CVE-2021-33649
📋 TL;DR
CVE-2021-33649 is an out-of-bounds read vulnerability in MindSpore's Transpose operator that occurs when the perm parameter exceeds input shape bounds. This allows attackers to read heap memory beyond allocated buffers, potentially exposing sensitive information. Users of affected MindSpore versions are vulnerable when processing untrusted models.
💻 Affected Systems
- MindSpore
📦 What is this software?
Mindspore by Mindspore
Mindspore by Mindspore
⚠️ Risk & Real-World Impact
Worst Case
Information disclosure leading to memory content leakage, potentially exposing sensitive data like model weights, credentials, or other process memory.
Likely Case
Application crash or denial of service due to invalid memory access, with possible limited information disclosure.
If Mitigated
No impact if proper input validation is implemented or vulnerable versions are not used.
🎯 Exploit Status
Exploitation requires crafting malicious models with specific Transpose configurations. No known public exploits.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: MindSpore 1.3.0 and later
Vendor Advisory: https://gitee.com/mindspore/community/blob/master/security/security_advisory_list/mssa-2021-006_en.md
Restart Required: Yes
Instructions:
1. Check current MindSpore version. 2. Upgrade to version 1.3.0 or later using pip: 'pip install --upgrade mindspore'. 3. Restart all services using MindSpore.
🔧 Temporary Workarounds
Input validation wrapper
allImplement custom validation for Transpose operator inputs before processing
# Python example: Validate perm parameter length matches input shape
def safe_transpose(input_tensor, perm):
if len(perm) != len(input_tensor.shape):
raise ValueError('Invalid perm parameter length')
if any(p >= len(input_tensor.shape) for p in perm):
raise ValueError('Perm values exceed input dimensions')
return original_transpose(input_tensor, perm)
🧯 If You Can't Patch
- Implement strict input validation for all model inference requests
- Isolate MindSpore services in restricted containers with minimal memory access
🔍 How to Verify
Check if Vulnerable:
Check MindSpore version: 'python -c "import mindspore; print(mindspore.__version__)"' and verify if below 1.3.0Check Version:
python -c "import mindspore; print('MindSpore version:', mindspore.__version__)"Verify Fix Applied:
After upgrade, verify version is 1.3.0+ and test with known vulnerable Transpose configurations📡 Detection & Monitoring
Log Indicators:
- Segmentation faults in MindSpore processes
- Unexpected memory access errors
- Model processing failures with Transpose operations
Network Indicators:
- Unusual model upload patterns to ML inference endpoints
- Repeated failed inference requests with similar parameters
SIEM Query:
process_name: "python" AND (event_description: "segmentation fault" OR event_description: "memory access violation") AND process_command_line: "*mindspore*"