Web application security masterclass in Python

Your Web 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.
The curriculum goes through the common Web application security issues following the OWASP Top Ten but goes far beyond it both in coverage and the details.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.
 

DAY 1
Cyber security basics

What is security?
Threat and risk
Cyber security threat types – the CIA triad
Consequences of insecure software

The OWASP Top 10 2021
A01 – Broken Access Control

Access control basics
Missing or improper authorization
Failure to restrict URL access
Lab – Failure to restrict URL access
Confused deputy- Insecure direct object reference (IDOR)- Path traversal- Lab – Insecure Direct Object Reference- Path traversal best practices- Authorization bypass through user-controlled keys- Case study – Authorization bypass on Facebook- Lab – Horizontal authorization

File upload- Unrestricted file upload- Good practices- Lab – Unrestricted file upload

Open redirects and forwards- Case study – Unvalidated redirect at Epic Games- Open redirects and forwards – best practices

Cross-site Request Forgery (CSRF)- Lab – Cross-site Request Forgery- CSRF best practices- CSRF defense in depth- Lab – CSRF protection with tokens

A02 – Cryptographic Failures

Information exposure- Exposure through extracted data and aggregation- Case study – Strava data exposure- Data exposure best practices- Data masking- Privacy violation   - Privacy essentials   - Related standards, regulations and laws in brief   - Privacy violation and best practices- System information leakage   - Leaking system information   - Exposure through debug information   - Exposure through files and directories- Information leakage through side channels   - Exposure through side channels   - Side channels and covert channels- Information exposure best practices
Cryptography for developers- Cryptography basics- Cryptography in Python- Elementary algorithms   - Random number generation     - Pseudo random number generators (PRNGs)     - Cryptographically strong PRNGs     - Seeding     - Using virtual random streams     - Weak PRNGs     - Using random numbers     - Lab – Using random numbers in Python     - True random number generators (TRNG)     - Assessing PRNG strength     - Case study – Equifax credit account freeze

DAY 2
A02 – Cryptographic Failures (continued)

Cryptography for developers- Elementary algorithms   - 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      - Some further key management challenges

Certificates- Certificates and PKI- X.509 certificates- Chain of trust- PKI actors and procedures- Certificate revocation

Transport security- Transport security weaknesses- The TLS protocol   - TLS basics   - TLS features (changes in v1.3)   - The handshake in a nutshell (v1.3)   - TLS best practices   - Lab – Using a secure socket in Python   - HTTP Strict Transport Security (HSTS)

A03 – 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

DAY 3
A03 – Injection (continued)

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- Output sanitization- Encoding challenges- Unicode challenges- Lab – Encoding challenges- Validation with regex

HTML injection – Cross-site scripting (XSS)- Cross-site scripting basics- Cross-site scripting types   - Persistent cross-site scripting   - Reflected cross-site scripting   - Client-side (DOM-based) cross-site scripting- Lab – Stored XSS- Lab – Reflected XSS- Case study – XSS in Fortnite accounts- XSS protection best practices   - Protection principles – escaping   - XSS protection APIs in Python   - XSS protection in Jinja2   - Lab – XSS fix / stored   - Lab – XSS fix / reflected   - Client-side protection principles   - Additional protection layers – defense in depth

A04 – Insecure Design

The STRIDE model of threats
Secure design principles of Saltzer and Schroeder- Economy of mechanism- Fail-safe defaults- Complete mediation- Open design- Separation of privilege- Least privilege- Least common mechanism- Psychological acceptability

Client-side security- Same Origin Policy   - Simple request   - Preflight request   - Cross-Origin Resource Sharing (CORS)   - Relaxing the Same Origin Policy   - Lab – Same-origin policy demo- Frame sandboxing   - Cross-Frame Scripting (XFS) attacks   - Lab – Clickjacking   - Clickjacking beyond hijacking a click   - Clickjacking protection best practices   - Lab – Using CSP to prevent clickjacking- JSON security   - JSON validation   - JSON injection   - Dangers of JSONP   - JSON/JavaScript hijacking   - Best practices   - Case study – ReactJS vulnerability in HackerOne- XML security   - XML validation   - XML injection     - XPath injection     - Blind XPath injection

DAY 4
A05 – Security Misconfiguration

Configuration principles
Server misconfiguration
Python configuration best practices- Configuring Flask

Cookie security- Cookie security best practices- Cookie attributes

XML entities- DTD and the entities- Attribute blowup- Entity expansion- Lab – Billion laughs attack- External Entity Attack (XXE)   - File inclusion with external entities   - Server-Side Request Forgery with external entities   - Lab – External entity attack   - Case study – XXE vulnerability in SAP Store   - Preventing XXE   - Lab – Prohibiting DTD

A06 – Vulnerable and Outdated Components

Using vulnerable components
Assessing the environment
Hardening
Untrusted functionality import
Malicious packages in Python
Vulnerability management- Patch management- Vulnerability databases- DevOps, the build process and CI / CD- Dependency checking in Python- Lab – Detecting vulnerable components

A07 – Identification and Authentication Failures

Authentication- Authentication basics- Multi-factor authentication- Time-based One Time Passwords (TOTP)- Authentication weaknesses- Spoofing on the Web- Case study – PayPal 2FA bypass- User interface best practices- Lab – On-line password brute forcing

Session management- Session management essentials- Why do we protect session IDs – Session hijacking- Session fixation- Session invalidation- Session ID best practices- Session handling in Flask

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   - Case study – The Ashley Madison data breach      - The dictionary attack      - The ultimate crack      - Exploitation and the lessons learned   - Password database migration      - (Mis)handling None passwords   - Outbound password management      - Hard coded passwords      - Best practices      - Lab – Hardcoded password      - Protecting sensitive information in memory         - Challenges in protecting memory

DAY 5
A08 – Software and Data Integrity Failures

Integrity protection- Authenticity and non-repudiation- Message Authentication Code (MAC)   - MAC in Python   - Lab – Calculating MAC in Python- Digital signature   - Digital signature in Python

Subresource integrity- Importing JavaScript- Lab – Importing JavaScript- Case study – The British Airways data breach

A09 – Security Logging and Monitoring Failures

Logging and monitoring principles
Insufficient logging
Case study – Plaintext passwords at Facebook
Log forging- Lab – Log forging- Log forging – best practices- Case study – Log interpolation in log4j- Case study – The Log4Shell vulnerability (CVE-2021-44228)- Case study – Log4Shell follow-ups (CVE-2021-45046, CVE-2021-45105)

Logging best practices
Monitoring best practices
Firewalls and Web Application Firewalls (WAF)- Intrusion detection and prevention- Case study – The Marriott Starwood data breach

A10 – Server-Side Request Forgery (SSRF)

Server-side Request Forgery (SSRF)
Case study – SSRF and the Capital One breach

Web application security beyond the Top Ten

Code quality- Code quality and security- Data handling- Function return values   - Unchecked Return Value- Language elements    - Using dangerous language elements    - Using obsolete language elements    - Portability flaw    - Module injection and monkey patching    - Dangers of compile(), exec() and eval()    - The difficulties of sandboxing untrusted code- Object oriented programming pitfalls   - Accessibility modifiers      - Private attributes and name mangling   - Multiple inheritance and security   - Equality checking, None, and __eq__()   - Mutability- Memory and pointers   - Null pointers

Denial of service- Flooding- Resource exhaustion- Sustained client engagement- Infinite loop- Economic Denial of Sustainability (EDoS)- Amplification   - Other amplification examples- Algorithm complexity issues   - Regular expression denial of service (ReDoS)      - Lab – ReDoS in Python      - Dealing with ReDoS

Security testing

Security testing techniques and tools- Code analysis   - Security aspects of code review   - The OWASP Code Review methodology   - Static Application Security Testing (SAST)   - Lab – Using static analysis tools

Dynamic analysis- Security testing at runtime- Penetration testing- Stress testing- Dynamic analysis tools- Dynamic Application Security Testing (DAST)   - Web vulnerability scanners   - Lab – Using web vulnerability scanners   - SQL injection tools   - Lab – Using SQL injection tools- Fuzzing

Metasploit- Metasploit basics- Using Metasploit modules- Lab – Using Metasploit

Password cracking- Using password cracking tools- Lab – Password cracking with John the Ripper

Proxies and sniffing- Proxy servers and sniffers- Sniffing – tools and considerations- Lab – Using a proxy

Wrap up

Secure coding principles- Principles of robust programming by Matt Bishop

And now what?- Software security sources and further reading- Python resources