Unknown
CVE-2021-37669
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-2021-37669
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 an attacker can cause denial of service in applications serving models using tf.raw_ops.NonMaxSuppressionV5 by triggering a division by 0. The implementation uses a user controlled argument to resize a std::vector. However, as std::vector::resize takes the size argument as a size_t and output_size is an int, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in CombinedNonMaxSuppression. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. 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
Vendors
Products
- tensorflow,
- tensorflow 2.5.0,
- tensorflow 2.6.0
References
Additional Info
Technical Analysis
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:
