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Refactor entropy scanning to use os.walk #298

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Refactor entropy scanning to use os.walk #298

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142 changes: 68 additions & 74 deletions backend/app/scanners/entropy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@

import math
import re
import os
from collections import Counter
from pathlib import Path
from typing import List
Expand Down Expand Up @@ -45,82 +46,75 @@ def is_allowlisted(token: str) -> bool:

def run_entropy(repo_dir: Path) -> List[Finding]:
findings: List[Finding] = []

ignored_dirs = {
"node_modules", "venv", ".venv", "build", "dist", "target", ".next",
".cache", "coverage", "vendor", "__pycache__", ".git",
".idea", ".vscode", ".tox", ".pytest_cache", ".mypy_cache",
".ruff_cache", "bin", "obj", "out", "tmp"
}

ignored_extensions = {
".png",
".jpg",
".jpeg",
".gif",
".ico",
".svg",
".zip",
".tar",
".gz",
".mp4",
".pdf",
".woff",
".woff2",
".eot",
".ttf",
".png", ".jpg", ".jpeg", ".gif", ".ico", ".svg", ".zip",
".tar", ".gz", ".mp4", ".pdf", ".woff", ".woff2", ".eot", ".ttf",
}

for file_path in repo_dir.rglob("*"):
if (
not file_path.is_file()
or file_path.suffix.lower() in ignored_extensions
or ".git" in file_path.parts
):
continue

try:
content = file_path.read_text(encoding="utf-8", errors="ignore")
except Exception:
continue

lines = content.splitlines()
for line_idx, line in enumerate(lines, start=1):
for match in STRING_LITERAL_REGEX.finditer(line):
token = match.group(2)

if is_allowlisted(token):
continue

entropy_score = calculate_shannon_entropy(token)
if entropy_score > 4.0:
relative_path = str(file_path.relative_to(repo_dir))
finding_id = (
f"entropy:high-entropy-string:{relative_path}:{line_idx}"
)
severity = "HIGH"

raw_data_for_extractor = {
"id": finding_id,
"severity": severity,
"location": {"path": relative_path},
"metadata": {"cwe_category": "CWE-798"},
}

ml_features = extract_features(
raw_data_for_extractor, scanner_name="entropy"
)

findings.append(
Finding(
id=finding_id,
category="secret",
severity=severity,
title="High Entropy String Detected",
description=f"Potential hardcoded secret or token discovered (Entropy: {entropy_score:.2f})",
location=Location(
path=relative_path,
start_line=line_idx,
end_line=line_idx,
),
metadata={
"engine": "entropy",
"entropy_score": entropy_score,
"token_preview": token[:10],
},
features=ml_features,
for root, dirs, files in os.walk(repo_dir):
dirs[:] = [d for d in dirs if d not in ignored_dirs]

file_path = Path(root) / file_name

if file_path.suffix.lower() in ignored_extensions:
continue

try:
content = file_path.read_text(encoding="utf-8", errors="ignore")
except Exception:
continue

lines = content.splitlines()
for line_idx, line in enumerate(lines, start=1):
for match in STRING_LITERAL_REGEX.finditer(line):
token = match.group(2)

if is_allowlisted(token):
continue

entropy_score = calculate_shannon_entropy(token)
if entropy_score > 4.0:
relative_path = str(file_path.relative_to(repo_dir))
finding_id = f"entropy:high-entropy-string:{relative_path}:{line_idx}"
severity = "HIGH"

raw_data_for_extractor = {
"id": finding_id,
"severity": severity,
"location": {"path": relative_path},
"metadata": {"cwe_category": "CWE-798"},
}

ml_features = extract_features(
raw_data_for_extractor, scanner_name="entropy"
)

findings.append(
Finding(
id=finding_id,
category="secret",
severity=severity,
title="High Entropy String Detected",
description=f"Potential hardcoded secret or token discovered (Entropy: {entropy_score:.2f})",
location=Location(
path=relative_path,
start_line=line_idx,
end_line=line_idx,
),
metadata={
"engine": "entropy",
"entropy_score": entropy_score,
"token_preview": token[:10],
},
features=ml_features,
)
)
)
return findings
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