CVE-2021-37648: Incorrect validation of `SaveV2` inputs in TensorFlow
Noroxi assessment
Priority: Monitor (action score 31/100)
- The sources we track (CISA KEV, Exploit-DB, Metasploit, Nuclei, GitHub) show no public exploit code or exploitation in the wild.
- Probability of exploitation in the next 30 days: 0.18% (FIRST EPSS).
- Someone with local access to the system can trigger it. A low-privileged account is enough. No user action is required. No special conditions are required; it is repeatable.
- Fixed version: bazel-skylib1.0.3 (openSUSE:Leap 15.3) 1.0.3-bp153.2.1; bazel3.7 (openSUSE:Leap 15.3) 3.7.2-bp153.4.1; tensorflow2 (openSUSE:Leap 15.3) 2.6.0-bp153.2.3.1.
Low priority for now. Upgrade to bazel-skylib1.0.3 (openSUSE:Leap 15.3) 1.0.3-bp153.2.1; bazel3.7 (openSUSE:Leap 15.3) 3.7.2-bp153.4.1; tensorflow2 (openSUSE:Leap 15.3) 2.6.0-bp153.2.3.1 or later.
Generated automatically from the record's data: CVSS (NVD and CNA), CISA KEV and SSVC, FIRST EPSS, exploit sources, fixed versions. How we calculate it
Primary sources: NVD · CVE.org · FIRST EPSS
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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.
- Published
- Aug 12, 2021
- Updated
- Jun 17, 2026
- EPSS
- 0.1% · 8th percentile
- CWE
- CWE-476
Report tools
Action score
31
Monitor
Low priority for now.
- CVSS
- 31 / 40 · 7.8 / 10
- CISA KEV
- 0 / 30 · Not listed
- EPSS
- 0 / 30 · 0.1%
CNA vs NVD score
- NVD
- 7.8
- CNA · GitHub_M
- 7.8
- agree
The score given by the assigning authority versus NVD’s independent score. A gap means the severity is contested.
Get told when this record changes
- Not in KEV: no record of exploitation in the wild
- No public exploit code on record
- A fix has been released
If any of these changes, we'll tell you in the daily email digest.
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Noroxi analysis
What does it mean in your environment?
The assessment above is generated automatically from the record's data; it doesn't know your environment. Our team verifies on your systems whether this vulnerability is actually exploitable and which mitigation is enough.
We use this product, ask for helpAffected systems
Is your version affected?
Pick the product and type the version you run. It's compared with this record's version ranges in your browser; the version isn't sent anywhere.
| Vendor | Product | CPE |
|---|---|---|
| tensorflow | cpe:2.3:a:google:tensorflow |
Affected versions
NVD version ranges (for catalog products). Add the product to your stack with a version and matching uses these.
- google tensorflow2.3.0 and later · before 2.3.4
- google tensorflow2.4.0 and later · before 2.4.3
- google tensorflow2.5.0
- google tensorflow2.6.0
Versions reported by the vendor
Affected version ranges reported by the assigning authority (GitHub_M). Independent of NVD's CPE analysis and usually ahead of it.
tensorflow tensorflow
- >= 2.5.0, < 2.5.1, >= 2.4.0, < 2.4.3, < 2.3.4affected
Package-level exposure
OSV and GitHub Advisory data: ecosystem, package and range. SBOM matching uses this table.
| Ecosystem | Package | Affected range | Fix |
|---|---|---|---|
| openSUSE:Leap 15.3 | bazel-skylib1.0.3 | before 1.0.3-bp153.2.1 | 1.0.3-bp153.2.1 |
| openSUSE:Leap 15.3 | bazel3.7 | before 3.7.2-bp153.4.1 | 3.7.2-bp153.4.1 |
| openSUSE:Leap 15.3 | tensorflow2 | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| openSUSE:Leap 15.3 | tensorflow2_2_6_0-gnu-hpc | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| openSUSE:Leap 15.3 | tensorflow2_2_6_0-gnu-openmpi2-hpc | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| openSUSE:Leap 15.3 | tensorflow2-lite | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| PyPI | tensorflow | from 2.3.0 · before 2.3.4 | 2.3.4 |
| PyPI | tensorflow | from 2.4.0 · before 2.4.3 | 2.4.3 |
| PyPI | tensorflow | from 2.5.0 · before 2.5.1 | 2.5.1 |
| PyPI | tensorflow | before 2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | from 2.3.0 · before 2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | from 2.4.0 · before 2.4.3 | 2.4.3 |
| PyPI | tensorflow-cpu | from 2.5.0 · before 2.5.1 | 2.5.1 |
| PyPI | tensorflow-cpu | before 2.3.4 | 2.3.4 |
| PyPI | tensorflow-gpu | from 2.3.0 · before 2.3.4 | 2.3.4 |
| PyPI | tensorflow-gpu | from 2.4.0 · before 2.4.3 | 2.4.3 |
| PyPI | tensorflow-gpu | from 2.5.0 · before 2.5.1 | 2.5.1 |
| PyPI | tensorflow-gpu | before 2.3.4 | 2.3.4 |
| SUSE:Package Hub 15 SP3 | bazel-skylib1.0.3 | before 1.0.3-bp153.2.1 | 1.0.3-bp153.2.1 |
| SUSE:Package Hub 15 SP3 | bazel3.7 | before 3.7.2-bp153.4.1 | 3.7.2-bp153.4.1 |
| SUSE:Package Hub 15 SP3 | tensorflow2 | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| SUSE:Package Hub 15 SP3 | tensorflow2_2_6_0-gnu-hpc | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| SUSE:Package Hub 15 SP3 | tensorflow2_2_6_0-gnu-openmpi2-hpc | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
| SUSE:Package Hub 15 SP3 | tensorflow2-lite | before 2.6.0-bp153.2.3.1 | 2.6.0-bp153.2.3.1 |
Same product
google: all recordsOther highest-scoring records for the same primary product.
- CVE-2023-25668TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation39Monitor
- CVE-2023-25664TensorFlow vulnerable to Heap Buffer Overflow in AvgPoolGrad39Monitor
- CVE-2022-41900FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow39Monitor
Published before and after this one in the same product
- ← EarlierCVE-2021-37662Aug 12, 2021 · Reference binding to nullptr in boosted trees in TensorFlow31Monitor
- ← EarlierCVE-2021-37664Aug 12, 2021 · Heap OOB in boosted trees in TensorFlow28Monitor
- Later →CVE-2021-37652Aug 12, 2021 · Use after free in boosted trees creation in TensorFlow31Monitor
Remediation
Which version to upgrade to
Fix versions compiled from the vendor, package registries and Microsoft. Verify the vendor's note before upgrading.
| Product / package | Fixed version | Source |
|---|---|---|
| opensuse:bazel-skylib1.0.3 | 1.0.3-bp153.2.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| opensuse:bazel3.7 | 3.7.2-bp153.4.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| opensuse:tensorflow2 | 2.6.0-bp153.2.3.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| opensuse:tensorflow2_2_6_0-gnu-hpc | 2.6.0-bp153.2.3.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| opensuse:tensorflow2_2_6_0-gnu-openmpi2-hpc | 2.6.0-bp153.2.3.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| opensuse:tensorflow2-lite | 2.6.0-bp153.2.3.1 · openSUSE:Leap 15.3 | Package registry (OSV) |
| PyPI:tensorflow | 2.3.4 | Package registry (OSV) |
| PyPI:tensorflow | 2.4.3 | Package registry (OSV) |
| PyPI:tensorflow | 2.5.1 | Package registry (OSV) |
| PyPI:tensorflow-cpu | 2.3.4 | Package registry (OSV) |
| PyPI:tensorflow-cpu | 2.4.3 | Package registry (OSV) |
| PyPI:tensorflow-cpu | 2.5.1 | Package registry (OSV) |
| PyPI:tensorflow-gpu | 2.3.4 | Package registry (OSV) |
| PyPI:tensorflow-gpu | 2.4.3 | Package registry (OSV) |
| PyPI:tensorflow-gpu | 2.5.1 | Package registry (OSV) |
| suse:bazel-skylib1.0.3 | 1.0.3-bp153.2.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
| suse:bazel3.7 | 3.7.2-bp153.4.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
| suse:tensorflow2 | 2.6.0-bp153.2.3.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
| suse:tensorflow2_2_6_0-gnu-hpc | 2.6.0-bp153.2.3.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
| suse:tensorflow2_2_6_0-gnu-openmpi2-hpc | 2.6.0-bp153.2.3.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
| suse:tensorflow2-lite | 2.6.0-bp153.2.3.1 · SUSE:Package Hub 15 SP3 | Package registry (OSV) |
Exploit status
No known public exploit
No public exploit has been observed yet. That doesn't mean you're safe, only that the bar is a little higher.
Research context
For pentesters and researchers: attack profile, score disagreement, timeline, patch commits, credits, variant and chain candidates, bug bounty scope. All derived from existing data; no exploit code.
Timeline
From publication to today: proof of concept, Metasploit module, CISA KEV and fix record. Dates are as reported by the sources.
No dated events beyond publication.
No history yet (it accumulates with the daily EPSS job).
Patch and commit links
Commit, PR and diff links among the references. A starting point for patch-diffing and variant hunting; fixes, not exploits.
Credits
All researchersFinders, reporters and analysts named in the CNA record. Click a name for that researcher’s other records.
No credits in the CNA record.
Variant candidates
Same product, same weakness class, within 18 months. If the patch missed the root cause, the sibling bug is here.
No nightly-computed relations.
Chain candidates
An authentication bypass and a privilege-requiring bug in the same product, published close together: combined they may become an unauthenticated path.
—
Bug bounty scope
No known public program.
Source: bounty-targets-data (public HackerOne, Bugcrowd, Intigriti, YesWeHack listings).
Technical details
Attack conditions
- Someone with local access to the system can trigger it.
- A low-privileged account is enough.
- No user action is required.
- No special conditions are required; it is repeatable.
If successful
- Confidentiality
- high · data can be read
- Integrity
- high · data or configuration can be modified
- Availability
- high · the service can be disrupted
- Attack vector
- Local
- Attack complexity
- Low
- Privileges required
- Low
- User interaction
- None
- Scope
- Unchanged
- Confidentiality impact
- High
- Integrity impact
- High
- Availability impact
- High
Weakness class (CWE)
CWE-476 · NULL Pointer DereferenceCVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvd-primary
Attack context
MITRE CAPEC attack patterns and ATT&CK techniques for this weakness class (CWE). A starting point for detection rules and threat hunting.
MITRE has no CAPEC/ATT&CK mapping for this CWE.
Change log
- Fix✗ → ✓
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References
Show all references (1 more)Show less
Vendor advisories and official records. Exploit/PoC links are deliberately left out.