CVE-2021-29518
Session operations in eager mode lead to null pointer dereferences
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
Attack profile
How easy it is to exploit
- Attack vector
- Local
- Complexity
- High
- Privileges needed
- Low
- User interaction
- None
What an attacker can affect
- Confidentiality
- None
- Integrity
- None
- Availability
- Low
Exploit likelihood
What each source reports
CVE List Score used
2.5
Session operations in eager mode lead to null pointer dereferences
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
CVE-2021-29518- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
EUVDEUVD-2021-0259
2.5
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
EUVD-2021-0259- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-62gx-355r-9fhg
2.0
Session operations in eager mode lead to null pointer dereferences
Impact
In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference:
import tensorflow as tf
tf.raw_ops.GetSessionTensor(handle=['\x12\x1a\x07'],dtype=4)
import tensorflow as tf
tf.raw_ops.DeleteSessionTensor(handle=['\x12\x1a\x07'])
The implementation dereferences the session state pointer without checking if it is valid:
OP_REQUIRES_OK(ctx, ctx->session_state()->GetTensor(name, &val));
Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior.
Patches
We have patched the issue in GitHub commit ff70c47a396ef1e3cb73c90513da4f5cb71bebba.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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 vulnerability has been reported by members of the Aivul Team from Qihoo 360.
- Record
GHSA-62gx-355r-9fhg- CVSS 4.0
- 2.0 Low
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N - CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
NVD
2.5
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
CVE-2021-29518- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - CVSS 3.1
- 7.8 High
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H - CVSS 2.0
- 4.6 Medium
AV:L/AC:L/Au:N/C:P/I:P/A:P - Weakness
- CWE-476
- Updated
- 2026-11-02
OSV
7.8
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
CVE-2021-29518- CVSS 3.1
- 7.8 High
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H - Updated
- 2026-11-02
OSVGHSA-62gx-355r-9fhg
2.0
Session operations in eager mode lead to null pointer dereferences
Impact
In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference:
import tensorflow as tf
tf.raw_ops.GetSessionTensor(handle=['\x12\x1a\x07'],dtype=4)
import tensorflow as tf
tf.raw_ops.DeleteSessionTensor(handle=['\x12\x1a\x07'])
The implementation dereferences the session state pointer without checking if it is valid:
OP_REQUIRES_OK(ctx, ctx->session_state()->GetTensor(name, &val));
Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior.
Patches
We have patched the issue in GitHub commit ff70c47a396ef1e3cb73c90513da4f5cb71bebba.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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 vulnerability has been reported by members of the Aivul Team from Qihoo 360.
- Record
GHSA-62gx-355r-9fhg- CVSS 4.0
- 2.0 Low
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N - CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
Show 4 moreShow less
OSVBIT-tensorflow-2021-29518 No score
Session operations in eager mode lead to null pointer dereferences
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
BIT-tensorflow-2021-29518- Updated
- 2026-11-02
OSVPYSEC-2021-155 No score
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
PYSEC-2021-155- Updated
- 2026-11-02
OSVPYSEC-2021-446 No score
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
PYSEC-2021-446- Updated
- 2026-11-02
OSVPYSEC-2021-644 No score
TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, ctx->session_state() is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit 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.
- Record
PYSEC-2021-644- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.1.4 | 2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
Show 18 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflowBitnami |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2 | 2.1.42.2.32.3.32.4.2 |
tensorflowPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflowPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 0.12.00.12.0rc00.12.0rc10.12.11.0.0 Show 45 moreShow less1.0.11.1.01.1.0rc01.1.0rc11.1.0rc21.10.01.10.0rc01.10.0rc11.10.11.11.01.11.0rc01.11.0rc11.11.0rc21.12.01.12.0rc01.12.0rc11.12.0rc21.12.21.12.31.13.0rc01.13.0rc11.13.0rc21.13.11.13.21.14.01.14.0rc01.14.0rc11.15.01.15.0rc01.15.0rc11.15.0rc21.15.0rc31.15.21.15.31.15.41.15.51.2.01.2.0rc01.2.0rc11.2.0rc21.2.11.3.01.3.0rc01.3.0rc11.3.0rc2 |
2.1.42.2.32.3.32.4.2 |
tensorflow-cpuPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 5 moreShow less2.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
tensorflow-gpuPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 40 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
History
| Recorded | Changed | Sources |
|---|---|---|
| aliases | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2021-29518 is a low vulnerability (CVSS 2.5) in Google Tensorflow, published May 14, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.20%, the 10th percentile. Fixed in tensorflow 2.1.4.
References
github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg
github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba
nvd.nist.gov/vuln/detail/CVE-2021-29518
github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-446.yaml
github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-644.yaml
github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-155.yaml
github.com/advisories/GHSA-62gx-355r-9fhg
Left out here: 45 versions. The JSON record has them.