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Integrate Microsoft Defender for Cloud with Endor Labs for reachability analysis and attack path visibility — available natively within the Defender for Cloud console. Prioritize what to fix without switching tools.
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The Cyber Resilience Act (CRA) sets mandatory security requirements for hardware and software. This blog covers key compliance objectives, challenges with OSS vulnerabilities, and best practices for maintaining security throughout the product life cycle.
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Get key insights from the 2024 Dependency Management webinar with Darren Meyer and Henrik Plate. We discuss how to prioritize vulnerabilities, navigate breaking changes, and leverage public vulnerability databases effectively.
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This blog covers key steps to simplify FedRAMP vulnerability management, helping you reduce risks and meet compliance timelines. It also provides practical tips to empower developers and streamline fixes for a smoother FedRAMP process.
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GitHub Actions are open source dependencies - secure them accordingly! Learn how to effectively manage the security risks associated with GitHub Actions with a proactive approach focusing on three key areas: visibility, hardening, and dependency management.
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Explore the five key categories of reachability and their practical applications in AppSec and development. Learn the differences between SCA and container scanning, and understand how various tools like Function-Level Reachability, Package Baselining, and Internet Reachability play crucial roles in identifying and prioritizing security risks.
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Explore the challenges of modern vulnerability management and the efficiency of the Vulnerability Exploitability eXchange (VEX) in our latest blog post. Learn how VEX helps identify and communicate the true exploitability of vulnerabilities, streamlining cybersecurity efforts in the face of overwhelming scanner findings.
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If you’ve been watching the software supply chain security space evolve, you likely know that a lot of the momentum and effort is coming out of the U.S. Federal government. This may seem surprising at first, but it shouldn’t be, when you account for the fact that the Federal government is one of the single largest procurers of technology and software in the world.
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Phantom dependencies are dependencies used by your code that are not declared in the manifest. If you miss them, they can sneak reachable risks into your application, lead to false positives, or inaccurate SBOMs. All very spooky. This article breaks down how phantom dependencies happen, and how to catch them.
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Learn why every SCA tool is wrong, and how to deal with it.
Join us for great networking, dinner and drinks, and see a presentation by Darren Meyer, Staff Research Engineer at Endor Labs.
With the rise of AI-fueled by Python-based libraries, it has become of paramount importance to scan Python-based projects and their dependencies for OSS vulnerabilities. Python relies on package managers like pip or conda to manage declared dependencies. Dependencies are declared in manifest files which the package manager uses to install the correct version of the required dependency. However, Python’s dependency management system coupled with its dynamic type nature makes it an especially challenging language to deal with.
Of particular focus is the phenomenon of phantom dependencies which are unreported dependencies in a project's manifest profile. These hidden dependencies, which are often provided dependencies (which is especially true for libraries such as tensorflow and pytorch which are essential for AI), challenge software composition analysis (SCA) of Python code, impacting the reliability of vulnerability results.
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