Buffer overflow in Google Tensorflow
CVE-2021-29537
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedResizeBilinear` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/50711818d2e61ccce012591eeb4fdf93a8496726/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L705-L706) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. 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 (11.5th 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
- Google Tensorflow
- Tensorflow — versions < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3
Weakness classification (CWE)
References
- security-advisories@github.com (x_refsource_CONFIRM, Exploit, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2021-29537?
- CVE-2021-29537 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-2021-29537?
- Low severity. CVSS v3 base score is 2.5 out of 10.