CVE-2022-21736
📋 TL;DR
This vulnerability in TensorFlow's SparseTensorSliceDataset allows attackers to cause a null pointer dereference by providing invalid input arguments that bypass validation checks. This affects all systems using vulnerable TensorFlow versions for machine learning workloads, potentially leading to crashes or arbitrary code execution.
💻 Affected Systems
- TensorFlow
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Remote code execution leading to complete system compromise if combined with other vulnerabilities or memory corruption techniques.
Likely Case
Application crash (denial of service) when processing malicious sparse tensor data.
If Mitigated
No impact if proper input validation is implemented or vulnerable code is not used.
🎯 Exploit Status
Exploitation requires crafting specific sparse tensor inputs to trigger the null pointer dereference. No public exploit code has been released.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: TensorFlow 2.8.0, 2.7.1, 2.6.3, 2.5.3
Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9
Restart Required: No
Instructions:
1. Update TensorFlow to patched version: pip install --upgrade tensorflow==2.8.0 (or appropriate version). 2. Verify update with: python -c 'import tensorflow as tf; print(tf.__version__)'. 3. Test SparseTensorSliceDataset functionality.
🔧 Temporary Workarounds
Input validation wrapper
allImplement custom validation for SparseTensorSliceDataset inputs before passing to TensorFlow
# Python example: Validate indices, values, dense_shape before calling SparseTensorSliceDataset
# Ensure all inputs are non-null and satisfy sparse tensor constraints
Disable vulnerable functionality
allAvoid using SparseTensorSliceDataset in production code until patched
# Replace SparseTensorSliceDataset with alternative sparse tensor processing methods
# Comment out or remove calls to vulnerable function
🧯 If You Can't Patch
- Implement strict input validation and sanitization for all sparse tensor data
- Isolate TensorFlow workloads in containers with minimal privileges
🔍 How to Verify
Check if Vulnerable:
Check TensorFlow version: python -c 'import tensorflow as tf; print(tf.__version__)'. Versions 2.5.0-2.7.0 are vulnerable.Check Version:
python -c 'import tensorflow as tf; print(tf.__version__)'Verify Fix Applied:
Verify version is 2.8.0, 2.7.1, 2.6.3, or 2.5.3. Test SparseTensorSliceDataset with edge case inputs.📡 Detection & Monitoring
Log Indicators:
- Segmentation fault logs
- TensorFlow crash reports
- Null pointer exception in application logs
Network Indicators:
- Unusual spikes in ML API failures
- Increased error rates in TensorFlow services
SIEM Query:
source="tensorflow" AND ("segmentation fault" OR "null pointer" OR "SparseTensorSliceDataset")🔗 References
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292
- https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292
- https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9
