CVE-2021-29521
CVE-2021-29521 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-131.
Key facts
- Severity: Low (CVSS 3.x base score 2.5)
- CVSS v2: 2.1
- EPSS exploit prediction: 0% (9th percentile)
- Actively exploited: Not listed in CISA KEV
- Weakness: CWE-131
- Affected product: Google Tensorflow
- Published:
- Last modified:
Description
TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
Frequently asked questions
- What is CVE-2021-29521?
- TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
- How severe is CVE-2021-29521?
- CVE-2021-29521 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-2021-29521 being actively exploited?
- It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (9th percentile), an estimate of the probability of exploitation in the next 30 days.
- What products are affected by CVE-2021-29521?
- CVE-2021-29521 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
- How do I fix CVE-2021-29521?
- Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
- When was CVE-2021-29521 published?
- CVE-2021-29521 was published on 2021-05-14 and last updated on 2026-06-17.
References
- https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm
Affected products (1)
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
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