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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applications | 25% | - Secure access for remote workers and distributed applications - API security architecture - Secure web gateway and firewall proxy solutions - Microservices and container security |
| Topic 2: Secure Infrastructure | 30% | - Modify the security architecture to address technical requirements
|
| Topic 3: Risk, Events, and Requirements | 30% | - Match the regulatory and industry compliance document to a given business or technical scenario - Describe how the SOC leverages incident handling and incident response tools - Describe the use of frameworks in the lifecycle of a security design
- Modify a security design following an incident |
| Topic 4: Artificial Intelligence, Automation, and DevSecOps | 15% | - Describe the functions, uses, and role of AI in securing network infrastructure - Describe DevSecOps concepts and practices for CI/CD pipelines - Evaluate policies to address the impacts of emerging technologies
|
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NEW QUESTION # 67
Which generative AI impact is addressed by a human-in-the-loop design policy?
Answer: D
Explanation:
In the realm of Artificial Intelligence security,AI hallucinationsoccur when a generative model perceives patterns that are non-existent or logically incorrect, leading to the creation of content that is nonsensical, factually wrong, or potentially dangerous. To mitigate the risks associated with these inaccuracies, ahuman- in-the-loop (HITL)design policy is essential. This policy ensures that human judgment and contextual understanding are integrated into the AI's decision-making or output validation process.
According to theCisco SDSI v1.0objectives, while AI is exceptional at processing high volumes of data, it lacks the ethical and logical framework to consistently identify its own hallucinations. By implementing a HITL approach, subject matter experts can review AI-generated responses, code, or security alerts before they are acted upon. This human oversight allows for the identification of "logical leaps" or false information that automated filters might miss.
Whiledeep fakes(Option B) are typically addressed through cryptographic watermarking or origin tracking, andphishing(Option C) is mitigated via email security gateways and user training, hallucinations are an inherent flaw in the model's predictive nature that requires manual verification.Scale changes(Option D) refer to technical image manipulations and are not a primary concern for HITL policies. Incorporating human feedback-often throughReinforcement Learning from Human Feedback (RLHF)-allows the security infrastructure to refine the model's accuracy over time, ensuring that generative outputs remain reliable, safe, and aligned with organizational standards.
NEW QUESTION # 68
Which benefit does AI provide in network security?
Answer: D
Explanation:
According to the Cisco SDSI v1.0 objectives, Artificial Intelligence and Machine Learning (ML) provide significant benefits in automating the identification of complex security weaknesses. One of the primary benefits is the ability of AI to performEncrypted Threat Analytics (ETA). AI models can analyze the metadata and initial handshake patterns of encrypted traffic-without needing to decrypt it-toidentify vulnerabilities associated with weak TLS algorithmsor outdated cipher suites.
By recognizing specific fingerprints in the TLS handshake, AI-driven tools can alert administrators to non- compliant encryption standards that might be susceptible to interception. While AI is a powerful force multiplier, it doesnot replacea comprehensive defense-in-depth strategy (Option B); rather, it enhances it. It does not directlyspeed up data transmission(Option A), as that is a function of hardware and bandwidth.
Furthermore, while AI helps mitigate DDoS attacks, it rarely provides "complete" protection (Option C) on its own, as DDoS mitigation requires a multi-layered approach involving massive bandwidth and specialized scrubbing. The ability to identify cryptographic weaknesses at scale is a core functional benefit of AI in modern security infrastructure, aligning with the Cisco goal of maintaining a hardened and compliant network posture through automated visibility.
NEW QUESTION # 69
A developer is building new API functions for a cloud-based application. Before writing the code, the developer wants to ensure that destructive actions, including deleting and updating data, are properly protected by access control identifying sensitive fields such as those that contain passwords or personally identifiable information. Which approach must be used to score the risks proactively?
Answer: B
Explanation:
Open API Specification Analysis evaluates API definitions before code is written, identifying risky endpoints (such as delete or update functions) and sensitive fields (like PII or passwords). This allows developers to proactively score risks and apply proper access controls early in the design phase.
NEW QUESTION # 70
Which tool is used by SOC analyst to quarantine an endpoint?
Answer: D
Explanation:
Cisco XDR (Extended Detection and Response) gives SOC analysts the ability to detect, investigate, and quarantine compromised endpoints. It integrates telemetry across endpoints, network, and cloud, enabling coordinated response actions.
NEW QUESTION # 71
A company published software that had a security vulnerability, and an attacker used the vulnerability to steal critical information from the environment. The issue was reported by the security team, and the administrator was instructed to run shift-left security tests before publishing the software. Which component of the software development pipeline must be recommended to run the tests?
Answer: B
Explanation:
Shift-left security means running security tests earlier in the development lifecycle. By integrating tests in the source code management stage (e.g., Git repositories), vulnerabilities can be detected and fixed before software is built and deployed, reducing the risk of publishing insecure code.
NEW QUESTION # 72
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