As applications become more complex, so does the task of securing them. While the source code making up applications consists of proprietary code, a great deal of it is also third-party, open source code. Development and security teams looking to release secure code while also maintaining a rapid pace of development, need to therefore combine static application security testing (SAST) and software composition analysis (SCA) as part of a comprehensive software security strategy.

The Payment Card Industry Data Security Standard, also known as PCI DSS is a thorough process that reviews a company’s systems and policies for handling and storage of sensitive consumer cardholder data.

Jazzer, our fuzzer for the JVM, is already being used with several JVM languages like Java and Kotlin. Recently, a member of the community asked us whether Jazzer can also fuzz Clojure code. The answer is yes, but it wasn't obvious how to set things up. So we've built a small helper library, jazzer-clj, which contains everything you need to get started with Jazzer for Clojure. There's also an example project to demonstrate the setup.

Application Programming Interface (APIs), allow services to communicate with each other. Naturally, applications that are interconnected through many APIs, require thorough security testing, as each connection could potentially include software vulnerabilities. Since there are different methods to test these junctions, I want to briefly discuss the benefits and weaknesses of the most commonly used API testing methods in this article.

Mobile application security testing (MAST) covers a wide range of topics, including authentication, authorization, data security, session management, and vulnerabilities for hacking. The mobile AST market is made up of buyers and sellers of products that identify vulnerabilities and apps used with mobile platforms during or post-development.

Ever since the public exploit of the Log4Shell remote code execution (RCE) vulnerability became known on December 10, 2021, security teams have been scrambling to understand the risk to their environments. Part of that scramble has been to ascertain which tools are best positioned to help detect the vulnerability. Which approaches are most effective and where do they fall short?

To help contain the damages that arise from the log4j vulnerability, Code Intelligence collaborated with Google’s Open Source Security Team. Together, we implemented effective bug detectors for Remote Code Execution Vulnerabilities (RCEs) to Google’s open source fuzzing framework, OSS-Fuzz.

Starting in early 2021, Snyk Code and became available as a freemium offering for Snyk users. Snyk Code helps developers quickly and accurately find, prioritize, and fix security flaws in proprietary code. With detailed remediation guidance at every stage of the software development lifecycle (SDLC), from the developer’s environment (IDE) to continuous integration and development (CI/CD) pipelines, Snyk Code revolutionizes static application security testing (SAST).