ECCouncil 312-97 Dumps

Kubernetes uses namespaces to logically isolate resources such as pods, services, and deployments. When an application like Jenkins is deployed into a specific namespace, the correct way to view the pods running in that namespace is by using the -n (or --namespace) flag with the kubectl get pods command. The command kubectl get pods -n jenkins instructs Kubernetes to list all pods in the “jenkins” namespace. The other options use invalid or unrelated flags that are not supported for namespace selection. Verifying pod status during the Release and Deploy stage is essential to ensure that applications have been deployed successfully and are running as expected before exposing services or proceeding to monitoring. This step supports deployment validation and operational readiness in Kubernetes-based DevSecOps environments.

By default, Brakeman returns a non-zero exit code when security warnings are detected, which can cause Jenkins builds to fail. The --no-exit-on-warn option modifies this behavior by instructing Brakeman toreturn an exit code of 0 even if warnings are found. This allows the CI pipeline to continue executing while still generating a security report that highlights vulnerabilities. This option is particularly useful when teams are initially integrating SAST tools and want visibility into security issues without immediately blocking builds. During the Build and Test stage, this approach supports gradual adoption of security enforcement, allowing teams to prioritize remediation efforts while maintaining delivery velocity. Over time, organizations can tighten policies by removing this option to enforce stricter build-breaking behavior once security baselines improve.

When changes are committed to a repository connected to an AWS Pipeline, the pipeline execution is triggered and monitored usingAmazon CloudWatch events. CloudWatch captures pipeline state changes, execution status, and approval notifications, enabling real-time monitoring and alerting. AWS Config tracks resource configuration changes, BinSkim is a binary analysis tool, and Security Hub aggregates security findings but does not directly track pipeline execution events. Integrating SonarQube into AWS Pipeline ensures static code analysis runs automatically upon commits, while CloudWatch provides visibility into pipeline activity. This setup strengthens security automation during the Code stage by ensuring every commit is analyzed and monitored.

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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.

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The Warnings Next Generation Plugin in Jenkins is designed tocollect, aggregate, visualize, and manage static analysis resultsproduced by various tools, including Brakeman. In this scenario, Dave uses Brakeman to scan Ruby on Rails applications for security vulnerabilities. Brakeman generates output files containing findings, and the Warnings Next Generation Plugin parses these results and presents them in a standardized, user-friendly format within Jenkins. This allows teams to track trends, enforce quality gates, and fail builds based on severity thresholds. The plugin does not inspect TypeScript code, validate compiler settings, or control Brakeman’s execution logic. Its role is purely to manage and display analysis results. Using this plugin during the Code stage improves visibility into security issues, supports decision-making, and helps enforce security standards across the development lifecycle.

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The secure communication principle focuses on protecting data as it moves between systems, services, and users. This is achieved by establishing and maintainingsecure trust relationships, which include strong authentication mechanisms, encryption, certificate management, and trusted communication channels. Preventing breaches and reducing attack surface are broader security objectives, not specific to communication security. Balancing default configuration settings relates to secure defaults rather than communication. Secure trust relationships ensure that only authenticated and authorized entities can exchange data and that information remains confidential and tamper-proof during transmission. Embedding this principle into DevOps culture ensures that secure communication practices are consistently applied across all stages of the DevSecOps pipeline.

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Jira usesAtlassian Query Language, commonly referred to as JQL, to search, filter, and manage issues. This query language allows users to create advanced searches using fields such as project, status, assignee, priority, and custom attributes. Although often informally called Jira Query Language, the official name among the given options is Atlassian Query Language. SQL and Java query language are unrelated and not used for issue searching in Jira. Using JQL during the Code stage improves traceability between source code commits, builds, and tracked issues, enabling teams to monitor progress, validate deployment status, and maintain alignment between development and delivery activities.

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Kubernetes clusters are managed and inspected using the kubectl command-line tool. To verify whether a Kubernetes cluster is functioning correctly, administrators commonly run kubectl version to confirm that both the client and server components are reachable and operational. This is followed by kubectl cluster-info, which displays information about the cluster’s control plane and core services. These commands together confirm API server availability, cluster connectivity, and basic health status. The other options list invalid command names such as kube, kubernetes, or kube-etcd, which are not used for standard cluster validation. Performing these checks during the Operate and Monitor stage helps quickly identify whether application issues stem from cluster-level problems or application-level misconfigurations. This supports faster troubleshooting and more reliable production operations.

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Bandit is a Static Application Security Testing (SAST) tool developed specifically for analyzingPython source code. It scans Python scripts and applications to identify common security issues such as use of weak cryptography, hardcoded passwords, unsafe use of functions like eval, and insecure imports. Bandit works by parsing Python Abstract Syntax Trees (ASTs) and applying a set of security-focused rules. It does not support Java, Ruby, or C++ code, which require different static analysis tools tailored to their respective languages. By integrating Bandit with Jenkins during the Build and Test stage, Allen enables automated detection of Python-specific security flaws as soon as code changes are introduced. This shift-left approach reduces remediation costs, prevents vulnerable code from progressing further in the pipeline, and improves overall application security posture.

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Jenkins automatically assigns a unique identifier to each build using the environment variableBUILD_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.

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Azure resource groups are created using the Azure CLI command az group create. The --name parameter specifies the resource group name, and --location defines the Azure region. Option A uses the correct CLI prefix (az), command group (group create), and valid parameters. Options B, C, and D are incorrect due to invalid command abbreviations or incorrect CLI prefixes (azure instead of az). Creating a resource group is a foundational step in the Release and Deploy stage, as it provides a logical container for AKS clusters, networking components, and related resources, enabling organized, secure, and manageable deployments.

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Chef InSpec executes compliance tests using the inspec exec command. When testing Azure infrastructure, InSpec requires a target specification using the -t flag with the Azure transport identifier azure://. The correct command is inspec exec inspec-tests/integration/ -t azure://. Options using exe instead of exec are invalid due to incorrect command spelling. Options that use the -it flag misuse command-line parameters that are not intended for target selection. Running InSpec tests in this way allows DevSecOps teams to validate that Azure resources comply with architectural, security, and regulatory requirements. Integrating these checks into the Build and Test stage ensures continuous compliance and reduces the risk of insecure infrastructure reaching production environments.

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The docker save command exports one or more Docker images to a tar archive by writing the image data to standard output (STDOUT). To redirect this output into a file, the > redirection operator is used. The correct syntax is docker save > .tar. In this scenario, the image repository name is centos, and the desired archive file is centos-all.tar, making option B correct. Options C and D incorrectly use input redirection (<) instead of output redirection. Option A includes a space in the filename (centos all.tar), which would be interpreted as two separate arguments and cause an error unless quoted. Saving images to a tar archive is a common operational task used for backups, transfers between environments, or offline analysis during the Operate and Monitor stage.

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Chef InSpec provides a command-line interface for creating and executing compliance profiles. To initialize a new profile with the required directory structure, metadata file, and example controls, the correct command is inspec init profile . In Jeremy’s case, running inspec init profile jyren-azureTests creates a new folder with all required artifacts needed to write and run Azure compliance tests. Options using prof are invalid abbreviations, and prefixing the command with chef is incorrect when using the InSpec CLI directly. Creating a structured InSpec profile during the Build and Test stage enables automated validation of infrastructure against architectural standards and security policies, supporting Infrastructure as Code security and continuous compliance practices.

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Jenkins plugins are distributed and installed as .hpi files. To manually install a plugin, administrators upload the .hpi file through the Jenkins Plugin Manager using the “Upload Plugin” option. This approach is commonly used in environments with restricted internet access or when custom plugin versions are required. .war files are used for deploying the Jenkins application itself, not plugins, while .zip and .conf files are not recognized plugin formats. Installing the InsightAppSec plugin allows Jenkins pipelines to automatically trigger dynamic application security scans during the Build and Test stage. This integration ensures that web applications are continuously evaluated for vulnerabilities before deployment, supporting proactive security testing and risk reduction.

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Azure Container Instances (ACI) exposes container logs via the Azure CLI using the az container logs command. To retrieve logs, you must provide the resource group and the container group name using the long-form parameters --resource-group and --name. Option A matches the correct CLI structure and parameter format: az container logs --resource-group ACI --name aci-test-closh. Options B and D incorrectly use single-dash forms (-resource-group and -name), which are not valid for these long option names. Options C and D incorrectly use azure instead of az; the Azure CLI command group is invoked with az, not azure. Getting logs after deployment review is a critical Operate and Monitor activity: it helps confirm the container started correctly, diagnose runtime errors, and validate that runtime protection (such as a RASP/micro-agent) is functioning. This visibility supports faster incident response and helps ensure the containerized workload remains secure and stable in its runtime environment.

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ThreatModeler’sAcceleratorcapability allows automatic generation of threat models directly from an organization’s live AWS environment. It connects to AWS services, analyzes deployed resources, and converts them into architectural diagrams and threat models without manual input. YAML-based orchestration tools and STRIDE per Element are methodologies used for modeling but do not automatically ingest live cloud configurations. Architect is a design construct, not an automation engine. Using Accelerator during the Plan stage enables proactive, continuous threat modeling, ensuring that evolving cloud infrastructure is always assessed for risk and security gaps.

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GitHub Code Scanning is a built-in security capability designed to automatically analyze source code for security vulnerabilities and coding errors. The primary and officially supported engine for GitHub Code Scanning isCodeQL. CodeQL works by converting source code into a database and running security queries to detect issues such as injection flaws, insecure coding patterns, and logic errors. William can enable CodeQL by configuring GitHub Actions with either the default or advanced CodeQL workflow. Once enabled, CodeQL scans are triggered on events such as code pushes and pull requests, and the results appear as code scanning alerts in the repository’s Security tab. Gauntlt is a security testing harness used mainly for infrastructure and application testing, GitMiner is used to discover sensitive data like secrets in repositories, and OWASP ZAP is a dynamic application security testing tool used against running applications. None of these tools configure GitHub’s native Code Scanning feature. Therefore, CodeQL is the correct tool to set up GitHub Code Scanning in the Code stage of a DevSecOps pipeline.

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The description matches AWSBugBust, which AWS positions as a gamified, team-based bug fixing challenge rather than a classic external “bug bounty” for finding vulnerabilities in AWS itself. The key hints are “fun-based solution for bashing bugs,” “encouraging team building,” and “friendly competition,” along with scoring points and awarding prizes. BugBust focuses on improving code quality by motivating developers to find and fix issues (often via static analysis findings) in languages like Java and Python. Participants earn points for remediations and compete on leaderboards, which aligns directly with Sarah “scored the highest points” and received a cash reward. The other names (BugFixer, BugFinder, BugHunt) are plausible-sounding but do not match the commonly referenced AWS gamified program described. In a DevSecOps context, this type of program supports culture by incentivizing secure coding habits, encouraging shared ownership of quality, and making remediation visible and rewarding across the engineering team.

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To complete Azure Key Vault integration with Jenkins, Kevin must createnew credentialsin Jenkins underGlobal Credentials (unrestricted). These credentials store the Azure client ID, client secret, tenant ID, and subscription details required by the Azure Key Vault plugin to authenticate securely. Modifying old credentials can lead to misconfiguration or credential reuse risks, while restricted credentials may prevent the plugin from accessing secrets across pipelines. Creating new unrestricted credentials ensures proper authentication and controlled access to secrets during the Code stage, supporting secure secret management across CI/CD workflows.

The git pull command is used to fetch changes from a remote repository and automatically merge them into the current local branch. In collaborative development environments, especially when multiple developers are committing code to a shared repository, regularly pulling updates is essential to stay synchronized and avoid merge conflicts. The syntax git pull correctly specifies the source of the updates. Commands such as git get and git grabs do not exist in Git, and git push performs the opposite action by sending local changes to the remote repository rather than retrieving updates. Using git pull during the Code stage supports continuous collaboration and ensures that developers integrate the latest changes securely and efficiently.

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In AWS-based DevSecOps pipelines, static analysis tools such as PHPStan commonly send their results to AWS services through event-driven processing. When PHPStan detects security issues, the results are typically parsed and processed by anAWS Lambda function, which can transform findings and forward them to AWS Security Hub. CloudFormation is used for infrastructure provisioning, AWS Config evaluates configuration compliance, and Elastic Beanstalk is an application deployment service—none of these are suited for parsing and relaying scan results. Lambda functions provide a scalable and serverless way to handle scan outputs automatically. This integration ensures that security findings are centralized, visible, and actionable, aligning with secure automation practices during the Code stage.

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Jenkins exposes a predefined endpoint for receiving GitHub webhook events. This endpoint is /github-webhook/ and must be appended to the Jenkins base URL in the GitHub webhook configuration. Option C correctly matches the required endpoint format. The other options use incorrect casing, separators, or naming conventions that Jenkins does not recognize. Correct webhook configuration ensures that Jenkins jobs are automatically triggered when code changes occur in GitHub repositories. This integration supports continuous integration and immediate feedback during the Code stage of the DevSecOps pipeline.

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In Go-based tool installation, the standard method to download, compile, and install a Go package is using the go get command followed by the repository import path. Since Matt has already ensured that Go version 1.8 or later is installed and that $GOPATH/bin is included in the system PATH, running go get github.com/michenriksen/gitrob will fetch the GitRob source code, build the binary, and place it in the appropriate bin directory. Options B, C, and D are invalid because go get does not accept multiple positional arguments in that manner, and go git is not a valid Go command. Installing GitRob during the Code stage enables DevSecOps teams to scan repositories for accidentally committed credentials, API keys, and other sensitive information, helping prevent data leakage from public repositories.

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Git hooks determine success or failure based on the exit code of the executed script. An exit code of0indicates successful execution, while any non-zero value signals failure and causes Git to abort the commit. In Jordon’s setup, a Bash shell calls a PowerShell script to perform pre-commit checks. If the PowerShell script exits with code 0, Git interprets this as a successful hook execution and allows the commit to proceed. Exit codes such as 1, 2, or 3 indicate errors or policy violations and will block the commit. This mechanism ensures that security or quality checks enforced by the pre-commit hook must pass before code is committed. Using exit codes in this way is a standard and reliable approach in cross-platform DevSecOps automation during the Code stage.

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Retire.js is a Software Composition Analysis (SCA) tool designed specifically to identify known vulnerabilities in JavaScript libraries used in web and NodeJS applications. It scans dependencies and compares detected versions against a vulnerability database to identify insecure libraries. Bandit is a static analysis tool for Python, Bundler-Audit is used for Ruby dependencies, and Tenable.io focuses on infrastructure and vulnerability management rather than JavaScript libraries. Using Retire.js during the Code stage allows DevSecOps teams to identify insecure third-party dependencies early, reducing the likelihood of vulnerable libraries being deployed into production. This supports shift-left security and strengthens the application’s overall security posture.

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Git post-commit hooks are executed automatically after a commit is successfully created. To trigger the Jenkins build job configured to respond to commits, Alex must create a valid Git commit using the correct Git command. The standard command to commit changes with a message is git commit -m "commit from terminal". Running this command records the changes in the repository and triggers the post-commit hook, which in turn initiates the Jenkins build. Commands using github commit are invalid because github is not a native Git command-line utility. The -b flag is also not used with git commit. Automating build triggers during the Code stage improves efficiency, reduces manual intervention, and ensures continuous integration is consistently enforced.

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Cloning a GitHub repository requires the standard Git command git clone followed by the correct repository URL format. GitHub repositories are structured as where USERNAME represents the account or organization name and REPOSITORY represents the project name. Option B follows this exact structure. Options using github clone are invalid because github is not a Git CLI command. Options that reverse the order of USERNAME and REPOSITORY do not match GitHub’s repository structure and will fail. Cloning repositories during the Code stage allows DevSecOps engineers to run static analysis, dependency scanning, and other security checks locally without modifying the original repository, supporting secure and controlled analysis workflows.

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Deploy-time checks are designed to identify vulnerabilities that may not surface during earlier stages such as commit-time, build-time, or test-time checks. These checks analyze applications in environments that closely resemble or are part of production, making it possible to detect configuration issues, runtime vulnerabilities, and environment-specific weaknesses. Pre-production testing often cannot fully replicate production conditions, so deploy-time checks act as an additional safety net. Commit-time and build-time checks focus on code quality and static analysis, while test-time checks validate application behavior in controlled environments. Deploy-time checks therefore help Victor uncover vulnerabilities missed earlier, improving overall security assurance before or during deployment.

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The correct installation procedure for the Sqreen PHP microagent involves downloading the installer script and executing it with the organization token and application name. The curl -s option downloads the script silently, while the > redirection operator saves it locally as sqreen-install.sh. The script is then executed using bash, passing the required token and app name as parameters. Options using input redirection (<) are incorrect because they do not save the downloaded script to a file. The -i option includes HTTP headers in the output, which is unnecessary and could corrupt the script. Installing the microagent correctly enables runtime monitoring, attack detection, and automatic blocking, supporting strong runtime security during the Operate and Monitor stage.

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