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GHSA-63xm-rx5p-xvqr
No affected components available
Impact
The implementation of SparseFillEmptyRowsGrad uses a double indexing pattern:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269
It is possible for reverse_index_map(i) to be an index outside of bounds of grad_values, thus resulting in a heap buffer overflow.
Patches
We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
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 reported by members of the Aivul Team from Qihoo 360.
The vulnerability can be exploited over the network without needing physical access. It is difficult for an attacker to exploit this vulnerability and may require special conditions. An attacker needs basic access or low-level privileges. No user interaction is needed for the attacker to exploit this vulnerability. The vulnerability can affect other systems as well, not just the initial system. There is a high impact on the confidentiality of the information. There is a high impact on the integrity of the data. There is a high impact on the availability of the system.
Exploitation activity has been observed. Apply available patches or mitigations urgently.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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