CVE-2021-37690
published 2021-08-13CVE-2021-37690: TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as…
PriorityP427medium6.6CVSS 3.1
AVLACLPRLUINSUCLILAH
EPSS
0.16%
5.9th percentile
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Affected
13 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | — | — | |
| tensorflow | — | — | |
| tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 | |
| tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 | |
| intel | optimization_for_tensorflow | >= 0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 0 < ee119d4a498979525046fba1c3dd3f13a039fbb1 | ee119d4a498979525046fba1c3dd3f13a039fbb1 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 |
| intel | optimization_for_tensorflow | >= 2.5.0 < 2.5.1 | 2.5.1 |
| tensorflow | tensorflow | < 2.3.4 | 2.3.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.16.6MEDIUMCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
nvdv2.04.6MEDIUMAV:L/AC:L/Au:N/C:P/I:P/A:P
vendor_debian6.6LOW
Stop checking back — get the weekly exploitation signal.
Every Monday: what got weaponized or added to CISA KEV in the last seven days — each CVE cross-linked to its PoC, Nuclei template, and detection rule. Free, one email a week, unsubscribe in one click.
GHSA
Use after free and segfault in shape inference functions
ghsa·2021-08-25
CVE-2021-37690 [MEDIUM] CWE-416 Use after free and segfault in shape inference functions
Use after free and segfault in shape inference functions
### Impact
When running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault.
`ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types.
### Patches
We have patched the issue in GitHub commit [ee119d4a4989795250
OSV
Use after free and segfault in shape inference functions
osv·2021-08-25
CVE-2021-37690 [MEDIUM] Use after free and segfault in shape inference functions
Use after free and segfault in shape inference functions
### Impact
When running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault.
`ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types.
### Patches
We have patched the issue in GitHub commit [ee119d4a4989795250
OSV
CVE-2021-37690: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-08-13
CVE-2021-37690 CVE-2021-37690: TensorFlow is an end-to-end open source platform for machine learning
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a49
Debian
CVE-2021-37690: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
vendor_debian·2021·CVSS 6.6
CVE-2021-37690 [MEDIUM] CVE-2021-37690: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a49
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hghttps://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg
2021-08-13
Published