Medium
Security advisory
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.
- Products
- Not specified
- Affected versions
- Not specified
- Fixed versions
- Not specified
- CVEs
- CVE-2020-26266
- Confirmed fixed CVEs
- Not specified
- Updated in this feed
- 31 Oct 2026, 12:40 UTC · Revision 1
Source evidence
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.
osv:CVE-2020-26266
Complete source record
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"url": "https://osv.dev/vulnerability/CVE-2020-26266",
"method": "structured",
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"kind": "advisory",
"title": "CVE-2020-26266",
"summary": "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.",
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"GHSA-qhxx-j73r-qpm2",
"PYSEC-2020-254",
"PYSEC-2020-297",
"PYSEC-2020-332"
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"published_at": "2020-12-10T23:15:12.647+00:00"
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