

The version of TensorFlow installed on the remote host is prior to 2.9.3. It is, therefore, affected by multiple vulnerabilities as referenced in the release notes.

    Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The version of TensorFlow installed on the remote host is prior to 2.10.1. It is, therefore, affected by multiple vulnerabilities as referenced in the release notes.

    Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The version of FreeBSD installed on the remote host is prior to tested version. It is, therefore, affected by a vulnerability as referenced in the 326b2f3e-6fc7-4661-955d-a772760db9cf advisory.

  - TensorFlow is an open source platform for machine learning. The reference kernel of the     `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the     result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the     number of input channels is different than the number of output channels, the wrong result will be     returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a     model with a specific number of input channels. It is then possible to write specific values through the     bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel     resolver is used in the interpreter. We have patched the issue in GitHub commit     72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also     cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and     still in supported range. (CVE-2022-41894)

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The version of tensorflow installed on the remote CBL Mariner 2.0 host is prior to tested version. It is, therefore, affected by a vulnerability as referenced in the CVE-2022-41894 advisory.

  - TensorFlow is an open source platform for machine learning. The reference kernel of the     `CONV_3D_TRANSPOSE` TensorFlow Lite operator wrongly increments the data_ptr when adding the bias to the     result. Instead of `data_ptr += num_channels;` it should be `data_ptr += output_num_channels;` as if the     number of input channels is different than the number of output channels, the wrong result will be     returned and a buffer overflow will occur if num_channels > output_num_channels. An attacker can craft a     model with a specific number of input channels. It is then possible to write specific values through the     bias of the layer outside the bounds of the buffer. This attack only works if the reference kernel     resolver is used in the interpreter. We have patched the issue in GitHub commit     72c0bdcb25305b0b36842d746cc61d72658d2941. The fix will be included in TensorFlow 2.11. We will also     cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and     still in supported range. (CVE-2022-41894)

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

ID	Name	Product	Family	Severity
197897	TensorFlow < 2.9.3 Multiple Vulnerabilities	Nessus	Misc.	critical
197513	TensorFlow < 2.10.1 Multiple Vulnerabilities	Nessus	Misc.	critical
174295	FreeBSD : py-tflite -- buffer overflow vulnerability (326b2f3e-6fc7-4661-955d-a772760db9cf)	Nessus	FreeBSD Local Security Checks	high
172958	CBL Mariner 2.0 Security Update: tensorflow (CVE-2022-41894)	Nessus	MarinerOS Local Security Checks	high

Detections

Analytics

CVE-2022-41894

high

Tenable Plugins

critical

critical

high

high