300-745 Cisco Designing Cisco Security Infrastructure (300-745 SDSI) v1.0 Free Practice Exam Questions (2026 Updated)

Aflow collector(such asCisco Secure Network Analytics, formerly Stealthwatch) is a critical tool within a Security Operations Center (SOC) for providing "pervasive visibility" into the network. Instead of capturing every full packet—which is resource-intensive—a flow collector ingests NetFlow or IPFIX data, which contains metadata like source/destination IPs, ports, and the volume of data transferred.

The SOC leverages this data forthreat detection and responseby establishing a baseline of normal network behavior. When a flow collector identifies an anomaly—such as an endpoint suddenly sending gigabytes of data to an unusual external IP (data exfiltration) or scanning internal ports (lateral movement)—it flags the incident for analysis. UnlikeReal-time content filtering(Option D), which happens at the gateway (e.g., Cisco Umbrella or WSA), flow collectors provide a historical record and behavioral analysis ofallinternal and external traffic. They do not performload balancing(Option B) orbackup/recovery(Option A). In the Cisco SDSI framework, flow analysis is essential for identifying the "unknown unknowns" and providing the forensic evidence needed to understand the scope and path of a security breach.

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.

In the context of theCisco Security Infrastructure (300-745 SDSI)objectives, ensuringdata integrityis a fundamental requirement, particularly in the healthcare sector where the accuracy of medical records at remote sites is critical for patient safety.Hashingis the primary mathematical process used to verify that data has not been altered or tampered with during transit between locations.

Hashing works by applying a cryptographic algorithm (such as SHA-256) to a data set to produce a fixed-size string of characters called a "hash" or "checksum." When data is sent from one remote site to another, the sender calculates a hash of the original data. Upon arrival, the receiving site recalculates the hash using the same algorithm. If the two hashes match exactly, the receiver is assured that the data is identical to the original and has maintained its integrity. Even a single-bit change in the original data would result in a completely different hash value.

WhileAuthentication(Option D) andPreshared Keys(Option C) are essential for verifying the identity of the sites and establishing secure tunnels (like IPsec VPNs), they do not, by themselves, provide the mathematical proof of content integrity.Data Masking(Option B) is a privacy technique used to hide sensitive information from unauthorized viewers, but it does not prevent or detect data corruption or unauthorized modifications. Therefore, hashing is the specified technical control for achieving verifiable data integrity across distributed infrastructures.

A Security Operations Center (SOC) is often overwhelmed by thousands of alerts from various security tools. The primary tool used to aggregate, correlate, and—most importantly—prioritizethese incidents is theSecurity Information and Event Management (SIEM)system. According to the Cisco SDSI domain on Risk, Events, and Requirements, a SIEM acts as the central brain of the SOC.

A SIEM (such as Splunk or Cisco Secure Cloud Analytics) ingests logs from firewalls, endpoints, and cloud services. It uses correlation rules and risk-scoring algorithms to distinguish between low-priority "noise" and critical security incidents. For example, a single failed login might be ignored, but ten failed logins followed by a successful one and a large data transfer would be escalated as a high-priority incident.Endpoint Detection and Response (EDR)(Option B) andEndpoint Protection Platforms (EPP)(Option D) provide deep visibility and protection on individual hosts but lack the cross-platform correlation needed to prioritize organizational risk.CloudWatch(Option C) is a monitoring service for AWS resources but does not function as a multi-source security correlation engine. By using a SIEM, SOC analysts can focus their limited time on the most impactful threats, ensuring a more efficient and effective incident response process.

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In the framework of theDesigning Cisco Security Infrastructure (300-745 SDSI)curriculum, the "Shift-Left" security strategy is fundamental to modern DevSecOps. To identify vulnerabilities like SQL injection at the earliest possible stage—specifically before the code is even compiled or deployed—Static Application Security Testing (SAST)is the required solution. SAST tools analyze the application’s source code, byte code, or binaries without actually executing the program.

By integrating SAST tools like Checkmarx or SonarQube into the CI/CD pipeline, the security team can automate the scanning of every code commit or pull request. These tools use sophisticated algorithms to trace data flows and identify dangerous patterns, such as user-controlled input being concatenated directly into SQL queries without proper sanitization or parameterization. This proactive approach allows developers to receive immediate feedback within their native workflow, enabling them to fix security flaws before they progress into later, more expensive stages of the development lifecycle.

In contrast,Dynamic Application Security Testing (DAST)(Option D) requires a running instance of the application and typically occurs much later in the pipeline, such as during the testing or staging phase. While DAST is excellent for finding runtime vulnerabilities, it does not meet the requirement of identifying issues "early in the development process" as effectively as SAST.Build log observability tools(Option B) andworkflow automation platforms(Option C) provide infrastructure and visibility but do not possess the specialized engine required to perform deep code analysis for application-layer vulnerabilities like SQL injection. Implementing SAST ensures that security is a foundational element of the code-writing phase, aligning with Cisco's vision for a secure, automated software supply chain.

According to theCisco Security Incident Responselifecycle and theNIST SP 800-61standards referenced in the SDSI objectives, the very first step in responding to a third-party vulnerability disclosure isIdentification and Validation. Before a team can patch, notify stakeholders, or monitor for exploits, they must perform an asset inventory check to confirm whether the specific vulnerable version of the product is actually running within their environment.

In a complex CI/CD pipeline, multiple tools and versions coexist. Jumping straight to patching (Option D) without validation can lead to unnecessary downtime or "breaking" integrated workflows if the vulnerability doesn't actually apply to the version in use. Similarly, using an IDS (Option A) is a detection/monitoring step that follows the confirmation of risk. Notifying customers (Option B) is a later phase in the incident response process, usually reserved for confirmed breaches or significant service impacts. By confirming the presence and version of the software first, the security team can accurately assess theblast radiusand prioritize remediation efforts based on the actual risk to the university's specific infrastructure. This systematic approach ensures that resources are allocated efficiently and that the security posture is managed based on verified data rather than assumptions.

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In the aftermath of a security breach, forensic investigators rely on theAccountingportion ofAAA (Authentication, Authorization, and Accounting)to reconstruct a timeline of events. While Authentication verifies identity and Authorization defines permissions, Accounting is the specific framework used to track user activity, including login/logout times and the specific commands executed during a session.

According to Cisco Security Infrastructure design objectives, implementing a centralized AAA solution (such asCisco Identity Services Engine (ISE)or a TACACS+/RADIUS server) is critical for accountability. In this scenario, the engineer would query the AAA logs to identify exactly "who" accessed the sales system during the compromise period.SNMP(Option A) is primarily for network monitoring and performance data, not granular user access logs.NACM(Option B) is an access control model for NETCONF but doesn't provide the broad auditing required here.PKI(Option D) provides the certificates used for digital signatures and encryption but does not log the historical "session" data needed for the investigation. Therefore, AAA is the fundamental architectural requirement for ensuring non-repudiation and providing the audit trail necessary to satisfy risk management and incident response requirements.

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In a modern cloud and campus environment, managing the lifecycle of an identity is the cornerstone of a secure architecture.Identity and Access Management (IAM)is the comprehensive framework of policies and technologies that ensures the right individuals have the appropriate access to technology resources. According to the Cisco SDSI objectives, IAM is the primary mechanism used to transition from manual, error-prone onboarding to a policy-driven approach based onroles and responsibilities.

IAM solutions allow administrators to define digital identities and associate them with specific roles (Role-Based Access Control). When a new employee is onboarded, the IAM system automatically provisions access to the necessary cloud applications and data based on their department or job function. This ensures the principle ofleast privilegeis maintained from day one. WhileSecurity Groups(Option B) andNetwork Access Control Lists (ACLs)(Option D) are important technical controls for filtering traffic at the network layer, they do not manage the identity lifecycle or the complex mapping of users to application permissions. AVPN(Option C) provides a secure tunnel for remote access but does not definewhata user can do once they are inside the network. IAM provides the central control plane for identity-centric security, which is essential for a large university environment with high user turnover and diverse access requirements.

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In the context of Designing Cisco Security Infrastructure, protecting Remote Access VPN (RAVPN) against brute-force and password spray attacks is a critical objective. On Cisco Firepower Threat Defense (FTD) and Adaptive Security Appliance (ASA) platforms, theDefaultWEBVPNGroupandDefaultRAGroupare the landing points for any connection request that does not specify a valid Group Alias or Group URL. Attackers frequently target these default profiles because they are often left with "None" as the authentication method, allowing the attacker to probe for valid usernames without immediate rejection.

By selectingOption D, the security designer ensures that any attempt to access the VPN via these default profiles requires valid AAA credentials. According to Cisco's hardened design guides, it is best practice to point these default profiles to a "sinkhole" AAA server or a local database with no users. This forces the password spray attack to fail at the initial authentication phase before any sensitive information is leaked or unauthorized access is granted. While Option A (ACLs) provides a temporary fix, it is ineffective against distributed attacks using rotating IP addresses. Option B (Disabling aliases) is a good obfuscation technique but doesn't stop an attacker from hitting the default profile. Option D provides a structural mitigation that aligns with theCisco SAFEarchitectural principle of reducing the attack surface by securing every possible entry vector into the private infrastructure.

Cisco TrustSec is a next-generation security architecture that provides software-defined segmentation to simplify the provisioning of network access control. In a hotel environment where guest privacy is paramount, TrustSec is the ideal solution to prevent "peer-to-peer" or cross-communication between devices located within the same VLAN. Traditional methods for this isolation, such as Private VLANs (PVLANs) or complex, manually managed Access Control Lists (ACLs), can be extremely difficult to maintain at scale across a global infrastructure.

TrustSec replaces these IP-based or VLAN-based restrictions with Scalable Group Tags (SGTs). When a device connects to the network, Cisco Identity Services Engine (ISE) authenticates the endpoint and assigns it a specific SGT based on its role, identity, or security posture. The network infrastructure (switches) then enforces policy based on these tags. To meet the requirement of preventing communication between devices in the same VLAN without using dynamic ACLs (dACLs), ISE can be configured to assign the same SGT to guest devices and then apply a Security Group ACL (SGACL) that denies traffic where both the source and destination tags are identical. This "intra-SGT" isolation effectively blocks devices from communicating with their neighbors on the same local segment. This approach aligns with the Cisco SAFE architecture by providing granular, identity-aware segmentation that is topology-independent, allowing the hotel chain to maintain a simplified network structure while ensuring robust client security.

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In aFull TunnelVPN configuration, all traffic from the remote client is sent to the VPN headend before being routed to its final destination. This often results in "hairpinning," where high-bandwidth latency-sensitive traffic, such as video conferencing, travels to the corporate data center only to be sent back out to the internet, doubling the bandwidth consumption at the headquarter's ISP link.

To resolve this, the company should implementSplit-Excludetunneling. This configuration allows the VPN administrator to define specific applications or IP ranges—in this case, the SaaS video platform—that should bypass the secure tunnel and go directly to the internet via the user's local ISP. This significantly reduces the load on the corporate headquarter's internet connection and often improves the "employee experience" by reducing latency for the video stream. Unlike Option A, which degrades quality, or Option C/D, which disrupts workflow and security posture, split-excluding trusted SaaS traffic maintains a high security standard for internal resources while optimizing infrastructure costs. This aligns with theCisco SDSIobjective of designing scalable and cost-effective remote access solutions usingCisco Secure Client(AnyConnect) and Firepower Threat Defense (FTD) policies.

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In the architecture of modern security, Artificial Intelligence (AI) and Machine Learning (ML) are leveraged to move beyond reactive, signature-based defenses. One of the most significant uses of AI in securing network infrastructure is the detection ofzero-day attacks(often referred to in exam contexts as "day zero" attacks). A zero-day attack exploits a vulnerability that is unknown to the software vendor or the public, meaning no signature exists for traditional firewalls or antivirus software to block it.

AI identifies these threats throughbehavioral analysisandanomaly detection. By establishing a highly granular baseline of "normal" network traffic patterns—including flow direction, packet size, inter-packet arrival times, and protocol behavior—AI models can detect subtle deviations that indicate a malicious exploit. For example,Cisco Secure Network Analytics(formerly Stealthwatch) andEncrypted Threat Analytics (ETA)use ML to identify the cryptographic "fingerprints" of malware even within encrypted traffic, without the need for decryption. This allows the security infrastructure to identify and mitigate threats at the moment they appear, rather than waiting for a vendor to release a signature. While load balancing (Option B), traffic shaping (Option C), and Quality of Service (Option D) are critical for network performance and availability, they are traditional traffic engineering functions that do not inherently provide the advanced threat detection capabilities offered by AI-driven security models. Within the Cisco SDSI objectives, AI is positioned as the primary technology for achieving proactive visibility and reducing the "Mean Time to Detect" (MTTD) for previously unseen vulnerabilities.

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.

In a Kubernetes environment,Namespacesprovide a logical partition for resources but do not, by default, provide network isolation. To prevent "app01" from communicating with "app02," aNetworkPolicymust be implemented. NetworkPolicies act as the Layer 3/4 distributed firewall for the cluster, allowing administrators to define explicit rules for ingress and egress traffic between pods and namespaces.

To achieve complete isolation, a common design pattern is to implement a "deny-all" default policy for each namespace and then explicitly allow only necessary traffic. This aligns with theCisco SAFEarchitectural principle of micro-segmentation. WhileRoleBinding(Option B) manages permissions for the Kubernetes API (who can create or delete pods), it does not control the actual network traffic between those pods.HTTPRoute(Option A) andGateway(Option D) are components of the Kubernetes Gateway API used for managing external traffic routing and load balancing, rather than internal pod-to-pod isolation. By deploying NetworkPolicies, the administrator ensures that the "blast radius" of a compromised application is contained within its own namespace, fulfilling a core objective of securing cloud-native application infrastructure.

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The spread of malware across a sensitive segment like themanagement networkhighlights a failure in host-level security and internal visibility. To detect and mitigate the spread of such threats and protect the overall network,Endpoint Detection and Response (EDR)is the most effective choice among the options. In the Cisco security ecosystem, the endpoint is often the last line of defense and the most critical source of telemetry for malware incidents.

By deploying an EDR solution likeCisco Secure Endpoint, the manufacturing company gains the ability to identify the "patient zero" of the infection. EDR uses advanced features likeDevice TraversalandLateral Movementdetection to see how malware moves from one machine to another over the management network. Once detected, the security team can use the EDR platform to initiate a "host isolation" command, effectively cutting off the infected device's communication with the rest of the network without physically unplugging it. WhileEncrypted Threat Analytics (ETA)(Option C) is a powerful network-based feature for detecting malware in encrypted traffic without decryption, EDR provides the most granular control and response capabilities specifically for malwareresiding on and spreading betweenhosts. RADIUS (Option B) and IPsec VPNs (Option D) focus on access control and encryption of data in transit, respectively, but do not provide the behavioral analysis needed to stop a running malware outbreak once the network has already been accessed.

In the architectural design of a modern Security Operations Center (SOC), visibility is paramount.Splunkis a leading Security Information and Event Management (SIEM) and log management platform used to aggregate data from disparate sources across the enterprise. According to theCisco SDSI v1.0objectives, specifically within the "Risk, Events, and Requirements" domain, a central repository for telemetry is essential for incident response and threat hunting.

Splunk collects logs, metrics, and other data from network devices (firewalls, switches, routers), endpoints (laptops, servers), and cloud applications. It then indexes this data, allowing security analysts to perform complex searches, create visualizations, and build dashboards that provide a real-time view of the organization's security posture.

While Cisco offers native tools likeCisco Secure Cloud AnalyticsorCloud Observability(Option B) for specific cloud and application performance monitoring, Splunk serves as the broader "single pane of glass" for the entire infrastructure.Cisco Email Security Appliance(Option A) andCisco Web Security Appliance(Option C) are specialized security engines thatgeneratelogs but do not function as the overarching collection and analysis platform for the entire enterprise. By integrating Cisco security products with Splunk, organizations can correlate events—such as a blocked web request from a WSA and a malware alert from a Secure Endpoint—to identify a coordinated attack, fulfilling the Cisco SAFE requirement for pervasive visibility.

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