Vulnerabilities > Google > Tensorflow
| DATE | CVE | VULNERABILITY TITLE | RISK |
|---|---|---|---|
| 2020-12-10 | CVE-2020-26267 | Out-of-bounds Read vulnerability in Google Tensorflow In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. | 7.8 |
| 2020-12-10 | CVE-2020-26266 | Use of Uninitialized Resource vulnerability in Google Tensorflow In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. | 5.3 |
| 2020-12-10 | CVE-2020-26271 | Use of Uninitialized Resource vulnerability in Google Tensorflow In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. | 3.3 |
| 2020-10-21 | CVE-2020-15266 | Improper Restriction of Operations within the Bounds of a Memory Buffer vulnerability in Google Tensorflow In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. | 7.5 |
| 2020-10-21 | CVE-2020-15265 | Out-of-bounds Read vulnerability in Google Tensorflow In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. | 7.5 |
| 2020-09-25 | CVE-2020-15214 | Out-of-bounds Write vulnerability in Google Tensorflow 2.2.0/2.3.0 In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. | 8.1 |
| 2020-09-25 | CVE-2020-15213 | Allocation of Resources Without Limits or Throttling vulnerability in Google Tensorflow 2.2.0/2.3.0 In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. | 4.0 |
| 2020-09-25 | CVE-2020-15212 | Out-of-bounds Write vulnerability in Google Tensorflow 2.2.0/2.3.0 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. | 8.6 |
| 2020-09-25 | CVE-2020-15211 | Out-of-bounds Write vulnerability in multiple products In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. | 4.8 |
| 2020-09-25 | CVE-2020-15210 | Out-of-bounds Write vulnerability in multiple products In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. | 6.5 |