Unknown
CVE-2021-37663
CVE ID
AttackerKB requires a CVE ID in order to pull vulnerability data and references from the CVE list and the National Vulnerability Database. If available, please supply below:
Add References:
CVE-2021-37663
MITRE ATT&CK
Collection
Command and Control
Credential Access
Defense Evasion
Discovery
Execution
Exfiltration
Impact
Initial Access
Lateral Movement
Persistence
Privilege Escalation
Topic Tags
Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in tf.raw_ops.QuantizeV2, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The implementation has some validation but does not check that min_range and max_range both have the same non-zero number of elements. If axis is provided (i.e., not -1), then validation should check that it is a value in range for the rank of input tensor and then the lengths of min_range and max_range inputs match the axis dimension of the input tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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.
Add Assessment
No one has assessed this topic. Be the first to add your voice to the community.
CVSS V3 Severity and Metrics
General Information
References
Additional Info
Technical Analysis
Report as Emergent Threat Response
Report as Zero-day Exploit
Report as Exploited in the Wild
CVE ID
AttackerKB requires a CVE ID in order to pull vulnerability data and references from the CVE list and the National Vulnerability Database. If available, please supply below:
