Heap OOB and null pointer dereference in RaggedTensorToTensor

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS 4.0

5.8 · CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N · score source

EPSS

• CVE-2021-29608: 0.23% estimated exploitation activity in the next 30 days; percentile 14.34 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.

As published by the source; long descriptions are shortened.

Impact Due to lack of validation in tf.rawops.RaggedTensorToTensor, an attacker can exploit an undefined behavior if input arguments are empty: The implementation only checks that one of the tensors is not empty, but does not check for the other ones. There are multiple DCHECK validations to prevent heap OOB, but these are no-op in release builds, hence they don't prevent anything. Patches We have patched the issue in GitHub commit b761c9b652af2107cfbc33efd19be0ce41daa33e followed by GitHub commit f94ef358bb3e91d517446454edff6535bcfe8e4a and GitHub commit c4d7afb6a5986b04505aca4466ae1951686c80f6. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This…

Published by the source

21 May 2021, 14:28 UTC

Last modified by the source

8 Jul 2026, 06:00 UTC

Source last checked

26 Oct 2026, 13:26 UTC

1. Revision 3 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-rgvq-pcvf-hx75

2. Revision 2 · amended · 25 Oct 2026

   Reviewed OSV alias/range/CVSS4 correction; package source scopes and original publication preserved. No customer finding resolved.

3. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-rgvq-pcvf-hx75

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# Patch Next advisory brief: CVE-2021-29608

Advisory: Heap OOB and null pointer dereference in `RaggedTensorToTensor`
IDs: CVE-2021-29608, GHSA-rgvq-pcvf-hx75
Record: https://patchnext.com/advisories/cve-2021-29608 (revision 3, source checked 26 Oct 2026, 13:26 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: Medium (CVSS 5.8)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: tensorflow 2.4.2, 2.3.3, 2.2.3, 2.1.4; tensorflow-gpu 2.4.2, 2.3.3, 2.2.3, 2.1.4; tensorflow-cpu 2.4.2, 2.3.3, 2.2.3, 2.1.4. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI tensorflow: affected < 2.1.4; >= 2.2.0, < 2.2.3; >= 2.3.0, < 2.3.3; >= 2.4.0, < 2.4.2; fixed in 2.4.2, 2.3.3, 2.2.3, 2.1.4
- PyPI tensorflow-gpu: affected < 2.1.4; >= 2.2.0, < 2.2.3; >= 2.3.0, < 2.3.3; >= 2.4.0, < 2.4.2; fixed in 2.4.2, 2.3.3, 2.2.3, 2.1.4
- PyPI tensorflow-cpu: affected < 2.1.4; >= 2.2.0, < 2.2.3; >= 2.3.0, < 2.3.3; >= 2.4.0, < 2.4.2; fixed in 2.4.2, 2.3.3, 2.2.3, 2.1.4

## Suggested inspection (read-only)
- `python -m pip show tensorflow`: prints the installed version. Run with the environment that serves production active.
- `python -m pip show tensorflow-gpu`: prints the installed version. Run with the environment that serves production active.
- `python -m pip show tensorflow-cpu`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on tensorflow, tensorflow-gpu, tensorflow-cpu.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://osv.dev/vulnerability/GHSA-rgvq-pcvf-hx75 (OSV record GHSA-rgvq-pcvf-hx75 lists affected ranges: PyPI tensorflow >=0 =2.2.0 =2.3.0 =2.4.0 =0 =2.2.0 =2.3.0 =2.4.0 =0 =2.2.0 =2.3.0 =2.4.0 <2.4.2 (fixed))
- Verified: https://github.com/advisories/GHSA-rgvq-pcvf-hx75 (GitHub-reviewed advisory GHSA-rgvq-pcvf-hx75 lists affected ranges: PyPI tensorflow >=0 =2.2.0 =2.3.0 =2.4.0 =0 =2.2.0 =2.3.0 =2.4.0 =0 =2.2.0 =2.3.0 =2.4.0 <2.4.2)

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