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TensorflowApplication · Google

CVE-2022-21728

HIGH · 8.1 CVSS v3.1 Published 2022-02-03
Fix available
A fix is available. Upgrade to after 2.6.2 or later.
See remediation →
87/100
Remediation priority · High
Public exploit Remotely reachable 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 Open Source Machine Learning Framework. The implementation of shape inference for `ReverseSequence` does not fully validate the value of `batch_dim` and can result in a heap OOB read. There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values. Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then the implementation of `Dim` would access elements before the start of an array. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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:<= 2.5.2>= 2.6.0, <= 2.6.2= 2.7.0

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
Network
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
High

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/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 a release after 2.6.2
Vendor patch github.com →
Recommended fix High confidence

TensorFlow 2.8.0 (or 2.7.1/2.6.3/2.5.3 for minimal version upgrades)

  1. 1. Identify the current TensorFlow version in your environment using `pip show tensorflow` or `python -c 'import tensorflow; print(tensorflow.__version__)'`
  2. 2. Determine the appropriate upgrade path based on your current version: If using 2.5.x, upgrade to 2.5.3 or later; if using 2.6.x, upgrade to 2.6.3 or later; if using 2.7.0, upgrade to 2.7.1 or later; if using 2.8.0 or later, you are already fixed
  3. 3. Upgrade TensorFlow using pip: `pip install --upgrade tensorflow==<target_version>` (e.g., `pip install --upgrade tensorflow==2.8.0` for the latest fixed release)
  4. 4. Verify the upgrade was successful: `python -c 'import tensorflow; print(tensorflow.__version__)'`
  5. 5. Run your test suite to ensure compatibility with the new TensorFlow version
Caveat TensorFlow minor version upgrades may include API changes, deprecated features, or behavioral changes; review the release notes for the target version before upgrading

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

We can identify the exact fixed release, upgrade, and verify it in staging — 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-2022-21728 in production — separate from our analysis above.

No notes yet

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
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