c06650b697
GitHub does not insert automatic links and smart code snippets in these files, so we have to do it manually. PiperOrigin-RevId: 333195707 Change-Id: I1e2fed8ff207fbfce6eb8fb2b910d12bcab4100c
2.2 KiB
TFSA-2020-007: Null pointer dereference in TFLite
CVE Number
CVE-2020-15209
Impact
A crafted TFLite model can force a node to have as input a tensor backed by a
nullptr buffer. This can be achieved by changing a buffer index in the
flatbuffer serialization to convert a read-only tensor to a read-write one. The
runtime assumes that these buffers are written to before a possible read, hence
they are initialized with
nullptr:
TfLiteTensorReset(type, name, ConvertArrayToTfLiteIntArray(rank, dims),
GetLegacyQuantization(quantization),
/*buffer=*/nullptr, required_bytes, allocation_type,
nullptr, is_variable, &tensor);
However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference.
Vulnerable Versions
TensorFlow 1.15.0, 1.15.1, 1.15.2, 1.15.3, 2.0.0, 2.0.1, 2.0.2, 2.1.0, 2.1.1, 2.2.0, 2.3.0.
Patches
We have patched the issue in 0b5662bc and will release patch releases for all versions between 1.15 and 2.3.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Workarounds
A potential workaround would be to add a custom Verifier to the model loading
code to ensure that no operator reuses tensors as both inputs and outputs. Care
should be taken to check all types of inputs (i.e., constant or variable tensors
as well as optional tensors).
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been discovered by members of the Aivul Team and is also discoverable through a variant analysis of another vulnerability reported by members of the Aivul Team from Qihoo 360.