AI–powered TypeScript Code Checker

With the addition of AI-driven TypeScript checkers, teams can uncover and resolve more advanced issues earlier in the secure software development lifecycle (SSDLC). These tools use machine learning models trained on vast amounts of open source code, learning symbolic rules for detecting and fixing potential flaws. By drawing on this collective knowledge, AI-based engines can often catch vulnerabilities and code quality problems that might slip through peer reviews or pair programming sessions. As a result, developers can remediate issues long before deployment, reducing risks to both production environments and end-users.

Snyk TypeScript Checker can surface a variety of problems: from security vulnerabilities (e.g., SQL injection, weak cryptography, insecure password handling) to more subtle semantic issues involving data flow, configuration errors, or code anti-patterns.

An essential principle of DevSecOps is “shifting left,” which means identifying and addressing security flaws earlier in the software development cycle. One effective way to achieve this is by integrating a TypeScript code scanner into your continuous integration and continuous delivery (CI/CD) workflow. Incorporating static analysis directly into the IDE helps developers spot vulnerabilities in TypeScript as they write code, allowing security concerns to be resolved at the source.

Our AI-powered checker is trained on extensive open-source data and expert curation, offering quick detection and actionable remediation advice that goes beyond peer reviews. This means developers catch and fix deeper bugs earlier, reducing time spent in QA and improving code quality in the long run.

As TypeScript is a superset of JavaScript, so as long as your JavaScript program doesn’t have any syntax errors then it is also a TypeScript program. Although generally, not all TypeScript programs are JavaScript programs, as TypeScript has some syntax of it’s own. Check out this guide for more detail about the difference between JavaScript and TypeScript.

Snyk TypeScript code checker goes beyond basic syntax and type checks performed by tsc. It includes static analysis for potential logic issues, semantic problems, and sometimes security vulnerabilities. In contrast, tsc focuses purely on compiling TypeScript—checking types, syntax, and generating JavaScript.

Linter tools are a great way to check the Syntax of your TypeScript code. A good open source option for linting is TypeScript ESLint. ESLint uses static analysis to find issues in your code, and allows the creation of lint rules to define how your code should look and behave.

Integrating a TypeScript code checker into the existing developer workflow is a great way to fix code issues earlier, while also helping developers learn about best practices. This can make a significant impact on the quality and security of TypeScript code that developers write going forward. More maintainable code can also improve the customer experience because there are fewer bugs and technical debt to deal with in the future.

When it comes to static application security testing (SAST) with a TypeScript code checker, it’s important to choose a developer-first tool that integrates into developer workflows and produces minimal false positives in scan results. A SAST tool also needs to take a comprehensive approach for scanning source code, and be able to combine with linters to check code syntax and style.

The most common types of SAST security analysis are:

• CONFIGURATION: Ensures that application configuration files follow security best practices and policies.

• SEMANTIC: Examines code contextually to estimate what the developer intended, and check whether the code syntax differs.

• DATA FLOW: Tracks the flow of data from insecure sources to ensure it’s cleansed before consumption by the TypeScript application.

• STRUCTURAL: Determines whether there are inconsistencies with implementing language-specific best practices and cryptographic techniques.

Snyk TypeScript code checker is a comprehensive vulnerability database to identify security issues at the code level, as well as known vulnerabilities introduced via open source dependencies. Vulnerability databases help developers stay on top of the latest security exploits as they’re discovered, without spending endless hours researching the current cyber threat landscape. This type of data-driven security works in tandem with threat intelligence to improve the overall security posture of your organization.

Finally, detecting TypeScript code security issues is only half the battle. An effective code checker solution will identify flaws, while also giving developers the insights they need to remediate them. This should include the precise source of the issue, and any known publicly available fixes for both security flaws and code anti-patterns.

TypeScript code security can be described using the CIA triad — confidentiality, integrity, and availability. The CIA triad is often used as a model for secure systems and to identify possible vulnerabilities and fixes. Today, applications consist of 80 to 90% open source dependencies. But the remaining 10 to 20% is critical: this code reflects your personal IP, and there is no open source community helping you keep it secure. The best practice is to accept the work of the open source community by scanning and updating software dependencies in your project using scanners like Snyk Open Source, while doing your part by scanning and fixing your code using Snyk Code.

Confidentiality

Secure software systems do not disclose information to parties that are not allowed to receive it. That includes malicious external actors as well as unauthorized internal stakeholders.

Integrity

Secure software systems make sure that data and processes are not tampered with, destroyed, or altered. Transactions succeed when all sub-transactions succeed, and the stored data does not contradict each other.

Availability

A secure system also needs to be able to be used in due time. Blocking a system by overloading parts of it renders the system useless and insecure.

TypeScript code quality is a subjective term, and it means something different to every development team. In general, however, the quality of code relates to how closely it follows commonly accepted coding standards and best practices, including:

• Reusability It’s best to write highly reusable code. For example, in object-oriented programming, it’s important to make classes and methods clean and modular so that code is easier to debug and scale across projects. Restricting access to certain reusable blocks of code through encapsulation can also improve security.

• Maintainability Along with being reusable, it’s important that TypeScript source code is maintainable. As a codebase grows, complexity and technical debt often increase, leading to bugs that are difficult to pinpoint and slow development in the long run. Automated code analysis and peer reviews can ensure that developers are only pushing highly maintainable code into production.

• Testability High-quality TypeScript code should support testing efforts. Along with writing modular code that makes automated testing easier, developers need to prioritize clear and up-to-date documentation. This allows test engineers to more easily understand the purpose of a particular code snippet.

• Consistency TypeScript code should be portable enough that it can run on any development, staging, or production environment without compatibility issues.

• Reliability Software should be designed for reliability from the start. Meaning developers need to proactively prevent technical debt from accruing when they push TypeScript code. Otherwise, software can become less reliable over time and have a decrease in availability, fault tolerance, data integrity, and ability to recover from outages. These lack of reliability can also have a negative impact on the security posture of an application.

Snyk TypeScript Checker can automatically run on every pull request or repository and serve as a CI/CD security gate.