CVE-2021-37662
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 end-to-end open source platform for machine learning. In affected versions an attacker can generate undefined behavior via a reference binding to nullptr in `BoostedTreesCalculateBestGainsPerFeature` and similar attack can occur in `BoostedTreesCalculateBestFeatureSplitV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) does not validate the input values. We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit 429f009d2b2c09028647dd4bb7b3f6f414bbaad7. 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 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>= 2.3.0, < 2.3.4>= 2.4.0, < 2.4.3= 2.5.0= 2.6.0CVSS 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 · scoped2.3.42.4.3
TensorFlow 2.6.0 (or 2.5.1, 2.4.3, 2.3.4 for minimal branch upgrades)
- Verify the current TensorFlow version in your environment using `pip show tensorflow` or `import tensorflow; print(tensorflow.__version__)`
- For Python pip installations, upgrade TensorFlow to version 2.6.0 or higher: `pip install --upgrade tensorflow==2.6.0`
- Alternatively, for the minimal patch versions, upgrade to 2.5.1, 2.4.3, or 2.3.4 depending on your original version branch: `pip install tensorflow==2.5.1` or `pip install tensorflow==2.4.3` or `pip install tensorflow==2.3.4`
- After upgrading, test that your machine learning workloads function correctly with the new TensorFlow version
- Ensure any model artifacts or serialized data formats are compatible with the new TensorFlow version
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-2021-37662 — 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-2021-37662 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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- Verified mitigations, workarounds, and config changes
- Version or environment caveats, and links to real fixes
- No weaponised exploit code, or anything meant to cause harm
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