CVE-2021-29569
CVE-2021-29569 is a low-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 2.5. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-125.
Key facts
- Severity: Low (CVSS 3.x base score 2.5)
- CVSS v2: 3.6
- EPSS exploit prediction: 0% (10th percentile)
- Actively exploited: Not listed in CISA KEV
- Weakness: CWE-125
- Affected product: Google Tensorflow
- Published:
- Last modified:
Description
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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.
Frequently asked questions
- What is CVE-2021-29569?
- TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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.
- How severe is CVE-2021-29569?
- CVE-2021-29569 has a CVSS 3.x base score of 2.5, rated low severity. It is exploitable over local access with high attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability low.
- Is CVE-2021-29569 being actively exploited?
- It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (10th percentile), an estimate of the probability of exploitation in the next 30 days.
- What products are affected by CVE-2021-29569?
- CVE-2021-29569 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
- How do I fix CVE-2021-29569?
- Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
- When was CVE-2021-29569 published?
- CVE-2021-29569 was published on 2021-05-14 and last updated on 2026-06-17.
References
- https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm
Affected products (1)
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
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