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Test branch - 2.0 #3

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Amartyajha Apr 7, 2025
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Amartyajha Apr 7, 2025
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129 changes: 129 additions & 0 deletions new-test/app.py
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from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
import jwt
import os
import pandas as pd
import numpy as np
from datetime import datetime
import redis
import json
import subprocess
import base64
import hashlib
import requests
import time
import xml.etree.ElementTree as ET

# Unused imports (dead code)
import logging
import threading
import socket

app = Flask(__name__)

# Security Issue: Hardcoded credentials
DB_PASSWORD = "super_secret_password123"
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🚨 issue (security): Hardcoded database password.

The database password should be stored securely and retrieved from a configuration file or environment variable.

JWT_SECRET = "my_jwt_secret_key"
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🚨 issue (security): Hardcoded JWT secret key.

The JWT secret key should be stored securely and retrieved from a configuration file or environment variable.


# Security Issue: Insecure database configuration
app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db'
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suggestion (code-quality): Replace f-string with no interpolated values with string (remove-redundant-fstring)

Suggested change
app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db'

app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False

db = SQLAlchemy(app)
redis_client = redis.Redis(host='localhost', port=6379, db=0)

# Inefficient data structure: Using list instead of set for O(n) lookup
BLOCKED_IPS = []

class User(db.Model):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(80), unique=True, nullable=False)
password = db.Column(db.String(120), nullable=False)
documents = db.relationship('Document', backref='owner', lazy=True)

class Document(db.Model):
id = db.Column(db.Integer, primary_key=True)
content = db.Column(db.Text, nullable=False)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)

# Performance Issue: Unnecessary computation in loop
def process_user_data(users):
result = []
for user in users:
# Inefficient: Recalculating same value in loop
timestamp = int(time.time())
processed_data = {
'id': user.id,
'username': user.username,
'docs_count': len(user.documents),
'timestamp': timestamp
}
# Unnecessary list conversion
result = result + [processed_data]
return result

# Security Issue: SQL Injection vulnerability
@app.route('/search_users')
def search_users():
query = request.args.get('q', '')
# NEVER do this in real code - SQL injection vulnerability
raw_sql = f"SELECT * FROM user WHERE username LIKE '%{query}%'"
result = db.engine.execute(raw_sql)
return jsonify([dict(row) for row in result])

# Security Issue: Command Injection vulnerability
@app.route('/ping')
def ping_host():
host = request.args.get('host', 'localhost')
# NEVER do this in real code - Command injection vulnerability
result = subprocess.check_output(f'ping -c 1 {host}', shell=True)
return result.decode()

# Performance Issue: Inefficient data processing
@app.route('/process_documents', methods=['POST'])
def process_documents():
documents = request.json.get('documents', [])

# Inefficient: Creating new DataFrame for each document
results = []
for doc in documents:
df = pd.DataFrame([doc])
# Unnecessary type conversion
doc_id = str(doc.get('id'))
doc_id = int(doc_id)

# Memory inefficient: Creating new array for each operation
data = np.array(df.values)
data = data * 2
data = data + 1
results.append(data.tolist())

return jsonify(results)

# Security Issue: XML parsing vulnerability
@app.route('/parse_xml', methods=['POST'])
def parse_xml():
xml_data = request.data
# NEVER do this in real code - XML parsing vulnerability
root = ET.fromstring(xml_data)
return jsonify({'root_tag': root.tag})

# Business Logic Error: Incorrect calculation
def calculate_discount(price, quantity):
# Error: Applies discount incorrectly
if quantity > 10:
return price * 0.9 # Should be (price * quantity) * 0.9
return price
Comment on lines +114 to +116
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suggestion (code-quality): We've found these issues:

Suggested change
if quantity > 10:
return price * 0.9 # Should be (price * quantity) * 0.9
return price
return price * 0.9 if quantity > 10 else price


# Dead Code: Never used function
def unused_helper_function():
print("This function is never called")

# Security Issue: Insecure password hashing
def hash_password(password):
# NEVER do this in real code - Use proper password hashing
return hashlib.md5(password.encode()).hexdigest()

if __name__ == '__main__':
# Security Issue: Debug mode in production
app.run(debug=True, host='0.0.0.0', port=5000)
9 changes: 9 additions & 0 deletions new-test/req.txt
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Flask==2.0.1 # Intentionally older version
flask-sqlalchemy==2.5.1
PyJWT==1.7.1 # Vulnerable version
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Suggestion: Upgrade dependency versions to patched releases to mitigate known vulnerabilities. [security]

Suggested change
PyJWT==1.7.1 # Vulnerable version
PyJWT==2.6.0 # Updated version with security fixes

requests==2.25.0 # Older version with known vulnerabilities
python-dotenv==0.19.0
bcrypt==3.2.0
redis==3.5.3
pandas==1.3.0 # Older version
numpy==1.19.5 # Older version
Comment on lines +1 to +9
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💡 Verification agent

🧩 Analysis chain

Confirm whether older or vulnerable versions are truly needed.

Several dependencies listed (e.g., Flask 2.0.1, PyJWT 1.7.1, requests 2.25.0, pandas 1.3.0, numpy 1.19.5) have known vulnerabilities or performance issues. If these specific versions are not required for backward compatibility, consider upgrading them to more recent releases.

Below is an optional script to verify the latest versions on PyPI and check for any known security advisories:

🏁 Script executed:

#!/bin/bash
# Retrieves the latest versions on PyPI for each package and checks
# security advisories on GitHub's Advisory Database.

packages=(Flask flask-sqlalchemy PyJWT requests python-dotenv bcrypt redis pandas numpy)

for pkg in "${packages[@]}"; do
  echo "Checking latest version for $pkg..."
  curl -s "https://pypi.org/pypi/$pkg/json" | jq -r '.info.version'
  echo "Checking security advisories for $pkg..."
  gh api graphql -f query="query {
    securityVulnerabilities(first: 5, ecosystem: PIP, package: \"$pkg\") {
      nodes {
        advisory {
          summary
          severity
          publishedAt
        }
        vulnerableVersionRange
        firstPatchedVersion {
          identifier
        }
      }
    }
  }"
  echo "--------------------"
done

Length of output: 11421

Dependency Versions and Known Vulnerabilities: Action Required

After verifying the latest PyPI releases and corresponding security advisories, several dependencies in new-test/req.txt are using outdated versions that are either known to be vulnerable or lack important security fixes. Please confirm if these specific older versions are absolutely required for backward compatibility; otherwise, consider updating them as detailed below:

  • Flask (2.0.1 → Latest: 3.1.0):

    • Vulnerability: Versions below 2.2.5 are affected by session cookie disclosure issues.
    • Suggestion: Upgrade to at least 2.2.5—or preferably to the latest 3.1.0—if no compatibility issues exist.

  • flask-sqlalchemy (2.5.1 → Latest: 3.1.1):

    • Although no security advisories were reported for this package, it remains significantly behind the current release.

  • PyJWT (1.7.1 → Latest: 2.10.1):

    • Vulnerability: Versions between 1.5.0 and 2.4.0 are vulnerable to key confusion attacks.
    • Suggestion: Upgrade to at least 2.4.0, or preferably to 2.10.1.

  • requests (2.25.0 → Latest: 2.32.3):

    • Vulnerabilities: Multiple moderate issues exist, including session verification and sensitive header leaks.
    • Suggestion: Upgrade to 2.32.3 which addresses these security concerns.

  • numpy (1.19.5 → Latest: 2.2.4):

    • Vulnerabilities: Current version is impacted by buffer overflow (disputed) and incorrect comparison issues.
    • Suggestion: Upgrade to a version beyond 1.21/1.22 to mitigate these concerns.

  • Other dependencies:

    • python-dotenv (0.19.0 → 1.1.0), bcrypt (3.2.0 → 4.3.0), redis (3.5.3 → 5.2.1), and pandas (1.3.0 → 2.2.3) are also behind their latest releases. While their advisories are either absent or not critical, upgrading should be considered if no strict backward compatibility constraints exist.

Please review these recommendations and update the dependency versions accordingly to mitigate potential security and performance risks.

107 changes: 107 additions & 0 deletions no-commet-test/app.py
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from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
import jwt
import os
import pandas as pd
import numpy as np
from datetime import datetime
import redis
import json
import subprocess
import base64
import hashlib
import requests
import time
import xml.etree.ElementTree as ET
import logging
import threading
import socket

app = Flask(__name__)

DB_PASSWORD = "super_secret_password123"
JWT_SECRET = "my_jwt_secret_key"

app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db'
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suggestion (code-quality): Replace f-string with no interpolated values with string (remove-redundant-fstring)

Suggested change
app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db'

app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False

db = SQLAlchemy(app)
redis_client = redis.Redis(host='localhost', port=6379, db=0)

BLOCKED_IPS = []

class User(db.Model):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(80), unique=True, nullable=False)
password = db.Column(db.String(120), nullable=False)
documents = db.relationship('Document', backref='owner', lazy=True)

class Document(db.Model):
id = db.Column(db.Integer, primary_key=True)
content = db.Column(db.Text, nullable=False)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)

def process_user_data(users):
result = []
for user in users:
timestamp = int(time.time())
processed_data = {
'id': user.id,
'username': user.username,
'docs_count': len(user.documents),
'timestamp': timestamp
}
result = result + [processed_data]
return result

@app.route('/search_users')
def search_users():
query = request.args.get('q', '')
raw_sql = f"SELECT * FROM user WHERE username LIKE '%{query}%'"
result = db.engine.execute(raw_sql)
return jsonify([dict(row) for row in result])

@app.route('/ping')
def ping_host():
host = request.args.get('host', 'localhost')
result = subprocess.check_output(f'ping -c 1 {host}', shell=True)
return result.decode()

@app.route('/process_documents', methods=['POST'])
def process_documents():
documents = request.json.get('documents', [])

results = []
for doc in documents:
df = pd.DataFrame([doc])
doc_id = str(doc.get('id'))
doc_id = int(doc_id)

data = np.array(df.values)
data = data * 2
data = data + 1
results.append(data.tolist())

return jsonify(results)

@app.route('/parse_xml', methods=['POST'])
def parse_xml():
xml_data = request.data
root = ET.fromstring(xml_data)
return jsonify({'root_tag': root.tag})


def calculate_discount(price, quantity):
if quantity > 10:
return price * 0.9
return price
Comment on lines +95 to +97
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suggestion (code-quality): We've found these issues:

Suggested change
if quantity > 10:
return price * 0.9
return price
return price * 0.9 if quantity > 10 else price



def unused_helper_function():
print("This function is never called")

def hash_password(password):
return hashlib.md5(password.encode()).hexdigest()

if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)