check file #2
check file #2
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Reviewer's Guide by SourceryThis pull request introduces a new Flask application with several security vulnerabilities, performance issues, and bad practices. It also adds a requirements file. No diagrams generated as the changes look simple and do not need a visual representation. File-Level Changes
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WalkthroughA new Flask application has been introduced to handle user and document data. The application defines two SQLAlchemy models (User and Document) and includes several processing functions. Various endpoints are implemented: one to search users (using a raw SQL query), one to ping a host (allowing command injection), one for document processing (with inefficient data handling), and one for XML parsing (vulnerable due to lack of validation). Additionally, a requirements file listing specific package versions has been added. Changes
Sequence Diagram(s)sequenceDiagram
participant C as Client
participant A as FlaskApp
participant DB as Database
C->>A: GET /search_users
A->>DB: Execute raw SQL query
DB-->>A: Return user data
A->>C: Respond with user data
sequenceDiagram
participant C as Client
participant A as FlaskApp
participant S as System
C->>A: GET /ping with command parameters
A->>S: Execute ping command
S-->>A: Return command output
A->>C: Send ping response
sequenceDiagram
participant C as Client
participant A as FlaskApp
participant DF as DataFrameProcessor
C->>A: POST /process_documents with document list
A->>DF: Process each document (inefficient handling)
DF-->>A: Return processed data
A->>C: Return processed results
Poem
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Hey @Amartyajha - I've reviewed your changes and found some issues that need to be addressed.
Blocking issues:
Overall Comments:
- This PR introduces several security vulnerabilities; consider addressing them before merging.
- The code contains performance inefficiencies that should be optimized.
- There's a mix of concerns in this PR; consider breaking it down into smaller, focused changes.
Here's what I looked at during the review
- 🟢 General issues: all looks good
- 🔴 Security: 2 blocking issues
- 🟢 Review instructions: all looks good
- 🟢 Testing: all looks good
- 🟢 Complexity: all looks good
- 🟢 Documentation: all looks good
Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
| app = Flask(__name__) | ||
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| # Security Issue: Hardcoded credentials | ||
| DB_PASSWORD = "super_secret_password123" |
There was a problem hiding this comment.
🚨 issue (security): Hardcoded password detected.
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| # Security Issue: Hardcoded credentials | ||
| DB_PASSWORD = "super_secret_password123" | ||
| JWT_SECRET = "my_jwt_secret_key" |
There was a problem hiding this comment.
🚨 issue (security): Hardcoded JWT secret detected.
| JWT_SECRET = "my_jwt_secret_key" | ||
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| # Security Issue: Insecure database configuration | ||
| app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db' |
There was a problem hiding this comment.
suggestion (code-quality): Replace f-string with no interpolated values with string (remove-redundant-fstring)
| app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db' | |
| app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db' |
| if quantity > 10: | ||
| return price * 0.9 # Should be (price * quantity) * 0.9 | ||
| return price |
There was a problem hiding this comment.
suggestion (code-quality): We've found these issues:
- Lift code into else after jump in control flow (
reintroduce-else) - Replace if statement with if expression (
assign-if-exp)
| if quantity > 10: | |
| return price * 0.9 # Should be (price * quantity) * 0.9 | |
| return price | |
| return price * 0.9 if quantity > 10 else price |
codeant-ai
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added
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![codeant-ai[bot]](https://avatars.githubusercontent.com/in/646884?s=60&v=4){kind=small}
| DB_PASSWORD = "super_secret_password123" | ||
| JWT_SECRET = "my_jwt_secret_key" |
There was a problem hiding this comment.
Suggestion: Replace hardcoded credentials with environment variable lookups. [security]
| DB_PASSWORD = "super_secret_password123" | |
| JWT_SECRET = "my_jwt_secret_key" | |
| DB_PASSWORD = os.getenv("DB_PASSWORD") | |
| JWT_SECRET = os.getenv("JWT_SECRET") |
| raw_sql = f"SELECT * FROM user WHERE username LIKE '%{query}%'" | ||
| result = db.engine.execute(raw_sql) |
There was a problem hiding this comment.
Suggestion: Use parameterized queries to safely incorporate user input in SQL statements. [security]
| raw_sql = f"SELECT * FROM user WHERE username LIKE '%{query}%'" | |
| result = db.engine.execute(raw_sql) | |
| from sqlalchemy import text | |
| raw_sql = text("SELECT * FROM user WHERE username LIKE :query") | |
| result = db.engine.execute(raw_sql, query=f"%{query}%") |
| 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) |
There was a problem hiding this comment.
Suggestion: Prevent command injection by eliminating shell=True and passing command arguments as a list. [security]
| result = subprocess.check_output(f'ping -c 1 {host}', shell=True) | |
| result = subprocess.check_output(['ping', '-c', '1', host]) |
| def hash_password(password): | ||
| # NEVER do this in real code - Use proper password hashing | ||
| return hashlib.md5(password.encode()).hexdigest() |
There was a problem hiding this comment.
Suggestion: Replace MD5 with a secure password hashing algorithm like bcrypt. [security]
| def hash_password(password): | |
| # NEVER do this in real code - Use proper password hashing | |
| return hashlib.md5(password.encode()).hexdigest() | |
| def hash_password(password): | |
| return bcrypt.hashpw(password.encode(), bcrypt.gensalt()).decode() |
| # Error: Applies discount incorrectly | ||
| if quantity > 10: | ||
| return price * 0.9 # Should be (price * quantity) * 0.9 | ||
| return price |
There was a problem hiding this comment.
Suggestion: Correct the discount calculation to apply the discount to the total price for quantities over 10. [possible bug]
| # Error: Applies discount incorrectly | |
| if quantity > 10: | |
| return price * 0.9 # Should be (price * quantity) * 0.9 | |
| return price | |
| def calculate_discount(price, quantity): | |
| if quantity > 10: | |
| return (price * quantity) * 0.9 | |
| return price * quantity |
Pull Request Feedback 🔍
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![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
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Actionable comments posted: 10
🧹 Nitpick comments (4)
new-test/app.py (4)
3-3: Remove unused imports to clean up the code.Imports such as
jwt,os,datetime,json,base64,requests,logging,threading, andsocketare not used anywhere in the file. Cleaning up unused imports improves maintainability and reduces confusion.Also applies to: 4-4, 7-7, 9-9, 11-11, 13-13, 18-18, 19-19, 20-20
🧰 Tools
🪛 Ruff (0.8.2)
3-3:
jwtimported but unusedRemove unused import:
jwt(F401)
35-36: Use a set for efficient membership checks.Access to
BLOCKED_IPSis O(n) for a list. If you anticipate frequent lookups, consider using a set for O(1) average-time lookups.- BLOCKED_IPS = [] + BLOCKED_IPS = set()
49-63: Optimize user data processing.
- Recomputing the timestamp on every loop iteration is redundant.
- Instead of repeatedly concatenating lists, consider appending to a single list to avoid performance overhead.
Below is a sample improvement:
-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 +def process_user_data(users): + result = [] + timestamp = int(time.time()) + for user in users: + processed_data = { + 'id': user.id, + 'username': user.username, + 'docs_count': len(user.documents), + 'timestamp': timestamp + } + result.append(processed_data) + return result
118-121: Consider removing or repurposing dead code.
unused_helper_functionis never called, which may lead to confusion. Either remove it or implement its usage if needed.
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Review profile: CHILL
Plan: Pro
📒 Files selected for processing (2)
new-test/app.py(1 hunks)new-test/req.txt(1 hunks)
🧰 Additional context used
🪛 Ruff (0.8.2)
new-test/app.py
3-3: jwt imported but unused
Remove unused import: jwt
(F401)
4-4: os imported but unused
Remove unused import: os
(F401)
7-7: datetime.datetime imported but unused
Remove unused import: datetime.datetime
(F401)
9-9: json imported but unused
Remove unused import: json
(F401)
11-11: base64 imported but unused
Remove unused import: base64
(F401)
13-13: requests imported but unused
Remove unused import: requests
(F401)
18-18: logging imported but unused
Remove unused import: logging
(F401)
19-19: threading imported but unused
Remove unused import: threading
(F401)
20-20: socket imported but unused
Remove unused import: socket
(F401)
29-29: f-string without any placeholders
Remove extraneous f prefix
(F541)
🪛 ast-grep (0.31.1)
new-test/app.py
[warning] 128-128: Detected Flask app with debug=True. Do not deploy to production with this flag enabled as it will leak sensitive information. Instead, consider using Flask configuration variables or setting 'debug' using system environment variables.
Context: app.run(debug=True, host='0.0.0.0', port=5000)
Note: [CWE-489] Active Debug Code. [REFERENCES]
- https://labs.detectify.com/2015/10/02/how-patreon-got-hacked-publicly-exposed-werkzeug-debugger/
(debug-enabled-python)
| Flask==2.0.1 # Intentionally older version | ||
| flask-sqlalchemy==2.5.1 | ||
| PyJWT==1.7.1 # Vulnerable version | ||
| 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 No newline at end of file |
There was a problem hiding this comment.
💡 Verification agent
🧩 Analysis chain
Pinned older and vulnerable package versions.
Several packages here are intentionally pinned to older versions (e.g., Flask==2.0.1, PyJWT==1.7.1, requests==2.25.0). These are known to have security or stability issues. It's strongly recommended to upgrade to newer, patched versions to prevent potential security breaches or incompatibilities.
Below is a script you can run to check for any active security advisories on each pinned package:
🏁 Script executed:
#!/bin/bash
# Description: Check for known security advisories for pinned packages using GitHub GraphQL API.
packages=("Flask" "PyJWT" "requests" "python-dotenv" "bcrypt" "redis" "pandas" "numpy")
for pkg in "${packages[@]}"; do
echo "Checking vulnerabilities for package: $pkg"
gh api graphql -f query="query(\$name: String!) {
securityVulnerabilities(first: 10, ecosystem: PIP, package: \$name) {
nodes {
advisory {
summary
publishedAt
severity
}
vulnerableVersionRange
firstPatchedVersion {
identifier
}
}
}
}" -F name="$pkg"
echo ""
doneLength of output: 10164
Action Required: Upgrade Vulnerable Package Versions
The current versions pinned in new-test/req.txt remain outdated and expose the project to known security vulnerabilities. Based on the GitHub GraphQL API checks:
-
Flask==2.0.1
- Detected multiple high-severity issues (e.g., DoS and session cookie disclosure). Upgrading to versions ≥2.2.5 or ≥2.3.2 is recommended.
-
PyJWT==1.7.1
- Falls within the vulnerable range (≥1.5.0, <2.4.0) due to key confusion attacks. An upgrade to at least 2.4.0 is advisable.
-
requests==2.25.0
- Identified with several moderate to high vulnerabilities (e.g., session fixation and information leakage). Upgrading to version 2.32.0 or later is recommended.
-
numpy==1.19.5
- Matches vulnerable version ranges concerning buffer overflow and other issues. Upgrading to ≥1.22 is recommended.
For the other packages listed (python-dotenv==0.19.0, bcrypt==3.2.0, redis==3.5.3, pandas==1.3.0), no active vulnerabilities were detected. However, the significant security concerns identified with Flask, PyJWT, requests, and numpy necessitate immediate action.
Action Items:
- Upgrade Flask to a secure version (≥2.2.5 or ≥2.3.2 as per respective advisories).
- Upgrade PyJWT to ≥2.4.0.
- Upgrade requests to ≥2.32.0.
- Upgrade numpy to at least 1.22.
| # Security Issue: Hardcoded credentials | ||
| DB_PASSWORD = "super_secret_password123" | ||
| JWT_SECRET = "my_jwt_secret_key" | ||
|
|
There was a problem hiding this comment.
Avoid hardcoding sensitive credentials.
Storing critical secrets like database passwords and JWT secrets in plain text can lead to security breaches. Consider using environment variables or a secure secrets manager.
| # 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}) | ||
|
|
There was a problem hiding this comment.
Validate or sanitize XML input to prevent XXE and other XML vulnerabilities.
Blindly parsing user-supplied XML can allow harmful payloads. Use secure parsers or implement checks to guard against malicious entities (e.g., disable external entity references).
| if __name__ == '__main__': | ||
| # Security Issue: Debug mode in production | ||
| app.run(debug=True, host='0.0.0.0', port=5000) |
There was a problem hiding this comment.
Disable debug mode in production.
Running the Flask app with debug=True reveals sensitive tracebacks and can further expose your system. Set debug=False or use configuration files/environment variables to toggle this safely.
-if __name__ == '__main__':
- app.run(debug=True, host='0.0.0.0', port=5000)
+if __name__ == '__main__':
+ app.run(debug=False, host='0.0.0.0', port=5000)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| if __name__ == '__main__': | |
| # Security Issue: Debug mode in production | |
| app.run(debug=True, host='0.0.0.0', port=5000) | |
| if __name__ == '__main__': | |
| app.run(debug=False, host='0.0.0.0', port=5000) |
🧰 Tools
🪛 ast-grep (0.31.1)
[warning] 128-128: Detected Flask app with debug=True. Do not deploy to production with this flag enabled as it will leak sensitive information. Instead, consider using Flask configuration variables or setting 'debug' using system environment variables.
Context: app.run(debug=True, host='0.0.0.0', port=5000)
Note: [CWE-489] Active Debug Code. [REFERENCES]
- https://labs.detectify.com/2015/10/02/how-patreon-got-hacked-publicly-exposed-werkzeug-debugger/
(debug-enabled-python)
| # 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() | ||
|
|
There was a problem hiding this comment.
Use a secure password hashing function.
MD5 is cryptographically broken and unsuitable for passwords. Switch to a robust library-based approach such as bcrypt or argon2.
-def hash_password(password):
- return hashlib.md5(password.encode()).hexdigest()
+import bcrypt
+
+def hash_password(password):
+ salt = bcrypt.gensalt()
+ return bcrypt.hashpw(password.encode(), salt).decode()📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # 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() | |
| # Security Issue: Insecure password hashing | |
| import bcrypt | |
| def hash_password(password): | |
| salt = bcrypt.gensalt() | |
| return bcrypt.hashpw(password.encode(), salt).decode() |
| # 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]) | ||
|
|
There was a problem hiding this comment.
Prevent SQL injection by using parameterized queries.
Constructing SQL strings with unsanitized input opens the door to attackers. Always use parameter binding or ORM methods.
- raw_sql = f"SELECT * FROM user WHERE username LIKE '%{query}%'"
- result = db.engine.execute(raw_sql)
+ # Example of using a safe parameter for LIKE queries:
+ raw_sql = text("SELECT * FROM user WHERE username LIKE :query")
+ result = db.engine.execute(raw_sql, {"query": f"%{query}%"})📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # 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: SQL Injection vulnerability | |
| @app.route('/search_users') | |
| def search_users(): | |
| query = request.args.get('q', '') | |
| # Example of using a safe parameter for LIKE queries: | |
| raw_sql = text("SELECT * FROM user WHERE username LIKE :query") | |
| result = db.engine.execute(raw_sql, {"query": f"%{query}%"}) | |
| return jsonify([dict(row) for row in result]) |
| # Security Issue: Insecure database configuration | ||
| app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db' |
There was a problem hiding this comment.
Insecure database configuration and extraneous f-string prefix.
- The database URI uses an f-string but does not interpolate any variable. Remove the
fprefix. - SQLite is fine for demos, but storing credentials in code plus referencing them is risky; ensure you handle credentials properly if you upgrade to a production-quality DB.
-app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db'
+app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db'📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # Security Issue: Insecure database configuration | |
| app.config['SQLALCHEMY_DATABASE_URI'] = f'sqlite:///app.db' | |
| # Security Issue: Insecure database configuration | |
| app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db' |
🧰 Tools
🪛 Ruff (0.8.2)
29-29: f-string without any placeholders
Remove extraneous f prefix
(F541)
| # 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() | ||
|
|
There was a problem hiding this comment.
Mitigate command injection by sanitizing or restricting user input.
Running shell commands directly with user input is extremely risky. Consider safer alternatives, like Python’s built-in ping libraries or verifying trusted host inputs.
- result = subprocess.check_output(f'ping -c 1 {host}', shell=True)
- return result.decode()
+ # Example of a safer approach:
+ import shlex
+ safe_host = shlex.quote(host)
+ result = subprocess.check_output(["ping", "-c", "1", safe_host])
+ return result.decode()📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # 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() | |
| # 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 | |
| # Example of a safer approach: | |
| import shlex | |
| safe_host = shlex.quote(host) | |
| result = subprocess.check_output(["ping", "-c", "1", safe_host]) | |
| return result.decode() |
| # Performance Issue: Inefficient data processing | ||
| @app.route('/process_documents', methods=['POST']) | ||
| def process_documents(): | ||
| documents = request.json.get('documents', []) | ||
|
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| # 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) | ||
|
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| # Memory inefficient: Creating new array for each operation | ||
| data = np.array(df.values) | ||
| data = data * 2 | ||
| data = data + 1 | ||
| results.append(data.tolist()) | ||
|
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| return jsonify(results) | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Streamline document processing to improve performance.
- Creating a new DataFrame for each document can be expensive.
- Repeated type conversions and array allocations may consume excessive memory.
Below is a sketch showing how you might handle all documents in a single DataFrame:
-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)
+def process_documents():
+ docs_json = request.json.get('documents', [])
+ df = pd.DataFrame(docs_json)
+ # Example vectorized transformations:
+ df['id'] = df['id'].astype(int)
+ numeric_data = df.select_dtypes(include=[np.number]) * 2 + 1
+ df.update(numeric_data)
+ return jsonify(df.to_dict(orient='records'))📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # 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) | |
| # Performance Issue: Inefficient data processing | |
| @app.route('/process_documents', methods=['POST']) | |
| def process_documents(): | |
| docs_json = request.json.get('documents', []) | |
| df = pd.DataFrame(docs_json) | |
| # Example vectorized transformations: | |
| df['id'] = df['id'].astype(int) | |
| numeric_data = df.select_dtypes(include=[np.number]) * 2 + 1 | |
| df.update(numeric_data) | |
| return jsonify(df.to_dict(orient='records')) |
| # 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 | ||
|
|
There was a problem hiding this comment.
Fix incorrect discount logic.
The discount calculation is likely intended to apply to the total cost of the items, not just the unit price.
-def calculate_discount(price, quantity):
- if quantity > 10:
- return price * 0.9
- return price
+def calculate_discount(price, quantity):
+ if quantity > 10:
+ return (price * quantity) * 0.9
+ return price * quantity📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| # 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 | |
| # Business Logic Error: Incorrect calculation | |
| def calculate_discount(price, quantity): | |
| # Error: Applies discount incorrectly | |
| if quantity > 10: | |
| return (price * quantity) * 0.9 | |
| return price * quantity |
User description
new app push
Summary by Sourcery
Create a new Flask application with multiple security vulnerabilities and performance issues
New Features:
Bug Fixes:
Enhancements:
CodeAnt-AI Description
This PR creates a new Flask application with significant security and performance issues, serving as a demonstration of common anti-patterns and vulnerabilities. The dependencies specified are outdated, highlighting potential risks in using older versions.
Changes walkthrough
app.py
Implement Flask app with security and performance issuesnew-test/app.py
functionality.
credentials and SQL injection.
req.txt
Add dependencies with vulnerable versionsnew-test/req.txt
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Summary by CodeRabbit
New Features
Chores