# CVE-2021-37647: Null pointer dereference in `SparseTensorSliceDataset` in TensorFlow > An attacker can cause a denial of service in TensorFlow by providing invalid arguments to SparseTensorSliceDataset, triggering a null pointer dereference. - **Severity:** High 7.7 (`CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H`) - **Exploited in the wild:** Not known - **Login needed:** Not needed - **Attackable:** Local or same network only - **Victim action needed:** Not needed - **Fix available:** Yes - **Published:** 12 Aug 2021 - **Updated:** 4 Aug 2024 - **Also known as:** BIT-tensorflow-2021-37647, GHSA-c5x2-p679-95wc, PYSEC-2021-269, PYSEC-2021-560, PYSEC-2021-758 ## What is CVE-2021-37647? CVE-2021-37647 is a high-severity vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim. ### Official description TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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. Weakness: CWE-476 (NULL Pointer Dereference) ## Which versions are affected by CVE-2021-37647? 22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product. | Package | Ecosystem | Affected | Fixed in | | --- | --- | --- | --- | | `tensorflow` | Bitnami | From 2.3.0 | 2.3.4, 2.4.3, 2.5.1 | | `tensorflow` | PyPI | All versions | 2.3.4 | | `tensorflow` | PyPI | All versions | 2.3.4 | | `tensorflow` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow` | PyPI | From 2.5.0 | 2.5.1 | | `tensorflow` | PyPI | From 2.5.0 | 2.5.1 | | `tensorflow-cpu` | PyPI | All versions | 2.3.4 | | `tensorflow-cpu` | PyPI | All versions | 2.3.4 | | `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow-cpu` | PyPI | From 2.5.0 | 2.5.1 | | `tensorflow-cpu` | PyPI | From 2.5.0 | 2.5.1 | | `tensorflow-gpu` | PyPI | All versions | 2.3.4 | | `tensorflow-gpu` | PyPI | All versions | 2.3.4 | | `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.4, 2.4.3 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.3 | | `tensorflow-gpu` | PyPI | From 2.5.0 | 2.5.1 | | `tensorflow-gpu` | PyPI | From 2.5.0 | 2.5.1 | Products: Google Tensorflow. ## How do I fix CVE-2021-37647? Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3 or 2.5.1. ## Is CVE-2021-37647 being exploited? There is no known exploitation of CVE-2021-37647 in the wild and no public exploit code. ## Other vulnerabilities in Google Tensorflow - [CVE-2023-25668](https://insights.sbomify.com/CVE-2023-25668/): TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation (critical 9.8) - [CVE-2018-7575](https://insights.sbomify.com/CVE-2018-7575/): Integer Overflow or Wraparound in Google TensorFlow (critical 9.8) - [CVE-2021-37678](https://insights.sbomify.com/CVE-2021-37678/): Arbitrary code execution due to YAML deserialization (critical 9.3) - [CVE-2021-35958](https://insights.sbomify.com/CVE-2021-35958/): Path traversal in n/a (critical 9.1) - [CVE-2020-15202](https://insights.sbomify.com/CVE-2020-15202/): Integer truncation in Shard API usage (critical 9.0) ## Fix prompt for AI coding agents ```text Check this codebase for CVE-2021-37647 and fix it if it is affected. What it is: CVE-2021-37647 is a high-severity vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim. Exploitation: There is no known exploitation of CVE-2021-37647 in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (Bitnami): affected from 2.3.0; fixed in 2.3.4, 2.4.3, 2.5.1 - tensorflow (PyPI): affected all versions; fixed in 2.3.4 - tensorflow (PyPI): affected all versions; fixed in 2.3.4 - tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.3 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.3 - tensorflow (PyPI): affected from 2.5.0; fixed in 2.5.1 - tensorflow (PyPI): affected from 2.5.0; fixed in 2.5.1 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.3.4 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.3.4 - tensorflow-cpu (PyPI): affected from 2.3.0; fixed in 2.3.4, 2.4.3 - tensorflow-cpu (PyPI): affected from 2.4.0; fixed in 2.4.3 Task: 1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies. 2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it. 3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead. 4. Run the tests and summarise what changed and why. 5. If nothing in the project is affected, say so and change nothing. Reference: https://insights.sbomify.com/CVE-2021-37647/ (Markdown: https://insights.sbomify.com/CVE-2021-37647/index.md) ``` ## Sources - CVE record: https://www.cve.org/CVERecord?id=CVE-2021-37647 - NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-37647 - OSV: https://osv.dev/vulnerability/CVE-2021-37647 --- From sbomify Insights: https://insights.sbomify.com/CVE-2021-37647/ Summaries are generated and may contain mistakes; the official description above is the record.