codesentry-backend/tests/fixtures/expected_findings.json

{
  "security_findings": [
    {
      "severity": "critical",
      "title": "Insecure Pickle Deserialization",
      "cwe": "CWE-502",
      "owasp_category": "A04",
      "line_number": 48,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "pickle.load() from a user-controlled path allows arbitrary code execution"
    },
    {
      "severity": "critical",
      "title": "LLM Output Passed to eval()",
      "cwe": "CWE-116",
      "owasp_category": "LLM02",
      "line_number": 78,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "eval() on untrusted LLM output allows arbitrary code execution"
    },
    {
      "severity": "critical",
      "title": "Prompt Injection via String Concatenation",
      "cwe": "CWE-74",
      "owasp_category": "LLM01",
      "line_number": 58,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "User input directly concatenated into prompt string"
    },
    {
      "severity": "critical",
      "title": "Hardcoded HuggingFace Token",
      "cwe": "CWE-798",
      "owasp_category": "LLM06",
      "line_number": 20,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "Hardcoded API token exposed in source code"
    },
    {
      "severity": "critical",
      "title": "SQL Injection in RAG Query",
      "cwe": "CWE-89",
      "owasp_category": "A03",
      "line_number": 90,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "Unsanitised user input in SQL LIKE query"
    },
    {
      "severity": "high",
      "title": "GPU Tensor Memory Leak",
      "cwe": "CWE-401",
      "owasp_category": "ML01",
      "line_number": 75,
      "file_path": "vulnerable_ml_code.py",
      "explanation": "Tensor allocated on CUDA device never moved to CPU or deleted"
    }
  ],
  "performance_findings": [
    {
      "type": "gpu_memory",
      "title": "FP32 dtype — should use BF16",
      "saving_mb": 3584,
      "file_path": "vulnerable_ml_code.py"
    },
    {
      "type": "throughput",
      "title": "N+1 embedding calls in loop",
      "saving_mb": 0,
      "file_path": "vulnerable_ml_code.py"
    },
    {
      "type": "latency",
      "title": "Model loaded inside request handler",
      "saving_mb": 0,
      "file_path": "vulnerable_ml_code.py"
    },
    {
      "type": "gpu_memory",
      "title": "Missing @torch.no_grad on inference",
      "saving_mb": 512,
      "file_path": "vulnerable_ml_code.py"
    }
  ]
}