CVE-2023-25676
📋 TL;DR
This vulnerability in TensorFlow allows a denial of service attack through a null pointer dereference in the ParallelConcat operation when using XLA compilation. It affects users running TensorFlow versions prior to 2.12.0 and 2.11.1 with XLA enabled. The issue causes segmentation faults when processing malformed input tensors.
💻 Affected Systems
- TensorFlow
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Complete service disruption through segmentation fault crashes, potentially leading to availability issues in production ML systems.
Likely Case
Denial of service through application crashes when processing specially crafted input with XLA compilation enabled.
If Mitigated
No impact if XLA is disabled or proper input validation is implemented before reaching vulnerable code paths.
🎯 Exploit Status
Exploitation requires ability to call tf.raw_ops.ParallelConcat with malformed shape parameter and XLA enabled.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: TensorFlow 2.12.0 or 2.11.1
Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6wfh-89q8-44jq
Restart Required: Yes
Instructions:
1. Upgrade TensorFlow to version 2.12.0 or 2.11.1 using pip: 'pip install --upgrade tensorflow==2.12.0' or 'pip install --upgrade tensorflow==2.11.1'. 2. Restart all TensorFlow applications and services. 3. Verify the update was successful.
🔧 Temporary Workarounds
Disable XLA compilation
allPrevent exploitation by disabling XLA compilation which is required for the vulnerability to be triggered
export TF_XLA_FLAGS="--tf_xla_auto_jit=0"
os.environ['TF_XLA_FLAGS'] = '--tf_xla_auto_jit=0'
Input validation for ParallelConcat
allAdd validation to ensure shape parameter rank is greater than zero before calling ParallelConcat
# Python code to validate shape before use
if shape is not None and len(shape) > 0:
# Proceed with ParallelConcat
else:
# Handle invalid shape appropriately
🧯 If You Can't Patch
- Disable XLA compilation globally in your TensorFlow environment
- Implement strict input validation for all calls to tf.raw_ops.ParallelConcat operations
🔍 How to Verify
Check if Vulnerable:
Check TensorFlow version and verify if XLA is enabled in your configurationCheck Version:
python -c "import tensorflow as tf; print(tf.__version__)"Verify Fix Applied:
Verify TensorFlow version is 2.12.0 or 2.11.1 and test ParallelConcat with edge cases📡 Detection & Monitoring
Log Indicators:
- Segmentation fault errors in application logs
- TensorFlow crash reports mentioning ParallelConcat
- XLA compilation errors with null pointer references
Network Indicators:
- Unusual spikes in service failures when processing ML inference requests
SIEM Query:
source="*tensorflow*" AND ("segmentation fault" OR "null pointer" OR "ParallelConcat")🔗 References
- https://github.com/tensorflow/tensorflow/commit/da66bc6d5ff466aee084f9e7397980a24890cd15
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6wfh-89q8-44jq
- https://github.com/tensorflow/tensorflow/commit/da66bc6d5ff466aee084f9e7397980a24890cd15
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6wfh-89q8-44jq
