信頼できる300-745|最高の300-745試験過去問試験|試験の準備方法Designing Cisco Security Infrastructure受験内容

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Cisco 300-745 認定試験の出題範囲:

トピック出題範囲
トピック 1
  • Applications: Focuses on selecting security solutions to protect applications and designing secure architectures for cloud-native, containerized, and serverless environments using segmentation. Also addresses security design impacts of emerging technologies like AI, ML, and quantum computing.
トピック 2
  • Risk, Events, and Requirements: Covers SOC incident handling and response tools, modifying security designs to mitigate or respond to incidents, and applying frameworks like MITRE CAPEC, NIST SP 800-37, and SAFE. Includes matching regulatory and compliance requirements to business scenarios.
トピック 3
  • Secure Infrastructure: Covers selecting security approaches for endpoints, identities, email, and modern environments like hybrid work, IoT, SaaS, and multi-cloud. Includes choosing VPN
  • tunneling solutions, securing management planes, and selecting the appropriate firewall architecture based on business needs.
トピック 4
  • Artificial Intelligence, Automation, and DevSecOps: Explores AI's role in securing network infrastructure, selecting tools for automated security architectures such as SOAR, IaC, and API tooling, and integrating security into DevSecOps workflows and pipelines to minimize deployment risk.

>> 300-745試験過去問 <<

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Cisco Designing Cisco Security Infrastructure 認定 300-745 試験問題 (Q31-Q36):

質問 # 31
Which function does a DLP system perform when protecting application data?

正解:D

解説:
A Data Loss Prevention (DLP) system inspects data in transit (and at rest or in use) to ensure sensitive information is handled according to security policies.


質問 # 32
After deploying a new API, the security team must identify the components of the application that are exposed to the internet and whether there are application authentication risks. Which technology must be deployed to discover the applications services and monitor for authentication issues?

正解:D

解説:
Securing APIs requires visibility into the "runtime" behavior of the application.API trace analysis(often part of anAPI Securitysolution like Cisco Panoptica) is the technology used to automatically discover API endpoints and analyze the traffic flowing through them. This process identifies "shadow APIs" (undocumented endpoints) that are exposed to the internet and inspects the headers and payloads for authentication risks, such as missing tokens or broken object-level authorization (BOLA).
By monitoring actual traffic traces, the security team can confirm if the API is following the intended security design or if it is leaking sensitive data due to poor authentication implementation.Cloud Security Posture Management (CSPM)(Option A) focuses on the configuration of the cloud infrastructure (like an open S3 bucket) rather than the internal logic of an API's authentication.Secret scanning(Option C) is a "shift-left" technique used to find hardcoded passwords in source code during the build phase, not for monitoring live traffic.Cloud Workload Protection (CWPP)(Option D) focuses on protecting the underlying host or container from malware and exploits. Only API trace analysis provides the specific visibility into service discovery and application-layer authentication health required in the Cisco SDSI v1.0 objectives for modern DevSecOps environments.


質問 # 33
An employee of a pharmaceutical company accidentally checked in code that contains AWS secret keys to a public GitHub repository, which exposes production resources to attackers.
Which mitigation strategy must a security engineer recommend to prevent future reoccurrence?

正解:C

解説:
An SCM (Source Code Management) precommit hook scans code for sensitive information such as AWS keys before it is committed. This prevents developers from accidentally pushing secrets to public repositories, protecting production resources from exposure.


質問 # 34
What is the primary benefit of conducting a root cause analysis after a security incident?

正解:B

解説:
Root cause analysis focuses on identifying the underlying cause of a security incident. This enables organizations to improve system design, controls, or processes so that similar incidents do not happen again, rather than only fixing symptoms.


質問 # 35
What does watermarking AI generated content prevent?

正解:A

解説:
In the realm of Artificial Intelligence and DevSecOps,watermarkingis a critical security technique used to identify the origin of synthetic media. As generative AI models become increasingly sophisticated, they can create highly realistic images, videos, and audio clips-often referred to asdeep fakes. These deep fakes pose a significant risk to organizational security and public trust, as they can be used for sophisticated social engineering attacks, such as impersonating executives in "Business Email Compromise" (BEC) scenarios or spreading misinformation.
By embedding a cryptographic or perceptible watermark into AI-generated content, security systems and users can verify the authenticity and provenance of the media. This proactive measure helps prevent the successful deployment of deep fakes by making it easier for automated security tools to flag synthetic content that lacks a valid "signature" of origin. While watermarking does not inherently stop the creation ofharmful content(Option C) or reduceresource consumption(Option A), it provides a layer of accountability and verification. Similarly,scale changes(Option D) are technical image manipulations that watermarking does not prevent. Within the Cisco SDSI framework, watermarking is viewed as an essential component of the AI security lifecycle, ensuring that generative technologies are used responsibly and that synthetic content is distinguishable from genuine data.
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質問 # 36
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