CVE-2020-15214
📋 TL;DR
This vulnerability in TensorFlow Lite allows memory corruption when processing models with unsorted segment IDs in segment sum operations. It affects users running TensorFlow Lite versions before 2.2.1 or 2.3.1, potentially leading to crashes or remote code execution.
💻 Affected Systems
- TensorFlow Lite
📦 What is this software?
⚠️ Risk & Real-World Impact
Worst Case
Remote code execution leading to complete system compromise if an attacker can supply malicious models and leverage the memory corruption as a write gadget.
Likely Case
Application crashes (segmentation faults) causing denial of service when processing malformed models.
If Mitigated
No impact if patched versions are used or if custom validation ensures segment IDs are sorted before processing.
🎯 Exploit Status
Exploitation requires crafting or modifying models with unsorted segment IDs. The advisory mentions it could provide a write gadget for memory corruption exploits, but no public exploits have been documented.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: TensorFlow 2.2.1 or 2.3.1
Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm
Restart Required: No
Instructions:
1. Upgrade TensorFlow to version 2.2.1 or 2.3.1 or later. 2. Update dependencies in your project to use the patched version. 3. Rebuild and redeploy applications using TensorFlow Lite.
🔧 Temporary Workarounds
Add custom segment ID validation
allImplement a custom verifier to check that segment IDs are sorted before processing models, but only works for statically stored segment IDs.
Implement validation in model loading code: verify segment_ids tensor is sorted in increasing order before passing to segment sum operations.
🧯 If You Can't Patch
- Implement runtime validation of segment IDs between inference steps if they are generated dynamically.
- Restrict model sources to trusted providers only and validate all incoming models before processing.
🔍 How to Verify
Check if Vulnerable:
Check TensorFlow version: if using TensorFlow Lite and version is below 2.2.1 or 2.3.1, you are vulnerable.Check Version:
python -c "import tensorflow as tf; print(tf.__version__)"Verify Fix Applied:
Verify TensorFlow version is 2.2.1, 2.3.1, or later after upgrade.📡 Detection & Monitoring
Log Indicators:
- Segmentation fault logs from TensorFlow Lite processes
- Application crashes when processing models with segment sum operations
Network Indicators:
- Unusual model uploads or requests to model processing endpoints
SIEM Query:
search for 'segmentation fault' AND 'tensorflow' in application logs🔗 References
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm
