CVE-2021-37658
📋 TL;DR
This vulnerability in TensorFlow allows an attacker to cause undefined behavior by binding a reference to a null pointer in MatrixSetDiagV* operations. Attackers can exploit incomplete validation of the 'k' tensor parameter to trigger memory corruption. All TensorFlow users running affected versions are potentially vulnerable.
💻 Affected Systems
- TensorFlow
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Remote code execution leading to complete system compromise, data theft, or denial of service through memory corruption.
Likely Case
Application crash or denial of service due to null pointer dereference, potentially leading to availability issues.
If Mitigated
No impact if patched or workarounds applied; otherwise, limited to denial of service in controlled environments.
🎯 Exploit Status
Exploitation requires the ability to call vulnerable TensorFlow operations with crafted inputs. No public exploit code is known at this time.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: TensorFlow 2.6.0, 2.5.1, 2.4.3, and 2.3.4
Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2
Restart Required: No
Instructions:
1. Update TensorFlow to patched version: pip install --upgrade tensorflow==2.6.0 (or appropriate version). 2. Verify installation with: python -c 'import tensorflow as tf; print(tf.__version__)'. 3. Restart any running TensorFlow applications.
🔧 Temporary Workarounds
Input Validation
allAdd validation to ensure 'k' tensor parameter has at least one element before passing to MatrixSetDiagV* operations.
# Python code to validate 'k' tensor
if k is not None and k.shape.num_elements() == 0:
raise ValueError('k tensor must not be empty')
🧯 If You Can't Patch
- Disable or restrict access to MatrixSetDiagV* operations in your application.
- Implement strict input validation for all TensorFlow operations to reject empty tensors.
🔍 How to Verify
Check if Vulnerable:
Check TensorFlow version: python -c 'import tensorflow as tf; print(tf.__version__)'. If version is between 2.3.0-2.3.3, 2.4.0-2.4.2, 2.5.0, or 2.6.0-rc, you are vulnerable.Check Version:
python -c 'import tensorflow as tf; print(tf.__version__)'Verify Fix Applied:
After patching, verify version is 2.6.0, 2.5.1, 2.4.3, or 2.3.4. Test MatrixSetDiagV* operations with empty 'k' tensor to ensure proper error handling.📡 Detection & Monitoring
Log Indicators:
- Application crashes or segmentation faults in TensorFlow processes
- Error logs containing 'MatrixSetDiag' or null pointer references
Network Indicators:
- Unusual API calls to TensorFlow endpoints with malformed tensor data
SIEM Query:
source="tensorflow" AND (error="segmentation fault" OR error="null pointer" OR "MatrixSetDiag")🔗 References
- https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2
- https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2
