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NEW QUESTION # 122
SinCaire is a software development company that develops web applications for various clients.
To measure the successful implementation of DevSecOps, the organization enforced U.S.
General Service Administrator (GSA) high-value DevSecOps metrics. Which of the following metrics implemented by SinCaire can measure the time between the code commit and production, and tracks the bug fix and new features throughout the development, testing, and production phases?
Answer: B
Explanation:
Change lead time measures the duration between a code commit and its successful deployment into production. This metric tracks how efficiently new features, bug fixes, and changes move through development, testing, and release stages. It is a key DevSecOps performance indicator used to assess pipeline efficiency and the effectiveness of automation and security integration.
Mean time to recovery focuses on restoring service after incidents, change volume measures the number of changes rather than delivery speed, and time to value is a broader business metric.
Change lead time directly reflects how well DevSecOps practices enable rapid yet secure delivery, making it the correct metric for measuring commit-to-production flow across all phases.
NEW QUESTION # 123
Emma, a DevSecOps engineer, is responsible for maintaining the security and stability of her organization's Jenkins environment. She is concerned that running build jobs directly on the Jenkins controller could expose the system to security risks, such as potential execution of untrusted or malicious build scripts on the controller, increased risk of system instability due to resource-intensive build jobs, unauthorized users modifying job configurations and running harmful commands. To mitigate these risks, Emma needs a solution that isolates build execution from the Jenkins controller while maintaining operational efficiency. Which approach should Emma implement to improve the security of the Jenkins infrastructure?
Answer: B
Explanation:
Running builds on Jenkins agents instead of the controller isolates build execution: untrusted build scripts never run on the controller, resource-intensive jobs don't destabilize it, and the attack surface on the controller is minimized-directly addressing Emma's concerns while keeping operations efficient. Sandboxing on the controller still executes code on it, and disabling all scripting is impractical.
NEW QUESTION # 124
Alex Hales recently joined TAVR Software Solution Pvt. Ltd. As a DevSecOps engineer. To automatically detect security loopholes in the web applications while building and testing them, he integrated OWASP ZAP DAST Plugin with Jenkins. How can Alex uniquely identify every build in the project?
Answer: D
Explanation:
Jenkins automatically assigns a unique identifier to each build using the environment variable BUILD_ID. When integrating OWASP ZAP with Jenkins, appending ${BUILD_ID} to output filenames or reports ensures that every scan result corresponds to a specific build execution. This avoids overwriting previous reports and allows traceability between build artifacts and security findings. Variables such as ${ZAPROXY_HOME} refer to installation paths, not build uniqueness, while ${Profile_ID} and ${zap_scan} are not standard Jenkins variables for uniquely identifying builds. Using ${BUILD_ID} supports better auditing, historical analysis, and correlation between detected vulnerabilities and the exact build in which they were found, which is critical during the Build and Test stage of a DevSecOps pipeline.
NEW QUESTION # 125
Kenji Watanabe, a DevSecOps engineer at a Tokyo gaming studio, needs a testing tool that combines code instrumentation with live traffic analysis, so it can pinpoint the exact line of vulnerable code triggered when a QA tester clicks through the application during functional testing. Which approach should Kenji choose?
Answer: A
Explanation:
IAST works by instrumenting the application with agents that monitor code execution from within while the application is exercised through normal functional or QA testing, allowing it to correlate detected vulnerabilities directly back to specific lines of source code in real time -- precisely what Kenji needs. Penetration testing is typically a manual or semi-manual black-box/gray-box assessment performed by security testers simulating real-world attacks, and does not inherently tie findings to exact source lines through instrumentation during routine QA clicks. Threat modeling is a design-time planning activity performed before code execution. Chaos engineering intentionally injects failures into production or production-like systems to test resilience, not to detect code-level vulnerabilities during functional testing. Because Kenji wants instrumented, line- level detection during live QA interaction, IAST is correct.
NEW QUESTION # 126
(Craig Kelly has been working as a software development team leader in an IT company over the past 8 years.
His team is working on the development of an Android application product. Sandra Oliver, a DevSecOps engineer, used DAST tools and fuzz testing to perform advanced checks on the Android application product and detected critical and high severity issues. She provided the information about the security issues and the recommendations to mitigate them to Craig's team. Which type of security checks performed by Sandra involve detection of critical and high severity issues using DAST tools and fuzz testing?)
Answer: C
Explanation:
Dynamic Application Security Testing (DAST) and fuzz testing require a running application in order to actively probe for vulnerabilities such as injection flaws, authentication bypasses, and improper input handling. These techniques are therefore performed after the application has been built and deployed to a testing environment, categorizing them astest-time checks. Commit-time and build-time checks rely primarily on static analysis and dependency scanning and do not exercise application behavior at runtime.
Deploy-time checks focus on configuration validation rather than aggressive attack simulation. Test-time checks are specifically designed to uncover critical and high-severity vulnerabilities by mimicking real-world attack scenarios. Performing DAST and fuzz testing during this stage allows teams to detect exploitable flaws before production release, significantly strengthening application security.
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NEW QUESTION # 127
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