CVE-2022-21736 json
Undefined behavior in Tensorflow
published 4y ago modified last mo. also BIT-tensorflow-2022-21736 , EUVD-2022-0299 , GHSA-pfjj-m3jj-9jc9 , PYSEC-2022-115 , PYSEC-2022-60 , PYSEC-2026-3223
- cvss
- 7.6
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.8%
- EPSS 0.8% chance of exploitation in 30 days, percentile 55%
- public exploits
- 0
- none known
Summary
Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseTensorSliceDataset` has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value. The 3 input arguments to `SparseTensorSliceDataset` represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Patch / fix
- pypi tensorflow 2.5.3, 2.6.3, 2.7.1
- pypi tensorflow-cpu 2.5.3, 2.6.3, 2.7.1
- pypi tensorflow-gpu 2.5.3, 2.6.3, 2.7.1
- bitnami tensorflow 2.5.3, 2.6.3, 2.7.1
Is CVE-2022-21736 in your dependencies? Fencer shows which of your repositories are affected as soon as an advisory lands, and opens the fix as a pull request.
Check with FencerCISA SSVC
- Exploitation
- Proof of concept is public
- Automatable
- no
- Technical impact
- partial
- Assessed
- last yr.
Exploit prediction
0.75% chance of exploitation in the next 30 days, higher than 55% of all scored CVEs (FIRST EPSS, 2026-11-09).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 7.6 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H |
| GitHub | 3.1 | 7.6 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H |
| NVD | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| NVD | 2.0 | 4.0 | AV:N/AC:L/Au:S/C:N/I:N/A:P |
| OSV | 3.1 | 7.6 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | <2.5.3 >=2.6.0, <2.6.3 >=2.7.0, <2.7.1 |
2.5.3 2.6.3 2.7.1 |
| pypi | tensorflow-cpu | <2.5.3 >=2.6.0, <2.6.3 >=2.7.0, <2.7.1 |
2.5.3 2.6.3 2.7.1 |
| pypi | tensorflow-gpu | <2.5.3 >=2.6.0, <2.6.3 >=2.7.0, <2.7.1 |
2.5.3 2.6.3 2.7.1 |
| bitnami | tensorflow | <2.5.3 >=2.6.0, <2.6.3 >=2.7.0, <2.7.1 |
2.5.3 2.6.3 2.7.1 |
Classification
- Weakness
-
- CWE-476 NULL Pointer Dereference
References
-
github.com
/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tenso
web, exploit, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-21736
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-60.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-115.yaml
web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-pfjj-m3jj-9jc9
advisory
Sources
- CVE List CVE-2022-21736
- GitHub Advisory GHSA-pfjj-m3jj-9jc9
- NVD CVE-2022-21736
- OSV BIT-tensorflow-2022-21736
- OSV PYSEC-2022-115
- OSV PYSEC-2022-60
- OSV PYSEC-2026-3223
Fencer Intel 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.