CVE intelligence and bounded remediation

CVE-2020-15193 — Google Tensorflow security vulnerability

High CVSS 7.1

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

Severity
High
CVSS
7.1 (3.1)
Published
2020-09-25
CISA KEV
Not currently listed
Ecosystem
python/pypi
Weaknesses
CWE-908

Affected products

  • google / tensorflow / 2.2.0
  • google / tensorflow / 2.3.0
  • opensuse / leap / 15.2

Matched remediation archetype

Buffer bounds, memory safety, and memory corruption

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Check exposure

  • Identify affected native-code versions, build flags, architectures, parsers, codecs, drivers, and input paths in all shipped artifacts.
  • Determine whether untrusted data reaches the affected routine and the process privilege, sandbox, and network exposure.
  • Confirm statically linked, vendored, firmware, and platform-provided copies, not only package-manager records.

Remediate safely

  • Apply the maintained upstream correction or replace the affected component, then rebuild every dependent artifact from clean inputs.
  • Adopt bounds-checked interfaces, validated sizes and integer conversions, clear ownership, and memory-safe components where practical.
  • Enable supported compiler and runtime hardening and add sanitized tests and fuzz regression seeds derived from non-weaponized fixtures.

Authoritative sources

Complete CVE record and remediation plan

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