Desktop application security in Python

Python developers working on desktop applications

• Getting familiar with essential cyber security concepts
• Identify vulnerabilities and their consequences
• Learn the security best practices in Python
• Input validation approaches and principles
• Managing vulnerabilities in third party components
• Understanding how cryptography supports security
• Learning how to use cryptographic APIs correctly in Python

General Python development

Day 1:

• Cyber security basics
  • What is security?
  • Threat and risk
  • Cyber security threat types
  • Consequences of insecure software
    • Constraints and the market
    • The dark side
• Input validation
  • Input validation principles
    • Blacklists and whitelists
    • Data validation techniques
    • Lab – Input validation
    • What to validate – the attack surface
    • Where to validate – defense in depth
    • When to validate – validation vs transformations
    • Output sanitization
    • Encoding challenges
    • Unicode challenges
    • Validation with regex
    • Regular expression denial of service (ReDoS)
    • Lab – ReDoS in Python
    • Dealing with ReDoS
  • Injection
    • Injection principles
    • Injection attacks
    • SQL injection
      • SQL injection basics
      • Lab – SQL injection
      • Attack techniques
      • Content-based blind SQL injection
      • Time-based blind SQL injection
    • SQL injection best practices
      • Input validation
      • Parameterized queries
      • Lab – SQL injection best practices
      • Additional considerations
      • Case study – Hacking Fortnite accounts
    • Code injection
      • Code injection via input()
      • OS command injection
        • Lab – Command injection
        • OS command injection best practices
        • Avoiding command injection with the right APIs
        • Lab – Command injection best practices
        • Case study – Shellshock
        • Lab – Shellshock
        • Python module hijacking
        • Lab – Library hijacking in Python

Day 2:

• Input validation
  • Integer handling problems
    • Representing signed numbers
    • Integer visualization
    • Integers in Python
    • Integer overflow
    • Integer overflows in ctypes and numpy
    • Other numeric problems
      • Working with floating-point numbers
  • Files and streams
    • Path traversal
    • Lab – Path traversal
    • Path traversal-related examples
    • Additional challenges in Windows
    • Virtual resources
    • Path traversal best practices
    • Lab – Path canonicalization
  • Format string issues
  • Unsafe native code
    • Native code dependence
    • Lab – Unsafe native code
    • Best practices for dealing with native code
• Security features
  • Authentication
    • Authentication basics
    • Multi-factor authentication
    • Time-based One Time Passwords (TOTP)
    • Authentication weaknesses
    • Case study – PayPal 2FA bypass
    • Password management
      • Inbound password management
        • Storing account passwords
        • Password in transit
        • Lab – Is just hashing passwords enough?
        • Dictionary attacks and brute forcing
        • Salting
        • Adaptive hash functions for password storage
        • Password policy
          • NIST authenticator requirements for memorized secrets
          • Password hardening
          • Using passphrases
          • Password change
          • Password recovery issues
          • Password recovery best practices
          • Lab – Password reset weakness
        • Case study – The Ashley Madison data breach
          • The dictionary attack
          • The ultimate crack
          • Exploitation and the lessons learned
        • Password database migration
      • Outbound password management
        • Hard coded passwords
        • Best practices
        • Lab – Hardcoded password
        • Protecting sensitive information in memory
          • Challenges in protecting memory
  • Information exposure
    • Exposure through extracted data and aggregation
    • Case study – Strava data exposure
    • System information leakage
      • Leaking system information
    • Information exposure best practices
  • Platform security
    • Python platform security
      • The Python ecosystem and its attack surface
      • Python bytecode and security
      • Security features offered by Python
      • PEP 578 and audit hooks
      • Sandboxing Python
• Using vulnerable components
  • Assessing the environment
  • Hardening
  • Case study – The British Airways data breach
  • Vulnerability management
    • Patch management
    • Vulnerability databases
    • DevOps, the build process and CI / CD
    • Dependency checking in Python
    • Lab – Detecting vulnerable components

Day 3:

• Cryptography for developers
  • Cryptography basics
  • Cryptography in Python
  • Elementary algorithms
    • Random number generation
      • Pseudo random number generators (PRNGs)
      • Cryptographically strong PRNGs
      • Using virtual random streams
      • Weak and strong PRNGs
      • Using random numbers in Python
      • Lab – Using random numbers in Python
      • Case study – Equifax credit account freeze
    • Hashing
      • Hashing basics
      • Common hashing mistakes
      • Hashing in Python
      • Lab – Hashing in Python
  • Confidentiality protection
    • Symmetric encryption
      • Block ciphers
      • Modes of operation
      • Modes of operation and IV – best practices
      • Symmetric encryption in Python
      • Lab – Symmetric encryption in Python
    • Asymmetric encryption
      • The RSA algorithm
        • Using RSA – best practices
        • RSA in Python
    • Combining symmetric and asymmetric algorithms
    • Key exchange and agreement
      • Key exchange
      • Diffie-Hellman key agreement algorithm
      • Key exchange pitfalls and best practices
  • Integrity protection
    • Authenticity and non-repudiation
    • Message Authentication Code (MAC)
      • MAC in Python
      • Lab – Calculating MAC in Python
    • Digital signature
      • Digital signature with RSA
      • Elliptic Curve Cryptography
        • ECC basics
        • Digital signature with ECC
      • Digital signature in Python
        • Lab – Digital signature with ECDSA in Python
  • Public Key Infrastructure (PKI)
    • Some further key management challenges
    • Certificates
      • Certificates and PKI
      • X.509 certificates
      • Chain of trust
      • PKI actors and procedures
      • PGP – Web of Trust
      • Certificate revocation
• Common software security weaknesses
  • Errors
    • Error and exception handling principles
    • Error handling
      • Returning a misleading status code
      • Information exposure through error reporting
    • Exception handling
      • In the except block. And now what?
      • Empty except block
      • Lab – Exception handling mess
  • Code quality
• Wrap up
  • Secure coding principles
    • Principles of robust programming by Matt Bishop
    • Secure design principles of Saltzer and Schröder
  • And now what?
    • Software security sources and further reading
    • Python resources