PYSEC-2026-973
Vulnerability from pysec - Published: 2026-07-07 10:17 - Updated: 2026-07-07 11:31Impact
The function tf.raw_ops.LookupTableImportV2 cannot handle scalars in the values parameter and gives an NPE.
import tensorflow as tf
v = tf.Variable(1)
@tf.function(jit_compile=True)
def test():
func = tf.raw_ops.LookupTableImportV2
para={'table_handle': v.handle,'keys': [62.98910140991211, 94.36528015136719], 'values': -919}
y = func(**para)
return y
print(test())
Patches
We have patched the issue in GitHub commit 980b22536abcbbe1b4a5642fc940af33d8c19b69.
The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by r3pwnx of 360 AIVul Team
| Name | purl | tensorflow-gpu | pkg:pypi/tensorflow-gpu |
|---|
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu",
"purl": "pkg:pypi/tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.11.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.12.0",
"0.12.1",
"1.0.0",
"1.0.1",
"1.1.0",
"1.10.0",
"1.10.1",
"1.11.0",
"1.12.0",
"1.12.2",
"1.12.3",
"1.13.1",
"1.13.2",
"1.14.0",
"1.15.0",
"1.15.2",
"1.15.3",
"1.15.4",
"1.15.5",
"1.2.0",
"1.2.1",
"1.3.0",
"1.4.0",
"1.4.1",
"1.5.0",
"1.5.1",
"1.6.0",
"1.7.0",
"1.7.1",
"1.8.0",
"1.9.0",
"2.0.0",
"2.0.1",
"2.0.2",
"2.0.3",
"2.0.4",
"2.1.0",
"2.1.1",
"2.1.2",
"2.1.3",
"2.1.4",
"2.10.0",
"2.10.0rc0",
"2.10.0rc1",
"2.10.0rc2",
"2.10.0rc3",
"2.10.1",
"2.11.0",
"2.11.0rc0",
"2.11.0rc1",
"2.11.0rc2",
"2.2.0",
"2.2.1",
"2.2.2",
"2.2.3",
"2.3.0",
"2.3.1",
"2.3.2",
"2.3.3",
"2.3.4",
"2.4.0",
"2.4.1",
"2.4.2",
"2.4.3",
"2.4.4",
"2.5.0",
"2.5.1",
"2.5.2",
"2.5.3",
"2.6.0",
"2.6.1",
"2.6.2",
"2.6.3",
"2.6.4",
"2.6.5",
"2.7.0",
"2.7.0rc0",
"2.7.0rc1",
"2.7.1",
"2.7.2",
"2.7.3",
"2.7.4",
"2.8.0",
"2.8.0rc0",
"2.8.0rc1",
"2.8.1",
"2.8.2",
"2.8.3",
"2.8.4",
"2.9.0",
"2.9.0rc0",
"2.9.0rc1",
"2.9.0rc2",
"2.9.1",
"2.9.2",
"2.9.3"
]
}
],
"aliases": [
"CVE-2023-25672",
"GHSA-94mm-g2mv-8p7r"
],
"details": "### Impact\nThe function `tf.raw_ops.LookupTableImportV2` cannot handle scalars in the `values` parameter and gives an NPE.\n\n```python\nimport tensorflow as tf\n\nv = tf.Variable(1)\n\n@tf.function(jit_compile=True)\ndef test():\n func = tf.raw_ops.LookupTableImportV2\n para={\u0027table_handle\u0027: v.handle,\u0027keys\u0027: [62.98910140991211, 94.36528015136719], \u0027values\u0027: -919}\n\n y = func(**para)\n return y\n\nprint(test())\n```\n\n### Patches\nWe have patched the issue in GitHub commit [980b22536abcbbe1b4a5642fc940af33d8c19b69](https://github.com/tensorflow/tensorflow/commit/980b22536abcbbe1b4a5642fc940af33d8c19b69).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n\n### Attribution\nThis vulnerability has been reported by r3pwnx of 360 AIVul Team\n",
"id": "PYSEC-2026-973",
"modified": "2026-07-07T11:31:13.687908Z",
"published": "2026-07-07T10:17:29.140012Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-94mm-g2mv-8p7r"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-25672"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/980b22536abcbbe1b4a5642fc940af33d8c19b69"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/tensorflow-gpu"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-94mm-g2mv-8p7r"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "TensorFlow has Null Pointer Error in LookupTableImportV2"
}
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.