Heap OOB and null pointer dereference in `RaggedTensorToTensor`
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2, 2.2.0rc0, and 3 more
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
Summary
TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.RaggedTensorToTensor`, an attacker can exploit an undefined behavior if input arguments are empty. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L356-L360) only checks that one of the tensors is not empty, but does not check for the other ones. There are multiple `DCHECK` validations to prevent heap OOB, but these are no-op in release builds, hence they don't prevent anything. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits 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.
Timeline
- CVE published
- Record last updated
Affected versions
- tensorflow tensorflow
fixed in 2.1.4; From 2.2.0 · fixed in 2.2.3; From 2.3.0 · fixed in 2.3.3; From 2.4.0 · fixed in 2.4.2
- tensorflow-gpuPyPI
fixed in 2.2.0rc0; From 2.2.0 · fixed in 2.3.0rc0; From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
fixed in 2.2.0rc0; From 2.2.0 · fixed in 2.3.0rc0; From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
fixed in 2.2.0rc0; From 2.2.0 · fixed in 2.3.0rc0; From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
fixed in 2.1.4
- tensorflowPyPI
From 2.2.0 · fixed in 2.2.3
- tensorflowPyPI
From 2.3.0 · fixed in 2.3.3
- tensorflowPyPI
From 2.4.0 · fixed in 2.4.2
- tensorflow-cpuPyPI
fixed in 2.1.4
- tensorflow-cpuPyPI
From 2.2.0 · fixed in 2.2.3
- tensorflow-cpuPyPI
From 2.3.0 · fixed in 2.3.3
- tensorflow-cpuPyPI
From 2.4.0 · fixed in 2.4.2
- tensorflow-gpuPyPI
fixed in 2.1.4
- tensorflow-gpuPyPI
From 2.2.0 · fixed in 2.2.3
- tensorflow-gpuPyPI
From 2.3.0 · fixed in 2.3.3
- tensorflow-gpuPyPI
From 2.4.0 · fixed in 2.4.2