CVE-2021-29600 json
Division by zero in TFLite's implementation of `OneHot`
published 2021-05-14 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-29600 , EUVD-2021-0341 , GHSA-j8qh-3xrq-c825 , PYSEC-2021-237 , PYSEC-2021-528 , PYSEC-2021-726
- 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 10%
- public exploits
- 0
- none known
Summary
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `OneHot` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L72). An attacker can craft a model such that at least one of the dimensions of `indices` would be 0. In turn, the `prefix_dim_size` value would become 0. 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
0.20% chance of exploitation in the next 30 days, higher than 10% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8qh-3xrq-c825 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 | 7.8 | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
| NVD | 2.0 | 4.6 | AV:L/AC:L/Au:N/C:P/I:P/A:P |
| OSV | 3.1 | 7.8 | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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-369 Divide By Zero
References
-
github.com
/tensorflow/tensorflow/commit/3ebedd7e345453d68e279cfc3e4072648e5e12e5
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-j8qh-3xrq-c825
web, exploit, patch, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2021-29600
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-528.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-726.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-237.yaml
web
-
github.com
/tensorflow/tensorflow
package
-
github.com
/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/one_hot.cc#L68-L7
web
Sources
- CVE List CVE-2021-29600
- GitHub Advisory GHSA-j8qh-3xrq-c825
- NVD CVE-2021-29600
- OSV BIT-tensorflow-2021-29600
- OSV PYSEC-2021-237
- OSV PYSEC-2021-528
- OSV PYSEC-2021-726
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.