CVE-2021-29544 json
CHECK-fail in `QuantizeAndDequantizeV4Grad`
published 2021-05-14 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-29544 , EUVD-2021-0285 , GHSA-6g85-3hm8-83f9 , PYSEC-2021-181 , PYSEC-2021-472 , PYSEC-2021-670
- cvss
- 2.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.3%
- EPSS 0.3% chance of exploitation in 30 days, percentile 23%
- public exploits
- 0
- none known
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`. This is because the implementation does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to `QuantizeAndDequantizePerChannelGradientImpl`. However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version.
Patch / fix
- pypi tensorflow 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.2, 2.4.3
- pypi tensorflow-cpu 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.2, 2.4.3
- pypi tensorflow-gpu 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.2, 2.4.3
- bitnami tensorflow 2.4.2
- google tensorflow 2.4.2
- tensorflow Arch Linux 2.5.0-1
arch linux advisories AVG-1962
Exploit prediction
0.31% chance of exploitation in the next 30 days, higher than 23% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6g85-3hm8-83f9 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 2.5 | CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L |
| GitHub | 3.1 | 2.5 | CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L |
| NVD | 3.1 | 5.5 | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| NVD | 2.0 | 2.1 | AV:L/AC:L/Au:N/C:N/I:N/A:P |
| OSV | 3.1 | 5.5 | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | >=2.4.0, <2.4.2 <2.2.0rc0 >=2.2.0, <2.3.0rc0 >=2.3.0, <2.3.4 >=2.4.0, <2.4.3 |
2.4.2 2.2.0rc0 2.3.0rc0 2.3.4 2.4.3 |
| pypi | tensorflow-cpu | >=2.4.0, <2.4.2 <2.2.0rc0 >=2.2.0, <2.3.0rc0 >=2.3.0, <2.3.4 >=2.4.0, <2.4.3 |
2.4.2 2.2.0rc0 2.3.0rc0 2.3.4 2.4.3 |
| pypi | tensorflow-gpu | >=2.4.0, <2.4.2 <2.2.0rc0 >=2.2.0, <2.3.0rc0 >=2.3.0, <2.3.4 >=2.4.0, <2.4.3 |
2.4.2 2.2.0rc0 2.3.0rc0 2.3.4 2.4.3 |
| bitnami | tensorflow | >=2.4.0, <2.4.2 |
2.4.2 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-754 Improper Check for Unusual or Exceptional Conditions
References
-
github.com
/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-6g85-3hm8-83f9
web, exploit, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequ
web
-
github.com
/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequ
web
-
nvd.nist.gov
/vuln/detail/CVE-2021-29544
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-472.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-670.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-181.yaml
web
-
github.com
/tensorflow/tensorflow
package
Sources
- CVE List CVE-2021-29544
- GitHub Advisory GHSA-6g85-3hm8-83f9
- NVD CVE-2021-29544
- OSV BIT-tensorflow-2021-29544
- OSV PYSEC-2021-181
- OSV PYSEC-2021-472
- OSV PYSEC-2021-670
Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.