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SCA
10 Dimensions of Python Static Analysis
Python static analysis, also known as "linting", is a crucial aspect of software development. It involves inspecting your Python code without running it to identify potential bugs, programming errors, stylistic issues, or non-adhering patterns to predefined coding standards. It also helps identify vulnerabilities early in the development process, reducing the chances of deploying insecure code into production.
Available Now: Veracode Scan for JetBrains IDEs
Veracode Scan for VS Code was one of the big hits on the expo floor at the RSA Security conference in May this year. People liked the integration of Veracode Static, Veracode SCA, and Veracode Fix into a single extension, giving developers the tools to scan their code and resolve problems with AI assistance while they are actively developing code.
Software Composition Analysis [Security Zines]
For those feeling code-conscious about shady dependencies lurking in their apps, Software Composition Analysis is the software security wellness check you need!
OSV Scanner vs npm-audit: A detailed comparison of SCA tools
The widespread adoption of external libraries and packages in the modern application development process introduces potential security risks that could impact the entire application. To address this, Software Composition Analysis (SCA) tools like npm-audit and OSV Scanner play an important role.
How Software Composition Analysis (SCA) Addresses President Biden's Executive Order (EO) 14028
EO 14028 is bringing a lot of new security documentation requirements with it. Here's how SCA can help with creating that documentation.
10 Popular SCA Tools to Protect Your Code in 2024
Software Composition Analysis (SCA) tools have been around since 2002, and they are now more critical than ever for identifying vulnerabilities in your codebase's libraries, frameworks, and third-party components. According to a Capterra report, 61% of businesses have been affected by a supply chain threat in the last year. If you’re one of the lucky 39%, Capterra suggests it really came down to luck - as nearly all companies use at least one third-party vendor.
Prioritize vulnerability remediation with Datadog SCA
Software Composition Analysis (SCA) is the practice of identifying the open source libraries your code depends on. By using SCA, you can analyze these dependencies and determine whether they are affected by any known vulnerabilities, contain malicious code, introduce licensing risk, or are poorly maintained. SCA helps teams understand their software’s dependencies and the security implications of using them so that they can safely build on and innovate with open source code.
Introduction to Software Composition Analysis and How to Select an SCA Tool
Software code is constantly growing and becoming more complex, and there is a worrying trend: an increasing number of open-source components are vulnerable to attacks. A notable instance was the Apache Log4j library vulnerability, which posed serious security risks. And this is not an isolated incident. Using open-source software necessitates thorough Software Composition Analysis (SCA) to identify these security threats.
Understanding Supply Chain Risk - Using SCA to protect your application
Understanding our supply chain means understanding all the components that make it. But this is harder than it appears. Open-source components make up 80 - 90% of our application's source code, but we must also remember that our open-source components are also made from open-source components, it's like supply chain inception. SCA or Software Composition Analysis is a security tool that looks at your entire supply chain and outlines vulnerabilities, including transitive or downstream dependencies.