We once audited a Python app where passwords were stored in plain text.
Yes, in 2025.
This wasn’t a small side project or a student assignment.
It was a production system handling real users and real data.
The truth is: most Python security failures aren’t caused by Python.
They’re caused by rushed development, missing reviews, and zero security gates in the delivery process.
Here are three real pitfalls we see repeatedly – and how ARIS prevents them before they become a breach.
1 Storing Passwords Incorrectly (Plain Text, Weak Hashing, No Salting)
This is still the most dangerous and surprisingly common issue.
We’ve seen apps storing credentials as:
- plain text
- MD5 (broken)
- SHA1 (weak)
- reversible encryption
Once breached, these systems expose not only the platform – but also every other account where users reuse the same password.
How ARIS prevents it:
- Mandatory use of PBKDF2, bcrypt, or Argon2
- Automated linting rules that flag insecure hash functions
- Enforced code review gates for all authentication modules
- Multi-layered password validation policies
This ensures security is built into the authentication flow – not added later as a patch.
2 Insecure API Endpoints (Missing Auth, Overly Broad Permissions)
Modern Python systems – especially Django REST or FastAPI backends – expose dozens of endpoints.
The top risks usually include:
- missing authentication
- missing permission checks
- endpoints returning more data than necessary
- debug endpoints left open in production
One such endpoint we audited allowed any user to download entire user lists. No login required.
How ARIS prevents it:
- OWASP API Security Top 10 scanning as part of CI
- Role-based access controls baked into architecture
- Endpoint-level permission decorators
- Automated tests simulating unauthorised access
- Weekly manual review of all exposed routes
This moves API security from “best practice” to “built-in architecture”.
3 Missing Input Validation (Leading to Injection & Logic Vulnerabilities)
Injection attacks aren’t limited to SQL.
We’ve seen issues caused by:
- unsanitised user input
- unsafe string formatting
- dynamic query creation
- file uploads with zero restrictions
These vulnerabilities often remain invisible until they’re exploited.
How ARIS prevents it:
- Pydantic validation for FastAPI
- Django ORM + parameterised queries
- Strict linting rules for string formatting
- Release gates requiring validation tests
- Continuous dependency scanning for vulnerable packages
By enforcing validation at every layer, we eliminate entire classes of security issues.
In Short
Python isn’t insecure – undisciplined processes are.
Security isn’t a one-time patch. It’s a culture built into:
- linting
- code reviews
- OWASP scanning
- CI pipelines
- permission rules
- architecture design
With the right gates in place, most breaches become preventable long before they reach production.
