CVE-2021-29519 json
CHECK-fail in SparseCross due to type confusion
published 2021-05-14 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-29519 , EUVD-2021-0260 , GHSA-772j-h9xw-ffp5 , PYSEC-2021-156 , PYSEC-2021-447 , PYSEC-2021-645
- cvss
- 2.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.2%
- EPSS 0.2% chance of exploitation in 30 days, percentile 8%
- public exploits
- 0
- none known
Summary
TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Patch / fix
- pypi tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
- pypi tensorflow-cpu 2.1.4, 2.2.3, 2.3.3, 2.4.2
- pypi tensorflow-gpu 2.1.4, 2.2.3, 2.3.3, 2.4.2
- bitnami tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
- google tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
- tensorflow Arch Linux 2.5.0-1
arch linux advisories AVG-1962
Exploit prediction
0.19% chance of exploitation in the next 30 days, higher than 8% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5 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 | <2.1.4 >=2.2.0, <2.2.3 >=2.3.0, <2.3.3 >=2.4.0, <2.4.2 |
2.1.4 2.2.3 2.3.3 2.4.2 |
| pypi | tensorflow-cpu | <2.1.4 >=2.2.0, <2.2.3 >=2.3.0, <2.3.3 >=2.4.0, <2.4.2 |
2.1.4 2.2.3 2.3.3 2.4.2 |
| pypi | tensorflow-gpu | <2.1.4 >=2.2.0, <2.2.3 >=2.3.0, <2.3.3 >=2.4.0, <2.4.2 |
2.1.4 2.2.3 2.3.3 2.4.2 |
| bitnami | tensorflow | <2.1.4 >=2.2.0, <2.2.3 >=2.3.0, <2.3.3 >=2.4.0, <2.4.2 |
2.1.4 2.2.3 2.3.3 2.4.2 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-843 Access of Resource Using Incompatible Type
References
-
github.com
/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5
web, exploit, patch, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2021-29519
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-447.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-645.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-156.yaml
web
Sources
- CVE List CVE-2021-29519
- GitHub Advisory GHSA-772j-h9xw-ffp5
- NVD CVE-2021-29519
- OSV BIT-tensorflow-2021-29519
- OSV PYSEC-2021-156
- OSV PYSEC-2021-447
- OSV PYSEC-2021-645
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.