Secure Coding Practices for Developers

Secure Coding Best Practices

Secure coding is the foundation of an effective application security (AppSec) program. The following best practices enable a development team to avoid common vulnerabilities and promote a culture of strong AppSec:

• Security Training: Developers need to be aware of common vulnerabilities in order to avoid them. Providing regular training on widespread vulnerability classes and secure coding best practices helps to empower developers and create a culture of strong AppSec within the organization.
• Threat Modeling: 威脅建模是一種結構化練習，用於識別應用程式中潛在的脆弱性和安全風險。 執行威脅建模使組織能夠更好地解決應用程式可能面臨的威脅。
• Input Validation and Sanitization: Input validation ensures that user-provided inputs meet expectations for length, content, and formatting. Input sanitization removes potentially dangerous content from user-provided input before processing it.
• 存取控制：應用程式應實施強大的存取控制，包括身分驗證和授權。 身份驗證驗證使用者的身份，而授權驗證經過身份驗證的使用者是否具有執行某些操作所需的權限。
• Data Security: Data should be secured both at rest and in transit. This includes the use of data encryption with secure management of cryptographic keys.
• Secrets Management: Applications may have access to various secrets, including passwords, cryptographic keys, API keys, and more. These secrets should be securely stored and not hardcoded into application code where they are at risk of potential exposure.
• 最小權限： The principle of least privilege states that users, applications, etc., should only have the minimum set of permissions needed to do their job, This principle should be designed into an application’s access control and privilege management system.
• 錯誤處理：應用程式應設計為明確處理它遇到的任何可能的錯誤。 否則，意外的輸入或行為可能會導致應用程式崩潰。
• Code Reviews: Code reviews are an essential component of an AppSec program. Having someone other than the developer review the code increases the probability that overlooked issues will be detected and remediated.
• Regular, Automated Vulnerability Scanning: Automated scanners can identify software vulnerabilities, hardcoded secrets, and other security risks within an application’s code. These tools should be used throughout the software development process and after deployment to enable potential security risks to be quickly identified and remediated.
• Automate Security Scanning in CI/CD Pipelines: Automated scanning can be built into automated CI/CD pipelines to decrease friction and improve test coverage. Before a commit is accepted to the repo, it can be automatically subjected to static and dynamic code analysis to identify potential vulnerabilities.
• Infrastructure as Code (IaC): IaC automates the process of configuring software and systems. This streamlines the deployment process and reduces the risk that human error will introduce security vulnerabilities.
• Leverage AI/ML: The evolution of artificial intelligence and machine learning (AI/ML) has dramatically expanded the capabilities of automated security scanning tools. Taking advantage of these new features enables vulnerabilities to be identified and remediated more quickly and easily.