
Developing trustworthy AI: 9 key threat categories
CSA’s AI Controls Matrix can help development and AppSec teams distill priorities for securing the AI software supply chain.
Learn More about Developing trustworthy AI: 9 key threat categoriesCode scanning is the automated analysis of source code to identify security vulnerabilities, coding errors, and quality issues early in the software development lifecycle. It helps detect flaws such as injection points, insecure configurations, and logic errors before code is deployed to production.
Code scanning is a foundational practice in modern application security. It is often used in secure DevOps (DevSecOps) pipelines to ensure that code is safe, compliant, and high-quality.
Software vulnerabilities often originate in source code and, if left undetected, can become exploitable weaknesses in production systems. Code scanning helps:
Without code scanning, vulnerabilities may only be discovered post-deployment, increasing remediation time, cost, and potential business impact.
Code scanning tools operate by statically analyzing source code to find security and quality issues without executing the code. They typically:
Advanced tools may also include AI-based analysis, taint tracking, and support for multiple programming languages
Term | Focus Area | Key Difference from Code Scanning |
---|---|---|
SAST | Security-focused static scanning | SAST is a subset of code scanning with a security lens. |
DAST | Runtime vulnerability scanning | DAST tests running applications, not source code. |
Dependency Scanning | Third-party component risks | Focuses on external libraries, not custom code. |
Code Review | Manual code inspection | Code scanning is automated, scalable, and consistent. |
CSA’s AI Controls Matrix can help development and AppSec teams distill priorities for securing the AI software supply chain.
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