Free Cisco 300-745 Practice Exam with Questions & Answers

For a financial company, protecting "data at rest" is a critical requirement of the Cisco Security Infrastructure blueprint. While physical security and BIOS-level protections have their place,Data encryption on disk(such as BitLocker, FileVault, or hardware-encrypted drives) is the only solution that fulfills the requirement of rendering the actual data unreadable if the device is lost or stolen.

Disk encryption uses cryptographic algorithms to transform readable data into ciphertext. Without the correct decryption key—which is typically released only after successful user authentication—the data remains a meaningless string of characters even if the hard drive is removed and connected to a different machine. AKensington Lock(Option A) is a physical deterrent to prevent theft but does not protect the data if the lock is cut or the device is stolen. ABIOS password(Option B) can prevent the OS from booting but does not stop an attacker from reading the data directly from the storage media.GPS tracking(Option D) helps in recovery but does not prevent unauthorized data access in the interim. Implementing full-disk encryption aligns with theCisco SAFEprinciple of pervasive data protection and ensures compliance with financial regulations regarding the safeguarding of sensitive client information on mobile endpoints.

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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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The requirement to restrict administrative tasks like "customer onboarding" to specific users based on their job function is a classic use case forRole-Based Access Control (RBAC). In the context of application security design, RBAC is the mechanism that maps a user's identity to a specific set of permissions within the application.

According to Cisco Security Infrastructure principles, RBAC ensures the principle ofleast privilegeby ensuring that an "Admin" role has access to onboarding functions, while a "Support" or "Standard User" role does not. This control is independent of the network layer and is enforced at the application or identity provider level. While aVPC(Option A) orSecurity Groups(Option C) provide network-layer isolation and can ensure the user is on the corporate network (by filtering IP ranges), they cannot distinguish between differentfunctionsoractionsperformed within the application once the connection is established. AService Mesh(Option D) is used for microservices communication and can provide some authorization, but RBAC is the primary architectural approach for defining "who can do what" within an application interface. Implementing RBAC allows the SaaS provider to secure sensitive administrative workflows, ensuring that only authorized personnel can modify customer data or system configurations.

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In a smart factory environment, IoT devices often use specialized industrial protocols (like Modbus, PROFINET, or EtherNet/IP) and have limited built-in security. To meet the requirements of protecting these devices from network-based attacks while gaining visibility into communication patterns and detecting anomalies, anIPS/IDS (Intrusion Prevention/Detection System)is the most effective solution.

Modern Cisco Secure Firewall (NGFW) systems integrate advanced IPS/IDS capabilities that go beyond simple port-based filtering. They provide deep packet inspection (DPI) to identify specific IoT protocols and baseline "normal" behavior. When an IoT device suddenly begins communicating with an unknown external IP or attempts to use a command it has never used before, the IPS/IDS can trigger an alert or block the traffic as an anomaly.

While aZone-Based Firewall(Option A) or aTraditional Firewall(Option C) can segment traffic and control access between zones, they generally lack the granular visibility and behavior-based anomaly detection required for IoT security. ATransparent Firewall(Option B) is a deployment mode that makes the firewall "invisible" at Layer 2, which is useful for insertion into existing networks but does not inherently provide the required anomaly detection. Therefore, IPS/IDS is the primary technology within the Cisco Security Infrastructure that addresses the need for signature-based protection combined with behavioral visibility for specialized IoT traffic.

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Based on the provided exhibits, the correct firewall feature for blocking malware in this context isFile Inspection.

Inimage_4c047c.png, we see a Cisco Secure Firewall Access Control Policy rule named "Default Inspect". This rule is configured to allow traffic from the "inside" zone to the "outside" zone while applying deep packet inspection. Crucially, the configuration includes aFile Policyfield, which is the mechanism used to perform malware analysis and file disposition lookups. By associating a File Policy with an Access Control rule, the firewall can inspect files as they transit the network, calculate their SHA-256 hash, and query the Cisco Collective Security Intelligence cloud to determine if the file is malicious, clean, or unknown.

The evidence of this feature in action is found inimage_4b1ebe.png, which shows theCisco Secure Endpoint(formerly AMP for Endpoints) Device Trajectory. The "Activity Details" pane specifically identifies a malicious file (iodnxvg.exe) categorized asW32.DFC.MalParent. While the log notes the file was not quarantined because it was in "audit only mode," the underlying technology performing the detection isFile Inspection. This feature provides the necessary visibility into the contents of encrypted or unencrypted data streams to identify and—when properly configured in a "Protect" or "Block" mode—stop the execution of malware. This aligns with the Cisco SDSI objective of building a layered defense that combines perimeter traffic control with granular file-level security.

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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When moving security closer to the data, the endpoint becomes the final perimeter. Ahost-based firewallis a software component that runs directly on the endpoint's operating system (Windows, macOS, or Linux). While the company already has Next-Generation Firewalls (NGFWs) at the network edge, those devices cannot protect endpoints from threats originating within the same local network segment (East-West traffic) or when the device is used outside the corporate office.

Implementing a host-based firewall provides a critical layer ofdefense-in-depth. It allows security administrators to enforce strict inbound and outbound traffic rules based on applications and services specific to that device. For example, it can prevent a compromised laptop from scanning other devices on a public Wi-Fi network. In the Cisco ecosystem, this is often achieved through theCisco Secure Client(AnyConnect) using theNetwork Visibility Module (NVM)or integrated endpoint security suites.

While aDistributed Firewall(Option C) is used for micro-segmentation within data centers/clouds and aWeb Application Firewall (WAF)(Option B) protects servers from web-based attacks, only a host-based firewall meets the requirement for traffic filtering directly on the diverse array of endpoint devices. This approach ensures that even if the network edge is bypassed, the individual host remains hardened against lateral movement and unauthorized communication.

Accidental exposure of sensitive credentials, such as API keys or AWS secrets, is a major risk in modern DevOps environments. To prevent such incidents from occurring, the most effective technical control is the implementation of aSource Code Management (SCM) precommit hook. A precommit hook is a script that runs locally on a developer's machine before a commit is finalized and pushed to a remote repository.

According to Cisco's DevSecOps design principles, precommit hooks can be configured to scan the code for specific patterns that resemble secrets (e.g., regex for AWS Access Key IDs). If the scanner detects a secret, it automatically aborts the commit, forcing the developer to remove or properly encrypt the sensitive data before the code can leave their local machine. This provides an immediate "shift-left" safety net that stops the leak at the source.

While aWeb Application Firewall (WAF)(Option A) protects against external attacks andPort Security(Option B) manages Layer 2 access, neither can prevent a developer from pushing code to GitHub. Aphishing education campaign(Option C) is beneficial for general security awareness but does not provide the automated, technical enforcement required to block credential leakage. By configuring precommit hooks, the pharmaceutical company establishes a proactive defense mechanism that significantly reduces the risk of credential exposure and aligns with the automation objectives of the Cisco SDSI curriculum.

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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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.