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: 脅威モデリングは、アプリケーション内の潜在的な脆弱性とセキュリティ リスクを特定するための構造化された演習です。 脅威モデリングを実行することで、組織はアプリケーションに対する潜在的な脅威に適切に対処できるようになります。
• 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.
• アクセス制御:アプリケーションは、認証や承認を含む強力なアクセス制御を実装する必要があります。 認証はユーザーの ID を検証し、承認は認証されたユーザーが何らかのアクションを実行するために必要な特権を持っていることを検証します。
• 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.
• 最小権限: 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.
• エラー処理:アプリケーションは、発生する可能性のあるエラーを明示的に処理するように設計する必要があります。 そうしないと、予期しない入力や動作によってアプリケーションがクラッシュする可能性があります。
• 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.