CVE-2020-15202 Detail
This vulnerability is currently undergoing analysis and not all information is available. Please check back soon to view the completed vulnerability summary.
Description
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Severity
References to Advisories, Solutions, and Tools
By selecting these links, you will be leaving NIST webspace. We have provided these links to other web sites because they may have information that would be of interest to you. No inferences should be drawn on account of other sites being referenced, or not, from this page. There may be other web sites that are more appropriate for your purpose. NIST does not necessarily endorse the views expressed, or concur with the facts presented on these sites. Further, NIST does not endorse any commercial products that may be mentioned on these sites. Please address comments about this page to [email protected].
Weakness Enumeration
| CWE-ID | CWE Name | Source |
|---|---|---|
| CWE-754 | Improper Check for Unusual or Exceptional Conditions | GitHub, Inc. |
| CWE-197 | Numeric Truncation Error | GitHub, Inc. |
Change History
0 change records found show changes
Quick Info
CVE Dictionary Entry:
CVE-2020-15202
NVD Published Date:
09/25/2020
NVD Last Modified:
09/25/2020
Source:
MITRE