Why is Secure Coding Important?
Secure coding demonstrates a changing shift in responsibility by literally naming the developer as responsible for code security rather than a security team. This also paves the way for the Shift-left security concept that is already being widely adopted as part of the Software Development Life Cycle (SDLC) best practices.
Secure coding introduces an abstraction layer that scans existing code and any new code as it is committed into a code repository. It helps enforce best practices that, in turn, enforce production-ready code standards as well as prevent human error and developers “cutting corners” to meet strict deadlines.
Security Vulnerabilities that Affect Code
Creating software, applications or writing infrastructure as code requires cloud secrets to access and control cloud resources, and sensitive parameters saved to enable automation. There are countless scenarios that could introduce vulnerabilities into your code, and below we explore the most critical and frequent issues encountered:
Leaked Access Keys
All programming languages require programmatic keys to access and manage cloud resources. Secret keys control access to IAM roles that grant permissions to be executed against cloud resources. Secrets should always be encrypted, but a common mistake made is embedding access keys and secrets into local parameter stores or var files. It’s easy for a developer to inadvertently commit these secrets to a code repository, especially if troubleshooting the code. If your chosen repo is public, any published secrets can be used by anyone in the world.
Hardcoded Application Secrets
Each application has an embedded configuration dataset that details the security parameters the application uses against associated apps. This might include database login credentials, database parameters, middleware configuration variables, or access details for front/back end web application services. The parameters and secrets should be encrypted and never written in plain text, but some applications only use file system permissions to protect unauthorized users from reading the configuration. If features like .gitignore is not used in the code committal, the file will be saved in plaintext.
Secure Coding Best Practices
Protecting and securing code to industry standards is extremely challenging to achieve. Here are the top secure code best practices to defend your workload against compromise.
- Visibility and Monitoring: Without secure coding protection, it’s extremely difficult to know exactly what data is saved to a code repository. Automated detection monitoring scans the repository looking for vulnerabilities and if any issues are encountered, alerts are triggered ready for triaging. Map and monitor hidden sensitive assets, codebases, logs, and other sensitive intellectual property that may be left exposed to public facing repositories.
- Security Automation: Automated secret detection eliminates the painstaking and repetitive process of having to manually search for code security vulnerabilities. Automated engines scan the repo using ML trained detectors to improve success rates, and pre-commit checks will identify issues before the code is committed to source control.
- Logs and Alerts: Secrets can unintentionally be included in log entries, therefore automated protections should target logs. Additionally, it’s critical to ensure verbose logging is enabled locally for custom applications, making it possible to monitor out-of-sight assets, but never check into the code repository.
- Block Reflected XSS: Protecting against non-persistent or reflected XSS attacks prevents malicious scripts being committed into source control. In turn, this protects users against the execution of targeted malicious HTML or JavaScript.
- Mitigate Misconfiguration: Human error and mistakes are an inevitability of coding, and secure coding best practices demand the ability to remediate any issues rapidly. Security lapses should be fixed immediately and all traces removed from the history of the repo.
- Protecting Secrets and Data: Secure coding protects against secrets and business data from leaking into the public domain. This includes passwords, API keys, Tokens, Credentials, PCI, PII, and PHI data. The solution should meet these OWASP recommendations as standard: 2017 – Broken Authentication, 2017 – Sensitive Data Exposure, 2017 – Broken Access Control, 2017 – Security Misconfiguration.
- Harnessing the Power of AI/ML: The scope of threats is immense, simplifying the task by using AI/ML datasets to train detectors to automatically identify both known and unknown code security risks.
Secure Coding Techniques
There are countless techniques that can be introduced to protect code and business data. The fundamentals of secure coding must cover mobile devices, servers, and embedded applications.
Here are some of the top secure coding techniques:
- Enforce Code Obfuscation: Where possible, protect your code with techniques such as code minification and code obfuscation.
- Avoid Cutting Corners: Don’t be tempted to take shortcuts. Developers have tight deadlines, but it’s essential to deliver production-ready code even if this incurs delays.
- Code Reviews: There is still a place for peer code reviews on major projects, allowing developers to bounce ideas off each other. Additionally, it gives the opportunity for additional experts to critique the code.
- Create a Culture of Security: Culture change is very difficult to achieve and it’s something that takes time to embed within the company. Taking the first steps towards the entire team promoting a security first narrative is critical to success.
- Document Standards: Secure coding standards must be documented and shared on a private repo. Writing down the rules gives the developer the opportunity to review and helps to drive culture change.
- Validate External Data Sources: Sometimes it makes sense to use modules and code that is already written. Validate that your sources are legitimate, cross-check downloads with SHA authentication and ensure any data pulled is encrypted and valid.
- Use Threat Modeling: Threat Modeling introduces a multistage process that examines code for weakness and vulnerabilities throughout the Software Development Process.
- Use Automated Tools Within CI/CD: Enforcing security standards is very hard to do effectively, consider investing in automated tools like Check Point CloudGuard Spectral that do all the hard work for you.
Secure Coding with CloudGuard Spectral
CloudGuard Spectral by Check Point is a professional automation tool that validates and enforces secure coding best practices. It prevents developers and DevOps from making costly mistakes by using automated routines to discover, identify and predict the vulnerabilities inyour code, providing powerful shift-left provenance from code to cloud.
Supercharge your IaC and CI/CD with end to end secret and misconfiguration scanning across your SDLC. Eliminate public blindspots by enforcing security policies uniquely matched to your business. Schedule a demo of CloudGuard Spectral to uncover security concerns you most likely not aware of, and learn how to promote a developer first security narrative throughout the business.
Feedback