Vulnerability · Published Sep 25, 2020 · Assigned by GitHub_M
CVE-2020-15196Heap buffer overflow in Tensorflow
High 8.5
In plain English
A high-severity memory corruption in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.9% (higher than 60% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official description
In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.3.1 | GHSA-pg59-2f92-5cph |
| PyPI | tensorflow | 2.3.1 | PYSEC-2020-119 |
| PyPI | tensorflow-cpu | 2.3.1 | GHSA-pg59-2f92-5cph |
| PyPI | tensorflow-cpu | 2.3.1 | PYSEC-2020-276 |
| PyPI | tensorflow-gpu | 2.3.1 | GHSA-pg59-2f92-5cph |
| PyPI | tensorflow-gpu | 2.3.1 | PYSEC-2020-311 |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | = 2.3.0 |
Weakness: CWE-119, CWE-122 · Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H