transformers
State-of-the-art machine learning framework for text, vision, audio, and multimodal models — inference and training.
Scanned: February 15, 2026
Report Version: 1.0.0
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Scan your repo free →Overall Grade
F24,183 total findings
Architecture
F17079
Correctness
B985
Performance
C104
Security
F6015
What Traditional Tools Missed
| Category | Colosseum | Bandit | Semgrep |
|---|---|---|---|
| Security | 6,015 | 0 | 0 |
| Architecture | 17,079 | 0 | 0 |
| Correctness | 985 | 0 | 0 |
| Performance | 104 | 0 | 0 |
| Total | 24,183 | 0 | 0 |
24,183 findings (100%) were not detected by Bandit or Semgrep. These include compound vulnerabilities, logic errors, and context-dependent security issues that rule-based scanners aren't designed to catch.
Notable Findings
CriticalSecurity
543 Unpinned Model Downloads via from_pretrained()
Impact: Calls to from_pretrained() without revision pinning allow supply-chain attacks. A compromised model on Hugging Face Hub would be silently loaded.
Recommended Fix: Pin model revisions with explicit commit hashes. Use verify_checksums=True where available. Implement model signature verification.
CriticalSecurity
25 Unsafe PyTorch Model Loads
Impact: torch.load() on untrusted data enables arbitrary code execution via pickle deserialization. Critical risk for any model loading pipeline.
Recommended Fix: Use torch.load(weights_only=True) or safetensors format. Never load untrusted .pt/.bin files without sandboxing.
HighSecurity
9 Pickle Deserialization Vectors
Impact: Direct use of pickle/shelve/dill on potentially untrusted data. Remote code execution risk in model serialization paths.
Recommended Fix: Replace pickle with safetensors or JSON for serialization. If pickle required, implement HMAC verification and sandboxing.
HighSecurity
7 SQL Injection Vectors
Impact: String-based query construction in database interaction code. Attackers could manipulate queries through crafted input.
Recommended Fix: Use parameterized queries or ORM methods. Replace all string formatting in SQL with prepared statements.
HighArchitecture
4,755 Bottleneck Saturation Points
Impact: Critical path analysis reveals extreme concentration of data flow through narrow module interfaces. Single-point failures could cascade across the framework.
Recommended Fix: Introduce interface abstractions at high-traffic module boundaries. Add circuit breakers for critical paths.
MediumSecurity
24 HTTP Requests Without Timeout
Impact: Network calls without timeout configuration can hang indefinitely, causing resource exhaustion and denial of service.
Recommended Fix: Set explicit timeout on all requests calls. Use requests.Session with default timeout configuration.
MediumArchitecture
578 Mutable Default Arguments Across 234 Files
Impact: Mutable default arguments in __init__ methods propagate as a pattern across the codebase. New code copies the anti-pattern from existing code.
Recommended Fix: Replace mutable defaults with None sentinel pattern: def __init__(self, items=None): self.items = items or []
Responsible Disclosure
This public report is intended to demonstrate the depth of analysis possible with modern code scanning tools and to help the broader open source community understand common vulnerability patterns.
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