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NEW QUESTION # 56
A company recently discovered that a former employee, who left to join a competitor, continued to access and exfiltrate sensitive data over several weeks after leaving. The breach highlighted vulnerabilities in the organization's data security and access management practices. To prevent such incidents in the future, the organization must adopt measures that detect and restrict unauthorized data access and transfer. Which mitigation strategy must be implemented to address the issue?
Answer: A
Explanation:
A Data Loss Prevention (DLP) strategy directly addresses the problem of unauthorized access and exfiltration of sensitive data. DLP tools monitor, detect, and block suspicious data transfers, ensuring that insiders or former employees cannot copy, email, or upload sensitive information without authorization. This provides the required prevention and control that the scenario calls for.
NEW QUESTION # 57
How does a SOC leverage flow collectors?
Answer: C
Explanation:
A flow collector gathers metadata about network traffic (such as NetFlow or IPFIX), which SOC analysts use to analyze communication patterns. This data is critical for threat detection and response, helping identify anomalies, lateral movement, or potential attacks.
NEW QUESTION # 58
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?
Answer: C
Explanation:
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.
NEW QUESTION # 59
Which generative AI impact is addressed by a human-in-the-loop design policy?
Answer: C
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 # 60
In preparation for an upcoming security audit, a metal production company decided to enhance the security of container-based services running in a Kubernetes environment. The company wants to ensure that all communications between applications and services are encrypted. The administrator plans to implement mTLS service between application and services to secure the data exchanges. Given the need to manage encryption at scale and maintain efficient communication across the cluster, which network transport technology must be employed?
Answer: C
Explanation:
In modern cloud-native architectures, managing security for hundreds of microservices manually is unfeasible. To implementmutual TLS (mTLS)at scale within a Kubernetes cluster, aService Mesh(such as Istio or Cisco Service Mesh Manager) is the architectural solution of choice. A service mesh provides a dedicated infrastructure layer for handling service-to-service communication without requiring changes to the application code itself.
The service mesh operates by deploying a "sidecar" proxy alongside every service instance. These proxies handle the heavy lifting of identity verification, certificate rotation, and the establishment of encrypted tunnels. This ensures that every data exchange is encrypted and that services only communicate with authenticated peers. While anIngress Controller(Option A) manages traffic entering the cluster andLoad Balancing(Option B) distributes traffic, neither provides the granular, internal encryption framework required for pod-to-pod mTLS.Kubernetes Network Policies(Option C) act as a distributed firewall to allow or deny traffic based on IP/Port but do not handle encryption or cryptographic identity. By choosing a Service Mesh, the company satisfies the audit requirement for end-to-end encryption and pervasive visibility into the application's communication flow, aligning with Cisco's design principles for secure, scalable microservices.
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NEW QUESTION # 61
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