CVE-2022-41890
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 · uneditedTensorFlow is an open source platform for machine learning. If `BCast::ToShape` is given input larger than an `int32`, it will crash, despite being supposed to handle up to an `int64`. An example can be seen in `tf.experimental.numpy.outer` by passing in large input to the input `b`. We have patched the issue in GitHub commit 8310bf8dd188ff780e7fc53245058215a05bdbe5. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 analysisA detailed technical summary for this CVE is being prepared.
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< 2.8.4>= 2.9.0, < 2.9.3>= 2.10.0, < 2.10.1CVSS 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
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/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 · scoped2.8.42.9.32.10.1
TensorFlow 2.11.0 (or any version >= 2.11); alternatively 2.10.1, 2.9.3, or 2.8.4 for patch backports
- Identify the current TensorFlow version in your environment using `pip show tensorflow` or `import tensorflow; print(tensorflow.__version__)`
- Upgrade TensorFlow to a patched version: pip install --upgrade tensorflow==2.11.0 (or newer)
- Verify the upgrade was successful by running `python -c "import tensorflow; print(tensorflow.__version__)"`
- Test that `tf.experimental.numpy.outer` with large inputs no longer crashes (the fix addresses the BCast::ToShape int32 overflow)
Generated from the published advisory — verify against the referenced sources before acting.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2022-41890 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2022-41890 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
- No weaponised exploit code, or anything meant to cause harm
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