Description
Description
Your application written in Python works as intended, so you are done, right? But did you consider feeding in incorrect values? 16Gbs of data? A null? An apostrophe? Negative numbers, or specifically -1 or -2^31? Because that’s what the bad guys will do – and the list is far from complete. Handling security needs a healthy level of paranoia, and this is what this course provides: a strong emotional engagement by lots of hands-on labs and stories from real life, all to substantially improve code hygiene. Mistakes, consequences, and best practices are our blood, sweat and tears. All this is put in the context of Python, and extended by core programming issues, discussing security pitfalls of the programming language. So that you are prepared for the forces of the dark side. So that nothing unexpected happens. Nothing.
Outline
- Cyber security basics
- Input validation
- Security features
- Using vulnerable components
- Cryptography for developers
- Common software security weaknesses
- Wrap up
Audience
Python developers working on desktop applications
What you’ll learn
- Getting familiar with essential cyber security concepts
- Input validation approaches and principles
- Identify vulnerabilities and their consequences
- Learn the security best practices in Python
- Managing vulnerabilities in third party components
- Understanding how cryptography supports security
- Learning how to use cryptographic APIs correctly in Python
Preparedness
General Python development.
Standards and references
CWE and Fortify Taxonomy
Platform
Desktop
Day 1
Cyber security basics
- What is security?
- Threat and risk
- Cyber security threat types – the CIA triad
- Cyber security threat types – the STRIDE model
- Consequences of insecure software
Input validation
- Input validation principles
- Denylists and allowlists
- What to validate – the attack surface
- Where to validate – defense in depth
- When to validate – validation vs transformations
- 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 – Using prepared statements
- 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
Security features
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
Using vulnerable components
- Assessing the environment
- Hardening
- Malicious packages in Python
- 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 PRNGs
- Using random numbers
- 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
- Random number generation
- 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
- The RSA algorithm
- 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
- Some further key management challenges
- Certificates
- Certificates and PKI
- X.509 certificates
- Chain of trust
- PKI actors and procedures
- Certificate revocation
- Symmetric encryption
Common software security weaknesses
- Time and state
- Race conditions
- File race condition
- Time of check to time of usage – TOCTTOU
- TOCTTOU attacks in practice
- Insecure temporary file
- File race condition
- Race conditions
- Errors
- Error and exception handling principles
- Exception handling
- In the except block. And now what?
- Empty except block
- Lab – Exception handling mess
Wrap up
- Secure coding principles
- Principles of robust programming by Matt Bishop
- Secure design principles of Saltzer and Schroeder
- And now what?
- Software security sources and further reading
- Python resources
