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CVE-2021-41208

Incomplete validation in boosted trees code

8.8 HighFix available

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
Low
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
High

Exploit likelihood

0.17%Down 0.6 points since Nov 6, 2021
90%50%10%1%

What each source reports

CVE List Score used8.8

Incomplete validation in boosted trees code

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
CVE-2021-41208
CVSS 3.1
8.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-476, CWE-824
Updated
2026-11-02
EUVDEUVD-2021-04308.8

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
EUVD-2021-0430
CVSS 3.1
8.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Updated
2026-11-03
GitHub AdvisoriesGHSA-57wx-m983-2f889.3

Incomplete validation in boosted trees code

Impact

The code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call.

Note: Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. Instead, please use the downstream TensorFlow Decision Forests project which is newer and supports more features. We will deprecate TensorFlow's boosted trees APIs in subsequent releases.

Patches

We have patched the issue in GitHub commit 5c8c9a8bfe750f9743d0c859bae112060b216f5c.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Record
GHSA-57wx-m983-2f88
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-476, CWE-824
Updated
2026-11-02
NVD8.8

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
CVE-2021-41208
CVSS 3.1
8.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
CVSS 3.1
7.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVSS 2.0
4.6 MediumAV:L/AC:L/Au:N/C:P/I:P/A:P
Weakness
CWE-476, CWE-824
Updated
2026-11-02
OSV7.8

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
CVE-2021-41208
CVSS 3.1
7.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Updated
2026-11-02
OSVGHSA-57wx-m983-2f889.3

Incomplete validation in boosted trees code

Impact

The code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call.

Note: Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. Instead, please use the downstream TensorFlow Decision Forests project which is newer and supports more features. We will deprecate TensorFlow's boosted trees APIs in subsequent releases.

Patches

We have patched the issue in GitHub commit 5c8c9a8bfe750f9743d0c859bae112060b216f5c.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Record
GHSA-57wx-m983-2f88
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-476, CWE-824
Updated
2026-11-02
Show 5 moreShow less
OSVBIT-tensorflow-2021-41208No score

Incomplete validation in boosted trees code

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
BIT-tensorflow-2021-41208
Updated
2026-11-02
OSVopenSUSE-SU-2024:12116-1No score

tensorflow-lite-2.9.1-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12116-1
Updated
2026-11-02
OSVPYSEC-2021-400No score

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
PYSEC-2021-400
Updated
2026-11-02
OSVPYSEC-2021-617No score

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
PYSEC-2021-617
Updated
2026-11-02
OSVPYSEC-2021-815No score

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing nullptrs or via CHECK-failures) as well as abuse undefined behavior (binding references to nullptrs). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Record
PYSEC-2021-815
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
2.6.0 up to 2.6.1
2.6.1
tensorflow
PyPI
2.5.0 up to 2.5.2
2.5.2
tensorflow
PyPI
before 2.4.4
2.4.4
tensorflow-cpu
PyPI
2.6.0 up to 2.6.1
2.6.1
tensorflow-cpu
PyPI
2.5.0 up to 2.5.2
2.5.2
tensorflow-cpu
PyPI
before 2.4.4
2.4.4
tensorflow-gpu
PyPI
2.6.0 up to 2.6.1
2.6.1
tensorflow-gpu
PyPI
2.5.0 up to 2.5.2
2.5.2
tensorflow-gpu
PyPI
before 2.4.4
2.4.4
tensorflow
Bitnami
2.4.0 up to 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1
2.4.42.5.22.6.1
Show 9 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
2.5.0 up to 2.5.2, plus listed versions
2.5.1
2.5.2
tensorflow
PyPI
before 2.4.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.4.4
tensorflow-cpu
PyPI
2.5.0 up to 2.5.2, plus listed versions
2.5.1
2.5.2
tensorflow-cpu
PyPI
before 2.4.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 14 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.3
2.4.4
tensorflow-gpu
PyPI
2.5.0 up to 2.5.2, plus listed versions
2.5.1
2.5.2
tensorflow-gpu
PyPI
before 2.4.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.4.4
tensorflow
PyPI
before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.0rc02.2.0rc12.2.0rc22.2.0rc32.2.0rc42.2.12.2.22.2.3
2.4.42.5.22.6.12.7.0
tensorflow-cpu
PyPI
before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 16 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.5.12.7.0rc1
2.4.42.5.22.6.12.7.0
tensorflow-gpu
PyPI
before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.4.42.5.22.6.12.7.0

History

History
RecordedChangedSources
facts
aliasesEUVD
first indexedCVE List, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2021-41208 is a high vulnerability (CVSS 8.8) in Google Tensorflow, published November 5, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.17%, the 6th percentile. Fixed in tensorflow 2.6.1.

References

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Left out here: 33 versions. The JSON record has them.

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