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: 위협 모델링은 애플리케이션 내에서 잠재적인 취약성과 보안 위험을 식별하기 위한 구조화된 연습입니다. 위협 모델링을 수행하면 조직은 애플리케이션에 대한 잠재적 위협에 더 효과적으로 대응할 수 있습니다.
• 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.
• 액세스 제어: 애플리케이션은 인증 및 권한 부여를 포함한 강력한 액세스 제어를 구현해야 합니다. 인증은 사용자의 신원을 확인하고 권한 부여는 인증된 사용자가 특정 작업을 수행하는 데 필요한 권한을 가지고 있는지 확인합니다.
• 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.
• 최소 권한: 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.
• 오류 처리: 애플리케이션은 발생할 수 있는 모든 오류를 명시적으로 처리하도록 설계되어야 합니다. 그렇지 않으면 예기치 않은 입력이나 동작으로 인해 애플리케이션이 충돌할 수 있습니다.
• 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.