Vulnerability in Google Tensorflow
CVE-2020-26266
In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
Published · last modified .
CVSS v3 metric
CVSS v3 base score 4.4 (Medium). Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L.
EPSS exploit prediction
EPSS: 0.003 (16.1th percentile), scored .
Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 16th percentile — 16.1% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.
EPSS over last 30 days · oldest: 0.003 · newest: 0.003 · change: +0.000
Affected products
- Google Tensorflow
- Tensorflow — versions < 1.15.5, >= 2.0.0, < 2.0.4, >= 2.1.0, < 2.1.3
Weakness classification (CWE)
References
- github.com/tensorflow/tensorflow/security/advisories/GHSA-qhxx-j73r-qpm2 (Exploit, Patch, Third Party Advisory)
- github.com/tensorflow/tensorflow/commit/ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2 (Patch, Third Party Advisory)
Frequently asked questions
- What is CVE-2020-26266?
- CVE-2020-26266 is a medium-severity vulnerability in Google Tensorflow, classified under Use of Uninitialized Resource. CVSS score: 4.4/10. Published 2020-12-10.
- How severe is CVE-2020-26266?
- Medium severity. CVSS v3 base score is 4.4 out of 10.