CVE-2021-41206
📋 TL;DR
TensorFlow is vulnerable to shape validation flaws in multiple operations, allowing attackers to trigger undefined behavior including crashes or potential memory corruption. This affects all users running vulnerable TensorFlow versions in applications that process untrusted input. The vulnerability was discovered internally via tooling rather than external exploitation.
💻 Affected Systems
- TensorFlow
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Memory corruption leading to arbitrary code execution or data leakage through heap manipulation.
Likely Case
Application crashes (segfaults or CHECK-fail) causing denial of service.
If Mitigated
Limited impact with proper input validation and sandboxing of TensorFlow operations.
🎯 Exploit Status
No public exploit available. Exploitation requires understanding of specific TensorFlow operations and crafting malicious tensor shapes. The vulnerability was discovered via internal tooling rather than external reports.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: TensorFlow 2.7.0, 2.6.1, 2.5.2, 2.4.4
Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww
Restart Required: Yes
Instructions:
1. Identify your TensorFlow version. 2. Upgrade to patched version: pip install tensorflow==2.7.0 (or appropriate version). 3. Restart all services using TensorFlow. 4. Test ML models to ensure compatibility.
🔧 Temporary Workarounds
Input validation wrapper
allImplement custom validation for tensor shapes before passing to vulnerable operations
# Python example: Validate tensor dimensions before use
import tensorflow as tf
def safe_operation(tensor, expected_shape):
if tensor.shape != expected_shape:
raise ValueError('Invalid tensor shape')
# Proceed with operation
🧯 If You Can't Patch
- Isolate TensorFlow operations in sandboxed environments with limited privileges
- Implement strict input validation and sanitization for all tensor data from untrusted sources
🔍 How to Verify
Check if Vulnerable:
Check TensorFlow version: python -c 'import tensorflow as tf; print(tf.__version__)'Check Version:
python -c 'import tensorflow as tf; print(tf.__version__)'Verify Fix Applied:
Verify version is 2.7.0, 2.6.1, 2.5.2, or 2.4.4: python -c 'import tensorflow as tf; print(tf.__version__)'📡 Detection & Monitoring
Log Indicators:
- Segmentation fault logs
- TensorFlow CHECK-failure messages
- Unexpected process crashes in ML services
Network Indicators:
- Increased error rates in ML API endpoints
- Unusual patterns of tensor shape requests
SIEM Query:
process.name:tensorflow AND (event.type:crash OR error.message:*segfault* OR error.message:*CHECK*)🔗 References
- https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4
- https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07
- https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d
- https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a
- https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261
- https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69
- https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4
- https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07
- https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d
- https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a
- https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261
- https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69
