Security context
What an agent needs to avoid regressing past fixes and find the next vuln in this repo.
fedml-ai/fedml
master @ 03e11df
15
Fixes
2
CVEs
HIGH
Peak severity
13.3%
Coverage
Highlights
Denial of Service: 4 prior fixes. Scrutinize any change in this area.
python/fedml/mlops/mlops_configs.py: most-fixed (3 issues). Treat as high-risk during review.
6 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.
Broken Cryptography: Serialized machine learning models are uploaded directly to IPFS without encryption, exposing intellectual property and sensitive training data to anyone on the public IPFS DHT. The fix enforces symmetric AES encryption prior to storage.
Command Injection: User-controlled or dynamic parameters such as the cache directory are interpolated directly into shell strings executed via os.system, presenting a direct path to remote code execution.
Insecure TLS Configuration: Requests fetching developer and testing environment configurations were historically transmitted over cleartext HTTP and omitted SSL/TLS certificate verification, rendering the platform vulnerable to active Man-in-the-Middle (MitM) attacks.