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NEW QUESTION # 29
Which two metrics are important for evaluating the performance of automated security response workflows? (Choose two.)
Answer: B,D
Explanation:
MTTD measures how quickly incidents are detected, and MTTR measures how quickly they are resolved. Together, they indicate the effectiveness of automated security response workflows.
NEW QUESTION # 30
A company hosted multiple applications in the Kubernetes environment, using the naming app01, app02, and so on. An app01 user could access app02 data because no security measures are implemented. The administrator decided to place each application within a separate namespace and ensure that the namespaces are completely isolated and cannot communicate with each other. Which solution must be used to accomplish the task?
Answer: B
Explanation:
In Kubernetes, a NetworkPolicy controls communication between pods and namespaces. By applying policies that deny cross-namespace traffic, the administrator can ensure each application (e.g., app01, app02) is isolated and cannot access data from other namespaces.
NEW QUESTION # 31
A manufacturing company recently experienced a network-down scenario due to malware spread on the management network. The company wants to implement a solution to detect and mitigate a similar threat in the future and protect the overall network. Which solution meets the requirements?
Answer: A
Explanation:
Endpoint Detection and Response (EDR) provides continuous monitoring, detection, and automated mitigation of malware at the endpoint level. By stopping threats before they spread across the management network, EDR protects the overall infrastructure from similar network- down scenarios in the future.
NEW QUESTION # 32
Which design policy addresses harmful content creation by generative AI?
Answer: A
Explanation:
The creation of harmful content (such as hate speech, misinformation, or malicious code) by generative AI models is a major concern in modern security design. The most effective design policy to mitigate this is the Human-in-the-loop (HITL)approach. This involves integrating human oversight and intervention at various stages of the AI's operation, particularly during the verification of the model's output before it is published or acted upon.
According to Cisco SDSI objectives regarding AI security, HITL ensures that automated decisions are subject to ethical judgment and contextual awareness that AI currently lacks. Humans can provide "Reinforcement Learning from Human Feedback" (RLHF) to tune the model's safety filters, ensuring it refuses to generate toxic or prohibited content. WhileWatermarking(Option B) helps identify content as AI-generated after the fact, it does not prevent thecreationof harmful material.Retrieval Augmented Generation (RAG)(Option C) is a technique for grounding AI in specific data to reduce "hallucinations" but doesn't inherently filter for harmful intent.Quantum resistant encryption(Option A) is a cryptographic standard unrelated to content moderation. HITL remains the primary safeguard for ensuring AI outputs align with safety guidelines and organizational requirements.
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NEW QUESTION # 33
A developer company recently implemented a testing environment based on Linux operating system. The company needs a technology solution that produces tracing and filtering capabilities in the Linux kernel.
Which technology meets these requirements without modifying the kernel source code?
Answer: A
Explanation:
In modern secure infrastructure design, especially within high-performance testing and developer environments, the ability to observe and filter traffic at a deep level is crucial. eBPF (extended Berkeley Packet Filter) is a revolutionary technology that allows developers to run sandboxed programs within the Linux kernel. The primary advantage of eBPF is that it enables sophisticated tracing, monitoring, and network filtering capabilities without the need to modify the underlying kernel source code or load intrusive kernel modules.
In the context of the Cisco SDSI objectives, eBPF is highlighted as a key component of distributed firewalling and cloud-native security architectures. It operates by attaching programs to various "hooks" in the kernel, such as network events, tracepoints, or system calls. When a packet enters the system or a specific event occurs, the eBPF program can inspect the context and make high-speed decisions on whether to allow, drop, or redirect traffic. This provides a much more efficient and flexible alternative to traditional technologies like IPTables. Because eBPF programs are verified for safety by a JIT compiler before being executed, they do not risk crashing the kernel, making them ideal for dynamic developer environments. Unlike Vector Packet Processing (VPP) (Option D), which moves packet processing into userspace, or standard Next-Generation Firewalls (NGFW) (Option C), which are typically separate appliances, eBPF provides "in-kernel" observability and enforcement that is programmable and highly scalable for microservices and containerized applications.
NEW QUESTION # 34
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