Secure Coding & Design Best Practices in Python

Secure coding means writing software that resists threats like hacking and data leaks by following guidelines and keeping security updated throughout development.

Define the course scope by focusing on code-level security, outlining secure coding practices amid layered enterprise security, while skipping infra, cloud, and network configurations.

Assess your fit: experienced coders seeking to ship secure code and gain confidence through experimentation should take this course; beginners should start with basics.

Learn secure design principles introduced by Saltzer and Schroeder, including economy of mechanism, complete mediation, least privilege, and open design, to embed security from the start.

Learn the economy of design principle, emphasizing minimal, modular mechanisms and trusted algorithms to reduce complexity, verify correctness, and minimize security risks at system edges.

Learn how fail safe defaults deny access by default and require explicit permissions to prevent security breaches, ensure secure failures, and protect resources.

Implement complete mediation by routing all access requests through a trusted module, enforcing authorization and validation for every resource, complementing failsafe defaults and preventing direct access.

Adopt the open design principle to promote transparency, independence from secrecy, and community-driven evaluation of security mechanisms for robust, well-documented systems.

Apply the principle of least privilege by granting users and processes only the minimum permissions necessary to perform tasks.

Apply separation of privilege to require multiple entities or conditions for critical actions, reducing misuse risk. Distinguish it from least privilege and illustrate dual-control ideas like two keys.

Explain psychological acceptability by ensuring security measures are precise and easy to use, with clear messages, and by favoring simple or biometric authentication over burdening passwords.

Learn how least common mechanism reduces security risk by minimizing shared mechanisms, using user-centric libraries, and securing password management and cryptographic functions.

Explore the work factor principle by comparing attacker resources to security costs, calculate brute-force implications for passwords, and guide design decisions to reduce breach risk.

Explain the compromise recording design principle as a practical security guideline that favors recording breaches over perfect prevention, and show how breach records help mitigate vulnerabilities.

Discover secure design principles in Python, including economy of mechanism, failsafe defaults, complete mediation, least privilege, separation of privilege, least common mechanism, psychological acceptability, work factor, and compromise recording.

Explore ten secure coding and design best practices for web apps, covering strong authentication, access control, secure configuration, encryption, secure storage, and safe input handling.

Strengthen web application security with strong authentication to prevent unauthorized access. Explore how weak passwords, lack of multi-factor authentication, insecure protocols like http basic authentication, and account lockout enable attackers.

Improve password validation by enforcing length and character rules—at least eight characters, one uppercase, one lowercase, and one special character—using regex, then proceed with authentication to deter brute force.

Implement strong password policies and enable MFA using various methods (sms, email, authenticator apps, hardware tokens), with https and oauth/openid connect for secure authentication. Enforce an account lock policy with failed attempts, gradually increase lockouts, and apply rate limiting to thwart brute-force attacks.

Enforce strong password policies and implement multifactor authentication with SMS, email verification, authenticator apps, or hardware tokens, plus HTTPS, OAuth 2.0 or OpenID Connect, lockout, and rate limiting.

Advance your understanding of access control by exploring authorization across networks, systems, and data, comparing role-based, attribute-based, and relationship-based models, and identifying common misconfigurations to prevent privilege escalation.

Validate authorization before database queries to ensure admins or owners can access profiles, while others are unauthorized; apply similar checks to transactions.

Adopt secure configuration by avoiding default or weak settings and disabling unnecessary services. Enforce secure permissions and use https to protect data from unauthorized access.

Demonstrates implementing secure checks before reading a file, enforcing owner-based permissions, and applying security hardening and secure configuration across the application stack.

Protect sensitive data by encrypting storage, securing password handling, and masking details in logs and interfaces. Use transport layer security, such as tls, to protect data in transit and credentials.

Learn how to replace MD5 with bcrypt for password hashing in Python, generate a salt, store the salt with the hash, and strengthen the protection of user credentials.

learn how to securely select and evaluate third-party components for web apps, keep dependencies up to date, avoid malicious or untrusted sources, manage dependency chains, and tighten insecure default configurations.

Ensure secure Python projects by using trusted and updated libraries, checking community support, and updating dependencies to address vulnerabilities when fetching data from URLs.

Explore serialization and deserialization, how data transfers between systems and is stored in a persistent format, and learn to prevent security vulnerabilities like remote code execution by validating untrusted data.

Demonstrates secure deserialization in Python by replacing marshal loads with json loads, showing errors on improper formats, and emphasizing encryption and access control to protect sensitive data.

Learn how precise logging and real time monitoring strengthen incident response and threat detection, avoiding gaps from incomplete or excessive logs and mitigating risks associated with sensitive data exposure.

Implement comprehensive, structured logging for fund transfers by recording action, sender, recipient, amount, and timestamps to improve monitoring, analysis, and incident response while avoiding sensitive data.

This lecture highlights why server side request validations are essential to protect user data, prevent SQL injection and XSS, and enforce robust input validation, data sanitization, and file upload checks.

Explore how to defend Python applications against injection and inclusion by validating and sanitizing untrusted input, preventing SQL injection, command injection, remote code execution, and file inclusion risks.

Demonstrates how sql injection can exploit a python login application programming interface by concatenating email and password in a query. Shows how to fix it with parameterized queries using placeholders.

Maintain a secure application by enforcing secure session management, protecting configuration files, encrypting sensitive values, avoiding hardcoded secrets, and applying security patches while validating text-to-code conversions.

Explore the OWASP top ten security risks—broken access control, cryptographic failures, injection, insecure design, misconfiguration, vulnerable components, and identification and authentication failures—to guide secure coding practices.

Explore the OWASP Juice Shop demo to uncover vulnerabilities like broken access control, insecure direct object references, SQL injection, and typosquatting in libraries.

Implement a secure software development life cycle that embeds security from compliance and risk assessment through architecture review, design, secure coding, automated and manual static analysis, and ongoing vulnerability checks.

Leverage both manual review and automated static analysis to detect bugs, security vulnerabilities, and technical debt, using tools like SonarQube and AI-assisted code corrections.

Fix vulnerabilities in python code after analysis, implement secure coding practices, and re-run analysis to verify remediation, while improving design guided by SonarCube and SonarLint.

Conduct regular vulnerability checkups to identify new threats and apply patches for software, dependencies, frameworks, and libraries. Use tools like OWASP dependency check and OpenVAS, and train with security experts.

Learn to embed security into every stage of the python application's lifecycle through secure SDLC practices, from requirements to maintenance, with code analysis, corrective actions, and vulnerability checks.