NVD / CVE Program· CNA GitHub_M

CVE-2021-29512: Heap buffer overflow in `RaggedBinCount`

HighCVSS 7.8 · v3.1—No exploit Fix available

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: 0.21% (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: tensorflow (PyPI) 2.3.3, 2.4.2; tensorflow-cpu (PyPI) 2.3.3, 2.4.2; tensorflow-gpu (PyPI) 2.3.3, 2.4.2.
Severity is disputed: the assigning authority (CNA) scores it 2.5, NVD 7.8.
Mentioned 1 time in Turkish national cyber security advisories (siberguvenlik.gov.tr).

Low priority for now. Upgrade to tensorflow (PyPI) 2.3.3, 2.4.2; tensorflow-cpu (PyPI) 2.3.3, 2.4.2; tensorflow-gpu (PyPI) 2.3.3, 2.4.2 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. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L433). Before the `for` loop, `batch_idx` is set to 0. The user controls the `splits` array, making it contain only one element, 0. Thus, the code in the `while` loop would increment `batch_idx` and then try to read `splits(1)`, which is outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.

Memory safety

Published: May 14, 2021
Updated: Jun 16, 2026
EPSS: 0.2% · 11th percentile
CWE: CWE-120

Report tools

JSON

Action score

Monitor

Low priority for now.

CVSS: 31 / 40 · 7.8 / 10
CISA KEV: 0 / 30 · Not listed
EPSS: 0 / 30 · 0.2%

CNA vs NVD score

NVD: 7.8
CNA · GitHub_M: 2.5; 5.3 point gap

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

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.

Is your version affected? Check it

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.

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Affected 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
google	tensorflow	cpe:2.3:a:google:tensorflow

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
- >=2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2affected

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 2.3.3
google tensorflow2.4.0 and later · before 2.4.2

Package-level exposure

OSV and GitHub Advisory data: ecosystem, package and range. SBOM matching uses this table.

Ecosystem	Package	Affected range	Fix
PyPI	tensorflow	from 2.3.0 · before 2.3.3	2.3.3
PyPI	tensorflow	from 2.4.0 · before 2.4.2	2.4.2
PyPI	tensorflow-cpu	from 2.3.0 · before 2.3.3	2.3.3
PyPI	tensorflow-cpu	from 2.4.0 · before 2.4.2	2.4.2
PyPI	tensorflow-gpu	from 2.3.0 · before 2.3.3	2.3.3
PyPI	tensorflow-gpu	from 2.4.0 · before 2.4.2	2.4.2

Same product

google: all records

Other highest-scoring records for the same primary product.

CVE-2023-25668TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
39Monitor
CVE-2023-25664TensorFlow vulnerable to Heap Buffer Overflow in AvgPoolGrad
39Monitor
CVE-2022-41900FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow
39Monitor

Published before and after this one in the same product

← EarlierCVE-2020-26269Dec 10, 2020 · Heap out of bounds read in filesystem glob matching in TensorFlow
30Monitor
← EarlierCVE-2020-26270Dec 10, 2020 · CHECK-fail in LSTM with zero-length input in TensorFlow
13Monitor
Later →CVE-2021-29554May 14, 2021 · Division by 0 in `DenseCountSparseOutput`
22Monitor

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
PyPI:tensorflow	2.3.3	Package registry (OSV)
PyPI:tensorflow	2.4.2	Package registry (OSV)
PyPI:tensorflow-cpu	2.3.3	Package registry (OSV)
PyPI:tensorflow-cpu	2.4.2	Package registry (OSV)
PyPI:tensorflow-gpu	2.3.3	Package registry (OSV)
PyPI:tensorflow-gpu	2.4.2	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.

Patch and commit links

Commit, PR and diff links among the references. A starting point for patch-diffing and variant hunting; fixes, not exploits.

tensorflow/tensorflowcommit eebb96c

National notice (Türkiye Cybersecurity Directorate / USOM)

Official security notices citing this record; remediation advice is on the agency's page.

TR-21-0701 · Sep 3, 2021(IBM Güvenlik Bülteni Yayınladı)

All national notices →

Not on record for this CVE: EPSS history · researcher credit · variant or chain candidate · public bounty program.

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-120 · Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')

CVSS vector

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

nvd-primary

Root cause

When data is copied, the source length is not compared with the size of the destination buffer. Excess data overwrites adjacent memory.

The bug in code

The whole CWE-120 class

A representative example of this vulnerability class. Not the vendor's source code; it shows the faulty pattern and its fix.

Vulnerable

1char buf[256];
2memcpy(buf, pkt->data, pkt->len);

Fixed

1char buf[256];
2if (pkt->len > sizeof(buf)) {
3  return -EINVAL;
4}
5memcpy(buf, pkt->data, pkt->len);

Attack context

MITRE CAPEC attack patterns and ATT&CK techniques for this weakness class (CWE). A starting point for detection rules and threat hunting.

Attack patterns (CAPEC)

ATT&CK techniques

—

Change log (1)

Fix✗ → ✓Sep 28, 2026, 10:45 PM UTC

For records you follow, these changes also arrive as notifications. →

References

github.com/tensorflow/tensorflow/commit/eebb96c2830d48597d055d247c0e9aebaea94cd5

Vendor advisories and official records. Exploit/PoC links are deliberately left out.

All records