Security context
What an agent needs to avoid regressing past fixes and find the next vuln in this repo.
tiiny-ai/powerinfer
main @ 8bd56d6
3
Fixes
0
CVEs
HIGH
Peak severity
0.0%
Coverage
Highlights
Insecure Deserialization: 1 prior fix. Scrutinize any change in this area.
convert-pth-to-ggml.py: most-fixed (1 issue). Treat as high-risk during review.
2 high-severity fixes in this history; regressions here are high-impact.
Recurring patterns
The bug types that recur here, drawn from past fixes, not open vulnerabilities.
Insecure Deserialization: The model conversion script utilized PyTorch's default deserialization, which relies on the unsafe pickle module, permitting arbitrary code execution when loading untrusted model weights. Subsequent code must always restrict loading to safe weights only.
Memory Corruption: An undersized temporary work buffer during OpenCL matrix multiplication could lead to buffer overflows and memory corruption. Native C++ components require strict buffer size constraints and boundary assertions during mathematical operations.
Path Traversal: Parsing model file headers without rigorous magic and format version validation exposes the loader to out-of-bounds reads or path traversal behaviors during model quantization or load workflows.