CVE-2021-29601
TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format.
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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.
CVSS
- Version: 3.1
- Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
- Base score: 7.1
Exploitation probability (EPSS)
- Probability of exploitation in the next 30 days: 0.19%
- Percentile among all scored CVEs: 8
- Score date: 10/7/2026
EPSS (Exploit Prediction Scoring System, FIRST) estimates how likely a vulnerability is to be exploited in the wild within 30 days. It complements CVSS (impact) and CISA KEV (confirmed exploitation).
Affected technologies (1)
CWEs
- CWE-190
References
- https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c84-4hx6-xmm4
- https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c84-4hx6-xmm4
Raw JSON (NVD)
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"published": "2021-05-14T20:15:15.487",
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"lang": "en",
"value": "TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. 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."
},
{
"lang": "es",
"value": "TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático. La implementación de TFLite de la concatenación es vulnerable a un problema de desbordamiento de enteros (https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). Un atacante puede diseñar un modelo tal que las dimensiones de una de las entradas de concatenación desborden los valores de \"int\". TFLite usa \"int\" para representar las dimensiones del tensor, mientras que TF usa \"int64\". Por lo tanto, los modelos TF válidos pueden desencadenar un desbordamiento de enteros cuando se convierten al formato TFLite. La corrección será incluida en TensorFlow versión 2.5.0. También seleccionaremos este commit en TensorFlow versión 2.4.2, TensorFlow versión 2.3.3, TensorFlow versión 2.2.3 y TensorFlow versión 2.1.4, ya que estos también están afectados y aún están en el rango compatible"
}
],
"lastModified": "2026-06-17T03:48:00.013",
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