SecAI D3

An AI-driven IDE extension uses contextual prompts to help developers correct vulnerable code patterns as they type. It also integrates with version control for security commits. Which two benefits does this offer?. Real-time vulnerability detection. Browser plug-in. Integrated development environment (IDE) plug-in. Command-line interface (CLI) plug-in.

A development team integrates a plug-in that connects their IDE to an external AI testing API, automatically identifying insecure dependencies during compilation. Which two features best describe this plug-in?. Browser plug-in. Command-line interface (CLI) plug-in. Integrated development environment (IDE) plug-in. Security automation.

A financial scam operation uses AI to generate convincing investment ads and videos featuring fake endorsements from known entrepreneurs. Which two threat types are evident?. Data poisoning. Impersonation. Misinformation. Disinformation.

A cybersecurity analyst installs an AI-based browser extension that flags malicious URLs and blocks phishing attempts in real time. Which tool category does this belong to?. IDE plug-in. Network proxy tool. CLI plug-in. Browser plug-in.

A cyber defense company integrates an AI-driven platform that learns attacker patterns, identifies irregular system behavior, and automates security alerts to prevent breaches. Which two use cases are demonstrated?. Incident management. Anomaly detection. Pattern recognition. Threat modeling.

A company uses an AI-enabled CI/CD pipeline that not only automates production rollouts but also performs intelligent rollback if performance metrics decline after release. Which two processes are demonstrated?. AI-assisted approval. Automated deployment. Manual failover. Automated rollback.

An AI system automatically writes inaccurate cybersecurity reports that users share online without fact-checking. Although the creators didn't intend harm, the information causes public confusion. Which two threats apply?. Data pollution. Impersonation. Disinformation. Misinformation.

An online retail company uses an AI model to analyze thousands of daily transactions and flag cases where spending patterns deviate from a customer's normal behavior. Which AI use case is being applied?. Summarization. Translation. Fraud detection. Pattern recognition.

A cloud administrator uses a browser extension to log in to multiple dashboards securely with AI-generated strong passwords and auto-fill capabilities. Which two security mechanisms are most relevant here?. Browser plug-in. AI automation. Command-line interface (CLI) plug-in. IDE plug-in.

An analyst wants to automate repetitive API calls and enrich threat data while still embedding custom Python snippets for unique conditions. Which platform type would best meet this need?. No-code platform. AI-only framework. Low-code platform. Full-code IDE.

A DevSecOps team integrates AI-driven automation to perform regression tests after every model update and automatically trigger rollback if performance metrics drop below defined thresholds. Which two CI/CD processes are working together here?. Automated rollback. Regression testing. Model testing. Manual approval.

An AI adversary identifies decoy systems by detecting low-interaction traffic patterns and avoids engaging with them, redirecting attacks to genuine targets. Which two mechanisms are evident here?. Honeypot detection. Payload encryption. Target prioritization. Attack vector enumeration.

A SOC team implements an AI platform that not only categorizes and prioritizes ongoing alerts but also predicts potential attack paths based on prior incidents. Which two AI use cases are evident?. Threat modeling. Pattern recognition. Anomaly detection. Incident management.

An AI-powered CI/CD system tests a fraud detection model's precision and recall metrics after every code change to validate consistency in its predictions before deployment. What type of testing does this describe?. Regression testing. Model testing. Functional testing. Load testing.

A financial institution's AI engine classifies large sets of transaction logs to identify repeated tactics used by known fraudsters, helping analysts recognize emerging fraud methods. Which AI use case is applied?. Incident management. Pattern recognition. Threat modeling. Anomaly detection.

A cybersecurity engineer deploys a workflow platform where non-technical staff can create alert-response automation using drag-and-drop modules, while developers extend functions by embedding PowerShell code in specific nodes. Which two scripting approaches are demonstrated?. No-code. Low-code. Manual scripting. Serverless scripting.

A threat intelligence platform uses AI to identify recurring attack methods across multiple organizations and generate predictive models showing which entities are likely to be targeted next. Which two use cases apply?. Anomaly detection. Threat modeling. Pattern recognition. Incident management.

After implementing a security patch in the CI/CD pipeline, an automated process reruns previous test cases to ensure that no previously functioning features were broken. Which testing practice is being applied?. Model testing. Integration testing. Regression testing. Unit testing.

A threat intelligence system correlates IP logs, DNS requests, and dark web chatter to automatically detect coordinated cyber threats. Which two AI techniques are combined here?. Automated data correlation. Social engineering. Anomaly detection. Reconnaissance.

A security operations center (SOC) analyst uses a platform that allows creating automation workflows by dragging and dropping components such as "Scan IP," "Generate Alert," and "Send Notification" without writing code. Which scripting approach does this best represent?. Low-code scripting. High-code framework. Manual scripting. No-code scripting.

A network administrator uses an AI system that continuously monitors network traffic and flags connections deviating from baseline behavior, then classifies them into potential threat categories. Which two use cases are being used together?. Threat modeling. Anomaly detection. Pattern recognition. Incident management.

A DevSecOps team integrates an AI tool into their change management workflow. The system reviews proposed configuration updates, analyzes potential security impacts, and automatically approves low-risk changes based on policy thresholds. What is this capability called?. Rollback automation. AI-assisted approvals. Change monitoring. Automated deployment.

A Tier-1 SOC analyst uses an AI system that automatically classifies new alerts, opens incident tickets, assigns them to analysts based on workload, and updates ticket statuses as responses progress. Which two AI capabilities are being demonstrated?. Dynamic workload balancing. Document synthesis. Incident response automation. Phishing detection.

A cybersecurity operations team deploys an AI agent that autonomously monitors code repositories, detects unauthorized configuration edits, and reverts them to a previous secure version without human intervention. What function of change management does this represent?. Human-in-the-loop review. Automated rollback. Policy auditing. AI-driven change enforcement.

A bank deploys an AI-driven system on its website that answers customer questions about account balances, card limits, and branch locations through natural language conversation. What type of tool is being used?. Personal assistant. Chatbot. Virtual desktop agent. Predictive model.

A financial analyst uses an AI tool that reviews multiple reports and generates both summaries and alerts when data inconsistencies suggest potential fraud. Which two use cases are in operation?. Data classification. Fraud detection. Summarization. Translation.