Know every vulnerabilitybefore it knows you.
DevGuard continuously monitors your dependencies and alerts you when CVEs like this one affect your stack — with real-time threat intelligence built for developers.
GHSA-g4h2-gqm3-c9wq
No affected components available
Impact
Calling tf.raw_ops.ImmutableConst with a dtype of tf.resource or tf.variant results in a segfault in the implementation as code assumes that the tensor contents are pure scalars.
>>> import tensorflow as tf
>>> tf.raw_ops.ImmutableConst(dtype=tf.resource, shape=[], memory_region_name="/tmp/test.txt")
...
Segmentation fault
Patches
We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Workarounds
If using tf.raw_ops.ImmutableConst in code, you can prevent the segfault by inserting a filter for the dtype argument.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
The vulnerability requires local access to the device to be exploited. 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 impact is confined to the system where the vulnerability exists. There is a low impact on the availability of the system.
Limited exploitation activity has been observed. Close monitoring and planned remediation are recommended.
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.
Browse More
Continuously monitor your dependencies and get alerted when vulnerabilities like this one affect your stack.
Checkout DevGuard