Desktop Application Security in Python (DASEC-PY) – Contenuti

Contenuti dettagliati del Corso

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
    • How to validate – validation vs transformations
    • Output sanitization
    • Encoding challenges
    • Lab – Encoding challenges
    • Validation with regex
    • Regular expression denial of service (ReDoS)
    • Lab – Regular expression denial of service (ReDoS)
    • 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
      • Additional considerations
      • Lab – SQL injection best practices
      • 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
        • Case study – Command injection via ping
        • Python module hijacking
        • Lab – Module hijacking
    • General protection best practices

DAY 2

Input validation

  • Integer handling problems
    • Representing signed numbers
    • Integer visualization
    • Integers in Python
    • Integer overflow
    • Integer overflow with ctypes and numpy
    • Lab – Integer problems in Python
    • Other numeric problems
      • Division by zero
      • Other numeric problems in Python
      • Working with floating-point numbers
  • Files and streams
    • Path traversal
    • Path traversal-related examples
    • Lab – Path traversal
    • Additional challenges in Windows
    • Virtual resources
    • Path traversal best practices
    • 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
    • Authentication weaknesses – spoofing
    • 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 length
          • Password hardening
          • Using passphrases
          • Password change
          • Forgotten passwords
          • 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
  • Python platform security
    • The Python ecosystem and its attack surface
    • Python bytecode and security
    • Security features offered by the Python runtime
    • PEP 578 and audit hooks
    • Sandboxing Python

Using vulnerable components

  • Assessing the environment
  • Hardening
  • Malicious packages in Python
  • Vulnerability management
    • Patch management
    • Bug bounty programs
    • Vulnerability databases
    • Vulnerability rating – CVSS
    • 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
      • Case study – Equifax credit account freeze
      • Lab – Using random numbers in Python
    • 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
        • Elliptic Curve Cryptography
          • The ECC algorithm
          • Using ECC – best practices
          • ECC in Python
        • Combining symmetric and asymmetric algorithms
          • 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
      • Digital signature with ECC
      • Digital signature in Python
  • Public Key Infrastructure (PKI)
    • Some further key management challenges
    • Certificates
      • Chain of trust
      • PGP – Web of Trust
      • Certificate management – best practices

Common software security weaknesses

  • Time and state
    • Race conditions
      • File race condition
        • Time of check to time of usage – TOCTTOU
        • Insecure temporary file
      • Avoiding race conditions in Python
        • Thread safety and the Global Interpreter Lock (GIL)
        • Case study: TOCTTOU in Calamares
  • Errors
    • Error and exception handling principles
    • Error handling
      • Returning a misleading status code
      • Information exposure through error reporting
    • Exception handling
      • In the except,catch block. And now what?
      • Empty catch block
      • The danger of assert statements
      • Lab – Exception handling mess
  • Code quality
    • Language elements
      • Using dangerous language elements
      • Using obsolete language elements
      • Portability flaw
      • Module injection and monkey patching
      • Dangers of compile(), exec() and eval()
      • Sandboxing Python
  • Denial of service
    • Denial of Service
    • Resource exhaustion
    • Cash overflow
    • Flooding
    • Algorithm complexity issues

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