Heap OOB in nested `tf.map_fn` with `RaggedTensor`s in TensorFlow
- 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- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean?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 2.5.1, 2.4.3, 2.3.4
- 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. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The implementation does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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.
Timeline
- CVE published
- Record last updated
Affected versions
- tensorflow tensorflow
From 2.5.0 · fixed in 2.5.1; From 2.4.0 · fixed in 2.4.3; fixed in 2.3.4
- tensorflow-gpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
fixed in 2.3.4
- tensorflowPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-cpuPyPI
fixed in 2.3.4
- tensorflow-cpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-gpuPyPI
fixed in 2.3.4
- tensorflow-gpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-gpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflowPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3