# CVE-2021-29612: Heap buffer overflow in `BandedTriangularSolve` > An attacker can trigger a heap buffer overflow in TensorFlow's BandedTriangularSolve operation due to missing input validation, potentially leading to code execution or crashes. - **Severity:** Low 3.6 (`CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:L`) - **Exploited in the wild:** Not known - **Login needed:** Any signed-in user - **Attackable:** Local or same network only - **Victim action needed:** Not needed - **Fix available:** Yes - **Published:** 14 May 2021 - **Updated:** 3 Aug 2024 - **Also known as:** BIT-tensorflow-2021-29612, GHSA-2xgj-xhgf-ggjv, PYSEC-2021-249, PYSEC-2021-540, PYSEC-2021-738 ## What is CVE-2021-29612? CVE-2021-29612 is a low-severity memory corruption vulnerability in Google Tensorflow, published on 14 May 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. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. 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. Weakness: CWE-787 (Out-of-bounds Write), CWE-120 (Buffer Copy without Checking Size of Input) ## Which versions are affected by CVE-2021-29612? 28 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 | All versions | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | | `tensorflow` | PyPI | All versions | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | | `tensorflow` | PyPI | All versions | 2.1.4 | | `tensorflow` | PyPI | All versions | 2.1.4 | | `tensorflow` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-cpu` | PyPI | All versions | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | | `tensorflow-cpu` | PyPI | All versions | 2.1.4 | | `tensorflow-cpu` | PyPI | All versions | 2.1.4 | | `tensorflow-cpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-cpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-gpu` | PyPI | All versions | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | | `tensorflow-gpu` | PyPI | All versions | 2.1.4 | | `tensorflow-gpu` | PyPI | All versions | 2.1.4 | | `tensorflow-gpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-gpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.2 | Products: Google Tensorflow. ## How do I fix CVE-2021-29612? Upgrade tensorflow to a fixed version for your release line: 2.1.4, 2.2.3, 2.3.3 or 2.4.2. ## Is CVE-2021-29612 being exploited? There is no known exploitation of CVE-2021-29612 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-2021-29612 and fix it if it is affected. What it is: CVE-2021-29612 is a low-severity memory corruption vulnerability in Google Tensorflow, published on 14 May 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-2021-29612 in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (Bitnami): affected all versions; fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 - tensorflow (PyPI): affected all versions; fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 - tensorflow (PyPI): affected all versions; fixed in 2.1.4 - tensorflow (PyPI): affected all versions; fixed in 2.1.4 - tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3 - tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3 - tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3 - tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.1.4 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-2021-29612/ (Markdown: https://insights.sbomify.com/CVE-2021-29612/index.md) ``` ## Sources - CVE record: https://www.cve.org/CVERecord?id=CVE-2021-29612 - NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-29612 - OSV: https://osv.dev/vulnerability/CVE-2021-29612 --- From sbomify Insights: https://insights.sbomify.com/CVE-2021-29612/ Summaries are generated and may contain mistakes; the official description above is the record.