Heap OOB in `UpperBound` and `LowerBound`
Medium5.5CVE-2021-37670 · Published Aug 25, 2021 · updated Jul 8, 2026
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.3.4 | 2.3.4 |
| >= 2.4.0, < 2.4.3 | 2.4.3 | |
| >= 2.5.0, < 2.5.1 | 2.5.1 |
Details and references
### Impact An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.UpperBound`: ```python import tensorflow as tf tf.raw_ops.UpperBound( sorted_input=[1,2,3], values=tf.constant(value=[[0,0,0],[1,1,1],[2,2,2]],dtype=tf.int64), out_type=tf.int64) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/searchsorted_op.cc#L85-L104) does not validate the rank of `sorted_input` argument: ```cc void Compute(OpKernelContext* ctx) override { const Tensor& sorted_inputs_t = ctx->input(0); // ... OP_REQUIRES(ctx, sorted_inputs_t.dim_size(0) == values_t.dim_size(0), Status(error::INVALID_ARGUMENT, "Leading dim_size of both tensors must match.")); // ... if (output_t->dtype() == DT_INT32) { OP_REQUIRES(ctx, FastBoundsCheck(sorted_inputs_t.dim_size(1), ...)); // ... } ``` As we access the first two dimensions of `sorted_inputs_t` tensor, it must have rank at least 2. A similar issue occurs in `tf.raw_ops.LowerBound`. ### Patches We have patched the issue in GitHub commit [42459e4273c2e47a3232cc16c4f4fff3b3a35c38](https://github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-125
- Also known as
- BIT-tensorflow-2021-37670, CVE-2021-37670, PYSEC-2021-292, PYSEC-2021-583, PYSEC-2021-781
- github.com/tensorflow/tensorflow/security/advisories/GHSA-9697-98pf-4rw7
- nvd.nist.gov/vuln/detail/CVE-2021-37670
- github.com/tensorflow/tensorflow/commit/42459e4273c2e47a3232cc16c4f4fff3b3a35c38
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-583.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-781.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-292.yaml
- github.com/tensorflow/tensorflow
More TensorFlow advisories
All TensorFlow| Date | Advisory | Severity | Fixed in |
|---|---|---|---|
| Aug 252021 | Segfault on strings tensors with mistmatched dimensions, due to Go code CVE-2021-37692Medium5.5fixed in 2.5.1 | Medium5.5 | 2.5.1 |
| Aug 252021 | FPE in LSH in TFLite CVE-2021-37691Medium5.5fixed in 2.3.4, 2.4.3, 2.5.1 | Medium5.5 | 2.3.4, 2.4.3, 2.5.1 |
| Aug 252021 | Use after free and segfault in shape inference functions CVE-2021-37690Medium6.6fixed in 2.3.4, 2.4.3, 2.5.1 | Medium6.6 | 2.3.4, 2.4.3, 2.5.1 |
| Aug 252021 | Null pointer dereference in TFLite MLIR optimizations CVE-2021-37689High7.8fixed in 2.3.4, 2.4.3, 2.5.1 | High7.8 | 2.3.4, 2.4.3, 2.5.1 |
| Aug 252021 | Null pointer dereference in TFLite CVE-2021-37688High7.8fixed in 2.3.4, 2.4.3, 2.5.1 | High7.8 | 2.3.4, 2.4.3, 2.5.1 |
| Aug 252021 | Infinite loop in TFLite CVE-2021-37686Medium5.5fixed in 2.6.0rc2 | Medium5.5 | 2.6.0rc2 |