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TensorflowApplication · Google

CVE-2021-37659

HIGH · 7.8 CVSS v3.1 Published 2021-08-12
Fix available
A fix is available. Upgrade to 2.3.4 / 2.4.3 or later.
See remediation →
80/100
Remediation priority · High
Zero-click Patch available

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis
How this class of weakness works · CWE-125

The code reads past the end (or before the start) of a buffer, returning memory that was never meant to be exposed. Attackers use it to leak secrets like keys or to defeat memory-protection defences. Remediation is validating indices and lengths before every read.

General guidance for the out-of-bounds read class — the official description and references above are authoritative for this specific CVE. Want a bespoke review and a reviewed fix? Ask our team →

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
TensorflowApplication
Affected:>= 2.3.0, < 2.3.4>= 2.4.0, < 2.4.3= 2.5.0= 2.6.0

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 2.3.4 / 2.4.3 or later
Fixed in 2.3.42.4.3
Vendor patch github.com →
Recommended fix High confidence

TensorFlow 2.6.1 (or 2.3.4/2.4.3/2.5.1 for respective branch users)

  1. 1. Identify current TensorFlow version by checking `import tensorflow; print(tensorflow.__version__)`
  2. 2. For TensorFlow 2.3.x users: Upgrade to version 2.3.4 or later using `pip install --upgrade tensorflow==2.3.4`
  3. 3. For TensorFlow 2.4.x users: Upgrade to version 2.4.3 or later using `pip install --upgrade tensorflow==2.4.3`
  4. 4. For TensorFlow 2.5.0 users: Upgrade to version 2.5.1 or later using `pip install --upgrade tensorflow==2.5.1`
  5. 5. For TensorFlow 2.6.0 users: Upgrade to version 2.6.1 or later using `pip install --upgrade tensorflow==2.6.1`
  6. 6. Verify the upgrade was successful by running `python -c "import tensorflow; print(tensorflow.__version__)"`
  7. 7. Test existing machine learning workloads to ensure compatibility with the new version
Caveat Minor version upgrades typically maintain backward compatibility, but test in staging environment before production deployment

Generated from the published advisory — verify against the referenced sources before acting.

We can perform the upgrade in your staging environment and verify nothing breaks — typical engagement from $3,200. Get the upgrade done

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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2021-37659 in production — separate from our analysis above.

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  • Version or environment caveats, and links to real fixes
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