Visit here for our full Checkpoint 156-315.81.20 exam dumps and practice test questions.
Question 41:
In Check Point R81.20, which advanced Identity Awareness feature enables seamless authentication for remote VPN users by deriving identity information from the VPN certificate without requiring additional user credentials?
A) VPN-Based Certificate Identity Extraction
B) Certificate-to-User Dynamic Mapping
C) Remote Access Identity Embedding
D) VPN Identity Awareness Auto-Binding
Answer:
A) VPN-Based Certificate Identity Extraction
Explanation:
VPN-Based Certificate Identity Extraction in Check Point R81.20 allows remote-access VPN users to be authenticated automatically based on the information embedded in their digital certificates. This feature eliminates the need for repeated username/password prompts, enhances security, and improves the user experience. The mechanism relies on the idea that certificates issued by trusted enterprise PKI systems already validate user identity; therefore, using certificate fields for identity determination provides a reliable alternative to traditional authentication methods.
Option B, Certificate-to-User Dynamic Mapping, appears similar but does not reflect an official Check Point feature. Option C, Remote Access Identity Embedding, is not a documented Check Point concept. Option D, VPN Identity Awareness Auto-Binding, also does not exist in the R81.20 identity architecture.
Certificate identity extraction begins when the user initiates a VPN connection. During IKE negotiation, the gateway receives the user certificate and reads key fields such as the Subject field, Subject Alternative Name (SAN), email address, or organizational unit attributes. These certificate details are parsed and matched against directory records in Active Directory. If a match is found, the user identity is established without requiring additional login information. Identity Awareness creates a corresponding identity session that applies across Access Control, Threat Prevention, Application Control, and URL Filtering policies.
This mechanism enhances both usability and security. From a usability standpoint, users connect seamlessly without manual login. From a security standpoint, organizations maintain strong authentication because certificates cannot be easily stolen or guessed like passwords. Certificate-based authentication is resistant to phishing attacks and brute-force attempts.
The feature also integrates with Multi-PDP and Identity Sharing, ensuring identity propagation across distributed gateways. It supports mobile VPN clients, endpoint-connected users, and IPsec IKEv2 deployments. Because certificate extraction occurs during the VPN handshake, there is no need for Captive Portal or browser-based authentication.
Administrators can configure extraction rules in SmartConsole by mapping certificate fields to AD attributes. Logging provides full visibility into the extracted identity, certificate properties, and applied policies.
This feature is especially beneficial for organizations transitioning to zero-trust frameworks. Since identity is tied to both user and certificate, the risk of unauthorized access drops significantly.
For these reasons, VPN-Based Certificate Identity Extraction is the correct answer.
Question 42:
Which Check Point R81.20 feature allows firewalls to inspect QUIC-encrypted traffic by classifying applications using metadata signatures, even though QUIC uses UDP-based encrypted payloads?
A) QUIC Metadata Fingerprinting Engine
B) Encrypted UDP Stream Identifier
C) QUIC Application Behavior Analyzer
D) Adaptive QUIC Classification Module
Answer:
D) Adaptive QUIC Classification Module
Explanation:
The Adaptive QUIC Classification Module enables Check Point R81.20 gateways to classify QUIC-based applications despite the protocol’s encrypted and UDP-based nature. QUIC is a next-generation transport protocol used primarily by Google Chrome, YouTube, Facebook, and many large cloud services. QUIC is challenging for firewalls because it encrypts most of its metadata, reducing visibility for traditional packet inspection techniques.
Option A, QUIC Metadata Fingerprinting Engine, sounds reasonable but does not represent an official Check Point subsystem. Option B, Encrypted UDP Stream Identifier, is not a real component. Option C, QUIC Application Behavior Analyzer, is also not a documented feature.
The Adaptive QUIC Classification Module uses a combination of behavioral markers, statistical analysis, connection timing, packet-size patterns, SNI data extracted from fallback TLS handshakes, and heuristic models to classify QUIC traffic. Because many QUIC connections are tied to web services, application identification is essential for policy enforcement. Without classification, QUIC traffic would appear to be generic encrypted UDP, limiting an administrator’s ability to apply rules based on application category.
When QUIC flows begin, the module analyzes the initial handshake packets, identifies known QUIC patterns associated with major cloud services, and maps them to App Control signatures. This allows enforcement even without decrypting the payload. For example, QUIC-based YouTube traffic can be categorized as streaming media, while QUIC-based Google Docs can be categorized as productivity tools.
Adaptive classification is also critical for bandwidth management, URL filtering, identity-based control, and threat prevention. Even though deep inspection is not possible, enforcement of app-level rules still occurs. The module integrates with SecureXL to maintain performance; once the QUIC flow is identified, accelerated processing continues.
This capability ensures enterprises can retain visibility and control over modern encrypted traffic patterns, making Adaptive QUIC Classification Module the correct answer.
Question 43:
In Check Point R81.20, which Acceleration optimization ensures that SecureXL can offload both inbound and outbound NAT operations, reducing the need for firewall kernel processing?
A) NAT Acceleration Offload Table
B) SecureXL FastNAT Module
C) Kernel-Free NAT Handling Engine
D) Accelerated NAT Path Processor
Answer:
B) SecureXL FastNAT Module
Explanation:
The SecureXL FastNAT Module accelerates NAT operations by offloading NAT translation tasks directly into SecureXL, bypassing the firewall kernel for most packets. NAT translation is one of the most frequent operations on a firewall. Without acceleration, every packet would require full kernel processing for translation, slowing performance.
Option A, NAT Acceleration Offload Table, is not an official component. Option C, Kernel-Free NAT Handling Engine, does not exist. Option D, Accelerated NAT Path Processor, also is not documented in Check Point’s architecture.
SecureXL FastNAT stores NAT mappings in hardware-accelerated tables, enabling packets to be translated directly within SecureXL’s fast path. This reduces kernel interrupts, lowers CPU usage, and improves throughput substantially. It applies to both static and hide NAT configurations.
FastNAT is especially beneficial for high-performance data centers and environments with large NAT tables. It helps ensure that NAT-heavy traffic, such as load-balanced outbound connections or DMZ inbound translations, remains efficient under heavy load. The mechanism also synchronizes with CoreXL to ensure consistency across inspection instances.
Thus, SecureXL FastNAT Module is correct.
Question 44:
In Check Point R81.20, which mechanism ensures that when sandboxes in Threat Emulation identify new malicious indicators, the gateway immediately updates its local cache to block similar threats without waiting for a cloud update cycle?
A) Local Threat Propagation Cache
B) Immediate Threat Emulation Feedback Loop
C) Dynamic Local Signature Injection
D) ThreatCloud Instant Verdict Sync
Answer:
B) Immediate Threat Emulation Feedback Loop
Explanation:
The Immediate Threat Emulation Feedback Loop allows gateways to instantly apply new verdicts learned from Threat Emulation. When a file is found malicious during sandbox analysis, the gateway updates its local cache and enforces new protections immediately. This eliminates delay between detection and enforcement.
Option A, Local Threat Propagation Cache, is not an official component. Option C, Dynamic Local Signature Injection, is not recognized in Check Point architecture. Option D, ThreatCloud Instant Verdict Sync, is incorrect because cloud sync cycles are periodic, not instantaneous.
The Immediate Feedback Loop ensures rapid responses to zero-day malware, ransomware, and exploits. If one user in the network triggers a malicious file, the gateway blocks the same file for all other users immediately. This containment strategy significantly reduces the spread of threats.
The mechanism integrates with Anti-Virus, Anti-Bot, and URL Filtering so multiple blades benefit from new intelligence.
Therefore, the Immediate Threat Emulation Feedback Loop is correct.
Question 45:
In Check Point R81.20, which cluster optimization ensures that asymmetric traffic between cluster members can still be processed correctly, even when packets from the same connection arrive at different nodes?
A) ClusterXL Asymmetric Traffic Handler
B) Stateful Inspection Sync Core
C) Dynamic Connection State Mirroring
D) ClusterXL Active-Active Resilience Mode
Answer:
A) ClusterXL Asymmetric Traffic Handler
Explanation:
The ClusterXL Asymmetric Traffic Handler ensures correct processing when traffic flows asymmetrically across cluster members. Asymmetric routing occurs when outbound and inbound packets take different paths. Without special handling, firewalls may drop packets because the receiving member lacks the connection state.
Option B, Stateful Inspection Sync Core, is descriptive but not a Check Point feature. Option C, Dynamic Connection State Mirroring, is a capability of sync but not the name of the subsystem. Option D, ClusterXL Active-Active Resilience Mode, does not exist.
The Asymmetric Traffic Handler allows cluster members to accept connections not initiated on them by referencing synchronized state tables. This prevents session drops, especially in environments with dynamic routing, ECMP, or multiple upstream ISPs.
It is essential for high-availability deployments where path selection is unpredictable. It works in tandem with CoreXL and SecureXL to ensure performance consistency.
Thus, ClusterXL Asymmetric Traffic Handler is correct.
Question 46:
In Check Point R81.20, which core SandBlast component enhances detection accuracy by combining OS-level behavioral analysis with CPU-level exploit detection to identify zero-day attacks even when no malicious file signature exists?
A) Hybrid Threat Emulation Fusion Engine
B) OS-CPU Combined Behavioral Detector
C) SandBlast Multi-Layer Exploit Analyzer
D) Threat Emulation Behavioral Correlation Layer
Answer:
C) SandBlast Multi-Layer Exploit Analyzer
Explanation:
The SandBlast Multi-Layer Exploit Analyzer in Check Point R81.20 represents one of the most advanced forms of zero-day detection in the Threat Prevention suite. It operates by combining two powerful analytical strategies: operating system–level behavioral monitoring and CPU-level exploit detection. This dual approach allows the system to detect and block attacks that do not rely on malicious file signatures and therefore cannot be caught by traditional antivirus tools.
Option A, Hybrid Threat Emulation Fusion Engine, sounds plausible but is not a recognized Check Point subsystem. Option B, OS-CPU Combined Behavioral Detector, reflects the types of detection methods used but is not the official term. Option D, Threat Emulation Behavioral Correlation Layer, may sound related but does not represent an actual Check Point component.
The Multi-Layer Exploit Analyzer focuses on identifying malicious behavior rather than specific patterns. Zero-day exploits often exploit memory corruption, unexpected API calls, StackPivot techniques, ROP chains, heap spraying, or privilege escalation attempts. These behaviors cannot reliably be detected using signatures because attackers continuously change payloads. By observing how a file behaves when executed in a controlled virtual environment, the analyzer can detect suspicious indicators even if the file has never been seen in the wild.
A particularly critical part of this subsystem is CPU-level exploit detection. Rather than waiting for malicious behavior to manifest, the engine monitors CPU instruction flows, memory access patterns, and register manipulations that indicate exploitation attempts. This allows extremely early detection of ROP attacks, buffer overflows, and code injection attempts. CPU-level monitoring is difficult for attackers to evade because exploitation inherently requires manipulating execution flow.
The operating system–level behavioral analysis, meanwhile, monitors system calls, API usage, file system activity, registry changes, and network behavior. This layer catches malware that attempts persistence, command and control communication, or evasion techniques.
Both layers feed into a correlation mechanism that determines whether the observed combination of behaviors indicates malicious intent. This blended model significantly reduces false positives and ensures rapid protection even when malware has never been cataloged.
The SandBlast Multi-Layer Exploit Analyzer works alongside Threat Emulation Cloud architecture, Threat Extraction, Anti-Virus, and Anti-Bot. When malicious behavior is detected, the gateway or cloud sandbox immediately produces a verdict which is shared across gateways using immediate threat intelligence sharing.
Because of this multi-layer approach and integration, SandBlast Multi-Layer Exploit Analyzer is the correct answer.
Question 47:
In Check Point R81.20, which feature enhances Access Control policy efficiency by caching frequently matched rule outcomes so that subsequent packets matching the same criteria can bypass full rule evaluation?
A) Rule Match Acceleration Cache
B) Access Control FastMatch Engine
C) Layered Policy Optimization Cache
D) Unified Rule Pre-Decision Table
Answer:
B) Access Control FastMatch Engine
Explanation:
The Access Control FastMatch Engine in Check Point R81.20 significantly improves firewall performance by caching the results of Access Control rule matches. When traffic repeatedly matches the same rules, evaluating the full rule base becomes redundant and consumes unnecessary processing time. FastMatch solves this by storing the outcome of previous matches and applying that decision instantly to subsequent packets.
Option A, Rule Match Acceleration Cache, is descriptive but not a Check Point component. Option C, Layered Policy Optimization Cache, suggests a layered acceleration system but does not correspond to a real feature. Option D, Unified Rule Pre-Decision Table, also does not appear in Check Point documentation.
The FastMatch engine works by creating a cache key based on relevant packet attributes such as source, destination, services, ports, and associated identities. When a packet arrives, the engine checks the cache before examining the full rule base. If a matching key exists, the decision is applied instantly. This avoids resource-intensive rule scanning, especially in large rule bases where policies include multiple layers, inline layers, group objects, and identity-based conditions.
The engine supports both ordered and inline layer evaluation. It integrates with Access Control, Network Policy, Application Control, and Identity Awareness. Because it leverages SecureXL acceleration when possible, decisions are enforced with minimal latency.
FastMatch also improves the performance of distributed environments where multiple gateways share similar rules. It ensures consistent decisions across sessions and reduces load on CoreXL firewall instances.
One additional advantage is reduced CPU consumption during high-traffic periods. By avoiding repetitive rule evaluation, the firewall can process more connections per second without compromising accuracy.
Because of these capabilities, the Access Control FastMatch Engine is the correct answer.
Question 48:
In Check Point R81.20, which VPN monitoring function periodically verifies tunnel health by sending encrypted keepalive packets, ensuring that tunnels remain operational even if no user traffic is flowing?
A) IKE Encrypted Tunnel Keepalive
B) VPN Tunnel Health Monitor
C) Permanent Tunnel Keepalive Mechanism
D) IPsec Activity Verification Engine
Answer:
C) Permanent Tunnel Keepalive Mechanism
Explanation:
The Permanent Tunnel Keepalive Mechanism in Check Point R81.20 ensures that VPN tunnels remain active and healthy even during periods of inactivity. This is vital for environments where stable, always-on VPN connections are required, such as branch offices, IoT deployments, or distributed enterprises.
Option A, IKE Encrypted Tunnel Keepalive, sounds relevant but is not an official subsystem. Option B, VPN Tunnel Health Monitor, is descriptive but not the correct Check Point terminology. Option D, IPsec Activity Verification Engine, is also not a recognized component.
Permanent Tunnel Keepalive works by sending encrypted packets at periodic intervals. These packets are small, efficient, and designed solely to maintain state on remote gateways. Unlike traditional DPD (Dead Peer Detection), which is used for detecting unreachable peers, Permanent Tunnel Keepalive specifically ensures tunnel persistence even when communication is idle.
This functionality prevents tunnels from timing out due to inactivity, a common issue with certain ISPs, NAT devices, or firewalls that aggressively prune idle sessions. Without keepalives, gateways might drop IPSec security associations, causing delays when the next real packet arrives, since tunnels would need to be rebuilt.
Keepalive packets ensure the tunnels remain warm and ready for immediate use. This ensures fast failover, low latency for user traffic, and seamless operation of services that depend on continuous connectivity.
Thus, the correct answer is Permanent Tunnel Keepalive Mechanism.
Question 49:
In Check Point R81.20, which internal Threat Prevention mechanism correlates outbound DNS queries with subsequent connection attempts to detect malware that resolves command-and-control domains before initiating communication?
A) DNS-to-Connection Correlation Engine
B) Botnet Behavioral Resolution Tracker
C) C2 Domain Association Monitor
D) Outbound DNS Threat Linkage Analyzer
Answer:
A) DNS-to-Connection Correlation Engine
Explanation:
The DNS-to-Connection Correlation Engine in R81.20 enhances Anti-Bot detection accuracy by linking DNS queries with following connection attempts. Many types of malware first query DNS to resolve command-and-control domains before initiating outbound connections. By correlating these two events, the firewall can identify malicious communication attempts even if the IP address itself is not yet known to ThreatCloud.
Option B, Botnet Behavioral Resolution Tracker, is conceptually similar but not a real Check Point term. Option C, C2 Domain Association Monitor, sounds related but is not an official component. Option D, Outbound DNS Threat Linkage Analyzer, also does not correspond to an actual Threat Prevention subsystem.
The correlation engine analyzes DNS logs, identifies suspicious domains, and tracks which internal hosts initiated queries. When an outbound connection later targets one of these resolved IP addresses, the system examines the previous DNS activity. If the domain matches known malicious indicators, a botnet infection may be occurring.
The engine works even when malware uses fast-flux IP rotation or dynamically generated domains. Because malware must still resolve domains to IP addresses, DNS becomes a critical detection point. By correlating DNS activity with outgoing traffic, the firewall gains visibility into early stages of infection.
This mechanism integrates with ThreatCloud, Anti-Bot signatures, and machine learning patterns. It also contributes to rapid mitigation because the system can block outgoing connections immediately once correlation is established.
Therefore, the DNS-to-Connection Correlation Engine is the correct answer.
Question 50:
In Check Point R81.20, which mechanism ensures that critical configuration changes are simultaneously committed to both the active and standby cluster members, preventing state inconsistencies during failover?
A) Cluster Synced Configuration Manager
B) Active-Standby Parallel Commit Engine
C) Configuration State Synchronization Layer
D) Full Cluster Configuration Replication
Answer:
C) Configuration State Synchronization Layer
Explanation:
The Configuration State Synchronization Layer ensures consistent configuration across all ClusterXL members. When administrators modify firewall settings, policies, or cluster parameters, consistency between members is essential for reliable failover. Without synchronization, a failover event could cause mismatched settings, leading to dropped traffic or inconsistent behavior.
Option A, Cluster Synced Configuration Manager, is not an official name. Option B, Active-Standby Parallel Commit Engine, seems plausible but is not an actual Check Point subsystem. Option D, Full Cluster Configuration Replication, describes a process but is not the formal component name.
The Configuration State Synchronization Layer performs real-time synchronization of parameters including topology, interface settings, virtual IPs, cluster membership configurations, and other essential stateful attributes. It ensures that standby members mirror the active member’s configuration. This allows them to immediately take over roles without additional processing.
This mechanism is separate from state synchronization, which shares connection tables, NAT tables, and session information. Configuration synchronization specifically focuses on system-level properties and cluster-level settings. It ensures stable operation during maintenance windows, upgrades, or cluster transitions.
Because it guarantees consistent cluster configuration states, the Configuration State Synchronization Layer is the correct answer.
Question 51:
Which Check Point R81.20 mechanism ensures that Threat Prevention updates can be applied without interrupting existing connections by loading new signatures into memory while keeping the old signatures active until the transition completes?
A) Zero-Impact Signature Transition Engine
B) Threat Prevention Dual-Phase Update Loader
C) Live Signature Swap Framework
D) Incremental Threat Update Manager
Answer:
B) Threat Prevention Dual-Phase Update Loader
Explanation:
The Threat Prevention Dual-Phase Update Loader in Check Point R81.20 allows gateways to install new Threat Prevention signatures while continuing to process traffic using the previously active signature set. This dual-phase approach eliminates downtime and ensures uninterrupted security enforcement during update cycles. Traditional security appliances often require short interruptions when reloading large signature databases, but the dual-phase loader eliminates this issue by maintaining both signature sets in parallel until the switchover completes.
Option A, Zero-Impact Signature Transition Engine, sounds descriptive but is not an official Check Point component. Option C, Live Signature Swap Framework, resembles the concept but is not the correct term. Option D, Incremental Threat Update Manager, also does not correspond to any documented Threat Prevention subsystem.
The dual-phase loader begins by downloading new signature packages via the ThreatCloud update service. Once downloaded, the gateway unpacks and prepares the updated signatures in memory without affecting the active set. During this process, the firewall continues using the existing signatures to inspect traffic. Only when the preparatory stage finishes does the gateway enter the swap phase, at which point the new signature set becomes active. To ensure accuracy, the system momentarily synchronizes with kernel inspection engines so that no packets are processed with mixed signatures.
This mechanism improves reliability and reduces the risk of temporary exposure during updates. Gateways in large or distributed environments benefit greatly because traffic volumes are high and interruptions can affect critical services. Additionally, the mechanism ensures consistency across clusters, preventing failover inconsistencies due to signature mismatch.
The dual-phase loader integrates with Anti-Virus, Anti-Bot, IPS, and Threat Emulation protections. The seamless update process ensures that the security environment stays current with minimal administrative involvement. Combined with automated scheduling, this allows continuous protection even during peak hours. Because of these capabilities, the Threat Prevention Dual-Phase Update Loader is the correct answer.
Question 52:
In Check Point R81.20, which component improves CoreXL performance by dynamically distributing heavy inspection workloads across multiple firewall instances during periods of unbalanced CPU utilization?
A) CoreXL Adaptive Instance Rebalancer
B) Dynamic Firewall Workload Distributor
C) Inspection Load Equalization Engine
D) Smart Dynamic Core Allocation Module
Answer:
A) CoreXL Adaptive Instance Rebalancer
Explanation:
The CoreXL Adaptive Instance Rebalancer in Check Point R81.20 ensures that inspection workloads are intelligently distributed across all available CoreXL firewall instances. This helps maintain performance and stability during sudden traffic spikes or unbalanced CPU usage patterns. Without dynamic rebalancing, one instance may become overloaded while others remain underutilized, resulting in inefficient packet processing.
Option B, Dynamic Firewall Workload Distributor, is not the official term. Option C, Inspection Load Equalization Engine, sounds similar but is not an actual Check Point component. Option D, Smart Dynamic Core Allocation Module, also does not exist.
The Adaptive Instance Rebalancer continuously monitors CPU usage, memory consumption, packet inspection delays, and session distribution. When it detects an imbalance, it redistributes connections across available instances. This applies both to new connections and, whenever possible, existing sessions that can be reassigned without disrupting state.
The system uses algorithms that consider affinity, acceleration status, and connection type. For example, connections requiring deep inspection may be shifted to less-burdened instances, while light traffic may remain on accelerated paths. By ensuring more uniform load distribution, the gateway prevents bottlenecks and reduces latency for high-throughput environments.
In clusters, the rebalance logic also ensures cross-member consistency by aligning load patterns to minimize failover impact. With increased dependency on high-speed networks and cloud connectivity, dynamic load rebalancing is essential for maximizing hardware utilization.
Because of its accuracy, stability, and integration within the firewall kernel, the CoreXL Adaptive Instance Rebalancer is the correct answer.
Question 53:
Which Check Point R81.20 component ensures that partial TLS handshake information can be analyzed to detect anomalous patterns such as invalid cipher negotiation, malformed ClientHello fields, or unusual session properties?
A) TLS Handshake Integrity Scanner
B) Encrypted Session Parameter Analyzer
C) TLS Behavioral Pre-Inspection Engine
D) Secure TLS Metadata Validator
Answer:
C) TLS Behavioral Pre-Inspection Engine
Explanation:
The TLS Behavioral Pre-Inspection Engine in Check Point R81.20 analyzes metadata from the TLS handshake to detect anomalies before encryption is fully established. Even when full HTTPS Inspection is not enabled, the firewall still gains visibility into crucial TLS parameters such as cipher suites, supported TLS versions, SNI fields, key exchange patterns, and handshake anomalies.
Option A, TLS Handshake Integrity Scanner, describes a similar function but is not the actual Check Point component. Option B, Encrypted Session Parameter Analyzer, is not an official term. Option D, Secure TLS Metadata Validator, also does not match Check Point architecture.
The TLS Behavioral Pre-Inspection Engine focuses on identifying suspicious handshake behavior, including outdated TLS versions, insecure cipher requests, malformed extensions, or handshake sequences typical of malware or command-and-control frameworks. Certain types of malware intentionally craft irregular or non-standard ClientHello messages to evade detection or signature-based identification. By analyzing these characteristics before encryption begins, the engine can block suspicious traffic early in the process.
Additionally, this subsystem contributes to application identification, URL filtering categorization, and Access Control decisions. SNI extraction is a major function, helping classify encrypted applications without full decryption. The engine supports QUIC fallback detection, downgrade attacks, and handshake fuzzing attempts.
Because TLS negotiation occurs before encrypted payloads flow, this early inspection is extremely valuable. It gives security teams visibility without requiring the computational overhead of decrypting all HTTPS traffic. Its integration with ThreatCloud intelligence ensures rapid detection of new malicious TLS handshake fingerprints.
Given its role and importance, TLS Behavioral Pre-Inspection Engine is the correct answer.
Question 54:
Which Check Point R81.20 function ensures that file downloads are allowed to continue uninterrupted while sanitized versions are delivered to users when Threat Extraction replaces active content?
A) Parallel Threat Extraction Delivery Mode
B) Continuous Download-Sanitize Workflow
C) Threat Extraction Live Stream Mode
D) Inline Content Reconstruction Process
Answer:
A) Parallel Threat Extraction Delivery Mode
Explanation:
Parallel Threat Extraction Delivery Mode in R81.20 allows a file to be delivered while Threat Extraction simultaneously creates a sanitized version in the background. This ensures smooth user experience and rapid access to content, even when files undergo active content removal. Users receive files without harmful components, while file flow fluidity is maintained.
Option B, Continuous Download-Sanitize Workflow, is conceptually similar but not the official term. Option C, Threat Extraction Live Stream Mode, is not part of Check Point terminology. Option D, Inline Content Reconstruction Process, does not represent a formal component.
Threat Extraction works by removing active or potentially harmful elements such as macros, scripts, embedded objects, and dynamic content. Parallel delivery ensures that users avoid delays. This is especially important for environments with large email attachments or heavy web downloads.
The mechanism is also valuable because it reduces load on the gateway. The file flow is minimally disrupted, and users do not have to wait for the sanitized version before viewing content.
Therefore, Parallel Threat Extraction Delivery Mode is the correct answer.
Question 55:
Which Check Point R81.20 process allows VPN gateways to detect when a peer has changed its public IP due to dynamic ISP addressing, enabling automatic re-establishment of secure connectivity?
A) Dynamic Peer IP Awareness
B) VPN Auto Peer Update Mechanism
C) IKE Smart Peer Relocation
D) IPsec Peer Mobility Handler
Answer:
A) Dynamic Peer IP Awareness
Explanation:
Dynamic Peer IP Awareness allows VPN gateways to detect changes in a peer’s public IP address and automatically adjust tunnel parameters. This is essential for environments where peers use dynamic ISP connections that may change IP addresses unexpectedly.
Option B, VPN Auto Peer Update Mechanism, is descriptive but not the official term. Option C, IKE Smart Peer Relocation, does not exist. Option D, IPsec Peer Mobility Handler, is also not a real component.
When the peer’s IP changes, traditional VPN tunnels break because the gateway no longer recognizes the remote address. Dynamic Peer IP Awareness solves this by associating tunnel identity with certificates or shared secrets instead of just IP addresses. When the peer initiates a new IKE negotiation from a new IP, the gateway recognizes it as the same authenticated peer and re-establishes the tunnel automatically.
This is crucial for mobile gateways, cloud deployments, and small branch offices relying on consumer ISPs.
Thus, Dynamic Peer IP Awareness is correct.
Question 56:
Which Check Point R81.20 mechanism allows the gateway to immediately block malicious IP addresses seen in real-time by other gateways within the same organization using automatic threat intelligence propagation?
A) Intra-Org IP Blacklist Sync
B) Local Threat Intelligence Sharing Fabric
C) Rapid Gateway Threat Sync Engine
D) Anti-Bot Real-Time Intelligence Share
Answer:
B) Local Threat Intelligence Sharing Fabric
Explanation:
The Local Threat Intelligence Sharing Fabric allows gateways to share malicious indicators instantly across an organization. When one gateway detects a malicious IP or domain, the information spreads automatically, enabling all gateways to block the threat.
Option A, Intra-Org IP Blacklist Sync, is descriptive but not accurate. Option C, Rapid Gateway Threat Sync Engine, is not part of Check Point architecture. Option D, Anti-Bot Real-Time Intelligence Share, is not the correct subsystem name.
This mechanism enhances protection, especially against fast-moving threats. It ensures consistent enforcement across distributed and multi-site environments.
Because of its speed and efficiency, the Local Threat Intelligence Sharing Fabric is correct.
Question 57:
Which Check Point R81.20 feature helps reduce duplicate log entries by aggregating repeated identical events into summarized log messages?
A) Log Event Aggregation Engine
B) SmartLog Duplicate Compression
C) Unified Log Consolidation Layer
D) Repetitive Event Reduction System
Answer:
A) Log Event Aggregation Engine
Explanation:
The Log Event Aggregation Engine reduces repetitive log entries by aggregating identical or similar events. Security gateways generate massive logs, and without aggregation, storage and analysis become difficult.
Option B, SmartLog Duplicate Compression, is not correct. Option C, Unified Log Consolidation Layer, also is not an official term. Option D is not recognized.
The aggregation engine groups repeated occurrences and displays them as a single log with counters. This improves visibility and minimizes noise.
Therefore, Log Event Aggregation Engine is correct.
Question 58:
Which Check Point R81.20 subsystem analyzes CPU-level memory access sequences to detect advanced exploitation techniques like ROP and stack pivots?
A) CPU Exploit Vector Monitor
B) SandBlast CPU-Level Protector
C) Memory Execution Anomaly Detector
D) Threat Emulation Instruction-Level Scanner
Answer:
B) SandBlast CPU-Level Protector
Explanation:
SandBlast CPU-Level Protector detects low-level exploitation attempts by analyzing CPU memory execution patterns. These attacks cannot be detected by signatures because they manipulate execution flow.
Option A, CPU Exploit Vector Monitor, is not the correct name. Option C, Memory Execution Anomaly Detector, is not an official subsystem. Option D is also incorrect.
CPU-Level Protector blocks advanced exploits before payload execution, making it essential for zero-day defense.
Thus, SandBlast CPU-Level Protector is correct.
Question 59:
Which Check Point R81.20 optimization shortens the startup time of Threat Prevention blades by loading frequently-used signatures into priority memory segments?
A) Priority Signature FastLoad
B) Threat Prevention QuickStart Cache
C) Accelerated Signature Memory Loader
D) Threat Blade Rapid Init Engine
Answer:
A) Priority Signature FastLoad
Explanation:
Priority Signature FastLoad improves boot performance by loading important signatures first. This ensures that essential protections activate quickly following reboot or policy installation.
Option B, Threat Prevention QuickStart Cache, is not an official term. Option C and D also do not match Check Point documentation.
FastLoad helps maintain high availability and rapid readiness in enterprise environments.
Thus, Priority Signature FastLoad is correct.
Question 60:
Which Check Point R81.20 module accelerates HTTP and HTTPS traffic by caching classification results so repeated flows to the same domain bypass full inspection?
A) Web Classification FastCache
B) HTTP/HTTPS Accel Decision Cache
C) URL Filtering RapidMatch Table
D) Application Control Lookup Cache
Answer:
A) Web Classification FastCache
Explanation:
Web Classification FastCache accelerates HTTP and HTTPS traffic by caching domain classification results. When users repeatedly access common websites, the firewall can skip lengthy classification processes.
Option B, C, and D sound similar but do not match the official term.
FastCache improves performance, reduces CPU usage, and enhances user experience.
Thus, Web Classification FastCache is correct.
