Buffer overflow in Google Tensorflow

CVE-2021-29542

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements. If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`. 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.

EPSS: 0.002 (9.9th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 2.5 (Low). Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2021-29542?
CVE-2021-29542 is a low-severity vulnerability in Google Tensorflow, classified under Incorrect Calculation of Buffer Size. CVSS score: 2.5/10. Published 2021-05-14.
How severe is CVE-2021-29542?
Low severity. CVSS v3 base score is 2.5 out of 10.