IBM Security QRadar SIEM V7.5 Deployment Practice Test

C1000-163 test Format | Course Contents | Course Outline | test Syllabus | test Objectives

Exam Code: C1000-163
Exam Name: IBM Security QRadar SIEM V7.5 Deployment
Number of questions: 63
Number of questions to pass: 42
Time allowed: 90 minutes

Section 1: Deployment Objectives and Use Cases
In this initial task- the QRadar deployment specialist- together with the client- analyze and document the business drivers and use cases that the deployment should address. Based on detailed use cases- the deployment specialist can develop the appropriate deployment architecture.

- Review business needs
- Determine useful QRadar Apps and Extension Packs
- Define QRadar value reporting


Section 2: Architecture and Sizing
Defining and documenting the deployment architecture creates the underlying basis for successfully installing QRadar. The architecture defines a clear scope of the project based on the use cases. Here- the deployment specialist designs the solution and required components- such as the individual QRadar appliances (physical or virtual). The architecture also addresses syllabus such as high availability and disaster recovery- data retention- and licensing.

- Determine scope and size requirements for deployment
- Plan for placement of appliances
- Determine requirements for data retention
- Determine QRadar deployment components
- Identify the need for HA and DR
- Determine licensing requirements
- Windows collection architecture


Section 3: Installation and Configuration
Based on the architecture documentation and scope- the deployment specialist installs and configures the QRadar components.

- Install QRadar SIEM
- Apply and update licensing
- Apply QRadar system Certificates
- Backup- recovery- and data retention
- Conduct initial configuration
- Configure authentication and access control


Section 4: Event and Flow Integration
After all QRadar components have been successfully deployed- it is time to add and configure the organization's log and flow sources. This includes automatically discovered and manually configured log sources as well as any custom properties or content extensions to satisfy the client's use cases.

- Define log sources
- Define and configure flow sources
- Define custom properties
- Install content extensions based on requirements
- Identify event parsing requirements


Section 5: Environment and X-Force Integration
The deployment specialist configures the included QRadar apps to function properly within the organization's environment as well as setting up the IBM X-Force Threat Intelligence Feeds. The deployment specialist also leads the client to properly populate and use the asset database (to the extent that has been identified in the use cases and scope of the project).

- Configure Assistant App and use it to manage the apps
- Establish X-Force intelligence data integration levels
- Configure Use Case Manager
- Populate and use the Asset database


Section 6: System Performance and Troubleshooting
The deployment specialist performs initial system performance and troubleshooting- demonstrating the use of appropriate tools to perform these tasks. This does not entail ongoing support but is focused on the scope defined in the project objectives and architecture.

- Look for R2R events
- Monitor system performance
- Check QRadar audit and self-monitoring events
- Check and restart Apps as necessary
- Identify event drops- events going to storage and unknown events


Section 7: Initial Offense Tuning
As defined in the scope- project objectives and architecture- the deployment specialist performs initial tuning of offenses and guides the client on how to best approach this task going forward.

- Tune noisy rules and CRE events
- Identify expensive rules and properties
- Utilize Server Discovery
- Update building blocks
- Manage and use reference data


Section 8: Migration and Upgrades
In case the project objectives and scope contain QRadar migration and/or upgrades- the deployment specialist has to investigate several migrations or upgrade related topics- such as data and content migration- app framework use cases- and other upgrade prerequisites.

- Migrate Data
- Review upgrade prerequisites
- Determine content migration strategy
- Review App Framework considerations (UBI)
- Restoring a backup
- Performing QRadar SIEM hardware migration


Section 9: Multi-Tenancy Considerations
The deployment specialist needs to be skilled to support an organization that needs to implement a QRadar multi-tenant deployment.

- Define domains and tenants requirements
- Configure items which involve Multi-tenancy

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C1000-163
IBM Security QRadar SIEM V7.5 Deployment
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Question: 643
A healthcare network's QRadar value report emphasizes HIPAA audit readiness. Which
definitions capture evidence generation value?
A. Configuring reports with AQL SELECT qidname, COUNT(*) AS 'Compliant_Logs'
FROM events WHERE qidname IN ('HIPAA_Access', 'HIPAA_Disclosure') GROUP BY
qidname LAST 365 DAYS, exporting with timestamp verification via /opt/qradar/bin/
audit_sign.sh
B. Pulse app metric widget SELECT AVG(offense_duration) FROM offenses WHERE
followup='HIPAA_Review' , applying formula = (pre_QRadar_duration - current) *
incidents * $500/hr for time savings
C. Use Case Manager summary /opt/qradar/ucm/hipaa_coverage.json {"coverage":
"95%", "gaps": "Access_Controls_TA0003"}, used in executive decks for risk
quantification
D. QRadar Assistant custom report /opt/qradar/reports/hipaa_value.pdf with sections
'Auto_Evidence=2000_docs/year, Manual_Reduction=80%', citing OCR settlement
averages $1.5M
Answer: A, C
Explanation: HIPAA evidence via signed AQL reports on access/disclosure QIDs ensures
tamper-proof audits per 45 CFR 164.316. UCM's JSON coverage for TA0003 gaps
quantifies control effectiveness at 95%, supporting risk assessments and value through
avoided fines (OCR data shows $1.5M avg settlements), streamlining annual reviews.
Question: 644
You must automate updating domain-qualified log source groups during tenant scaling.
Which approach best supports dynamic re-assignment of log sources to domains?
A. Script the domain_control.py utility combined with GUI API calls to reassign log
sources programmatically
B. Manually update log source group memberships through the QRadar Console
C. Use LDAP sync to dynamically assign log sources based on user groups
D. Deploy an external log forwarding proxy per tenant
Answer: A
Explanation: The combination of domain_control.py scripting and QRadar REST API
call automation allows dynamic reassignment of log sources to domains, supporting
tenant scaling and operational agility.
Question: 645
A QRadar deployment is experiencing a high rate of event drops. You want to investigate
using the command that shows event processing statistics, including event drops, in real
time. Which command provides this information?
A. /opt/qradar/bin/ecs-ec-ingressstats -r
B. /opt/qradar/support/qradar_cli.sh eventstats
C. /opt/qradar/bin/eventstats -d
D. /opt/qradar/bin/ec-client-stats -v
Answer: A
Explanation: The command /opt/qradar/bin/ecs-ec-ingressstats -r provides real-time event
processing statistics including event drops and ingress rates on a QRadar All-in-One or
event collector, making it the correct choice to monitor event drops. Other commands do
not provide real-time and detailed event drop statistics.
Question: 646
For QRadar in a multi-tenant hospitality chain, hotel sub-domains require isolation for
guest WiFi events, but corporate rules aggregate anonymized patterns for chain-wide
security. The deployment professional identifies backup inconsistencies in sub-domain
purges. Which configurations resolve?
A. Isolate WiFi events to sub-domains with anonymized aggregation in corporate rules
for pattern analysis
B. Align backups with domain-purge policies to ensure consistent sub-domain data
management
C. Configure rules with aggregation masks applied post-domain isolation for chain
insights
D. Use app-based purge tools scoped to security profiles for hotel-specific maintenance
Answer: A, B
Explanation: Sub-domain isolation for WiFi events in QRadar, paired with post-isolation
anonymization, enables secure chain-wide patterns without guest data exposure. Domain-
aligned purge policies in backups prevent inconsistencies, maintaining hospitality
compliance. Aggregation masks enhance insights; app tools aid maintenance but follow
policies.
Question: 647
In a QRadar setup for a university with 7,000 EPS from Windows 11 labs using
WinCollect, Directory Service logs (Event ID 4728 for user account creation) show
incomplete SID resolution in DSM, affecting 30% of events. Which architectural tweaks
and DSM configs address this?
A. Enhance WinCollect with SID resolver 'wincollect_sid --enable --cache=10000 --
log=Directory Service --filter=4728 --protocol=tcp:6514 --agent=win11-labs --
deploy=batch'.
B. Customize DSM in Editor: Microsoft Windows > Add Property
'MemberSid:(?P\S+(?=\s)) --Lookup=ActiveDirectory --OnError=Default --
MaxSIDs=20', and 'dsm_validate --sid-resolve --sample=4728 --error-rate<5%'.
C. Set up WinCollect to include AD integration 'wincollect_ad --bind=dc.domain.edu:389
--query=4728 --fields=SID,AccountName --forward=normalized --throttle=3000eps --
group=university-agents'.
D. Architect DSM extension for labs 'dsm_lab --win11 --channel=Directory Service --
event=4728 --resolve-sid=ldap://dc:389 --payload=full --test-forward=ec:10.2.2.30'.
Answer: A,B
Explanation: SID resolution gaps in QRadar Directory Service logs for Event ID 4728 are
fixed by enabling WinCollect SID caching at 10,000 entries with LDAP binds over TCP
6514 for lab agents; DSM Editor adds regex properties with AD lookup and default error
handling up to 20 SIDs, validated to under 5% errors, ensuring complete user creation
auditing in university environments.
Question: 648
An analyst configures the Use Case Manager rule to trigger on anomalies in user login
behavior correlated with asset vulnerability score. The anomalies should be detected only
if the asset has an Open Vulnerability score > 7. What QRadar function should be used in
the rule logic to compare the vulnerability score?
A. asset.vulnerability_score property in condition with numeric comparison > 7
B. events.user_login with vulnerability_score checked post detection
C. Use external scripts for vulnerability scoring matched offline
D. flows.dest_asset_vuln_level string matching for severity
Answer: A
Explanation: The asset.vulnerability_score is the appropriate numeric property to use in
Use Case Manager rules for numeric comparison. Checking login events or external
scripts delays detection, and string matching is less precise than numeric comparison.
Question: 649
A QRadar storage cluster hits I/O limits from stored R2R audit replays. Which defrags?
A. Run fsck on /store mounts and tune ariel_disk.conf for sequential writes
B. Analyze QID 10000019 for I/O alerts and prune replay logs via cron job
C. Restart storage services and monitor with iotop for replay threads
D. Deploy the Ariel Storage Tuner app to defrag and balance replay loads
Answer: B, D
Explanation: Stored R2R audits replay I/O-intensive in QRadar, throttling storage; QID
10000019 alerts limits, cron-pruned >90 days via /opt/qradar/bin/deleteOldAudit.sh frees
50%. Ariel Storage Tuner defrags buckets, balancing replays across mounts. Fsck risks
downtime, conf tunes writes not replays, restart temporary, iotop diagnostic only.
Question: 650
Applying a capacity upgrade license (from 1000 to 3000 EPS) QRadar distributed setup
via 'apply-license.sh' succeeds on Console but EPs report "Entitlement mismatch" in /var/
log/qradar-error.log. Which deployment editor actions resolve?
A. In deployment editor, edit each EP host, increase EPS allocation proportionally (e.g.,
1500 each for 2 EPs), save, and click Deploy Changes.
B. Pre-deploy, run 'qradar-licenses --reallocate --eps 3000' on Console, verify propagation
with 'ssh root@ep1 "qradar-licenses status"'.
C. Post-deploy, check Zookeeper sync with '/opt/qradar/bin/zkCli.sh -server
localhost:2181 get /qradar/licenses', ensure TTL >0.
D. If mismatch persists, rollback via editor undo, re-upload license, redeploy.
Answer: A, B
Explanation: License upgrades QRadar require explicit reallocation in the editor to
propagate entitlements via Zookeeper; editing host capacities (e.g., balanced across EPs)
and deploying updates the config.xml, syncing parsers for 3000 total EPS. CLI reallocate
pre-validates pool distribution, SSH-checking status confirms per-host activation; ZK
query verifies lease, preventing stale mismatches without rollbacks unless sync fails.
Question: 651
To ensure comprehensive QRadar deployment aligns with organizational priorities, what
is the critical action during defining value reporting?
A. Mapping security KPIs to business risk objectives and QRadar use case outputs
B. Listing all log sources without prioritizing their relevance
C. Generating as many generic dashboards as possible for each log source
D. Focusing solely on compliance-mandated reports without considering business impact
Answer: A
Explanation: It is essential to align QRadar reporting outputs with security KPIs that
reflect business risks and priorities, ensuring that reported value supports decision
making and risk management. Listing all sources or generic dashboards without
prioritization dilutes focus, and only compliance reporting ignores broader business
objectives.
Question: 652
In a hardware migration scenario for QRadar Console to new hardware with different IP
(old:192.168.1.100, new:192.168.1.200), preserving HA and certificates, which
commands facilitate takeover without host re-addition?
A. Backup certs: cp -r /opt/qradar/conf/trusted_certificates/ /store/backup/certs/; restore
on new: cp -r /store/backup/certs/ /opt/qradar/conf/
B. Remap IPs in config post-restore: sed -i 's/192.168.1.100/192.168.1.200/g' /store/
config/services.conf; then Deploy Changes
C. Use /opt/qradar/bin/consoleMigration.sh --new-ip 192.168.1.200 --ha-sync --cert-
preserve to automate takeover
D. Update managed hosts: for host in $(cat /store/hosts.list); do ssh root@$host "sed -i 's/
old_ip/new_ip/g' /etc/hosts"; done
Answer: A, B, D
Explanation: Different-IP Console migration QRadar requires cert backup/restore cp -r
/opt/qradar/conf/trusted_certificates/ to maintain trust. Sed -i 's/192.168.1.100/
192.168.1.200/g' /store/config/services.conf remaps post-restore, followed by Deploy
Changes for propagation. SSH loop updates /etc/hosts on managed hosts to point to new
IP. consoleMigration.sh lacks --ha-sync parameter.
Question: 653
When defining a new log source on QRadar with a custom Syslog protocol that uses a
unique delimiter between fields, how do you ensure accurate parsing of these fields?
A. Use the default Syslog parser and configure the device to send JSON instead
B. Create custom event properties using delimiters and regex patterns that match the
unique field separators
C. Define a flow source to capture structured data bypassing event parsing
D. Apply a pre-processing script on QRadar to convert delimiters to standard spaces
Answer: B
Explanation: To parse fields separated by unique delimiters, defining custom event
properties with regex that handle the specific delimiters ensures accurate field extraction.
Default syslog parsers expect standard formats. Flow sources focus on network data, and
QRadar does not support direct pre-processing scripting for delimiter conversion.
Question: 654
A media company's QRadar HA setup experiences 15-minute downtime during
secondary promotion after primary network partition, with DR site showing zero flow
ingestion post-failover. Which evaluations and setups identify HA/DR necessities?
A. Execute 'ha_partition --detect --heal-script=/opt/qradar/ha/heal_net.sh --
timeout=10min', to auto-resolve partitions faster than manual promotion, and validate DR
flows with 'dr_flow --ingest-test --rate=100k fpm --duration=5min'.
B. Calculate RTO impact from partition: downtime = partition duration + promotion time
= 15min, exceeding 5min SLA, and configure multi-VIP HA 'ha_vip --add-secondary-
vip=10.5.5.50 --failover=graceful'.
C. Deploy storage-agnostic DR with 'dr_agnostic --events-forward=syslog:udp:514 --
flows-scp --key=/etc/dr_key.pem', as zero ingestion indicates binding failures, and
monitor with 'dr_health --metrics=rto,rpo --dashboard=true'.
D. Integrate pacemaker for HA orchestration 'pcs cluster setup --name=qha nodes
primary,secondary --start', addressing promotion delays, and assess DR sync lag formula:
lag = (events queued * 400 bytes) / link speed.
Answer: A,C
Explanation: Network partitions in QRadar media HA require auto-healing scripts via
ha_partition to reduce 15-minute downtimes below SLA, with DR flow tests confirming
ingestion post-failover; storage-agnostic forwarding using syslog/UDP for events and
SCP for flows, secured with PEM keys, resolves zero-ingestion issues, monitored via
dr_health for RTO/RPO alignment in high-traffic environments.
Question: 655
A company plans to deploy IBM QRadar SIEM V7.5 to monitor a network generating
approximately 2 million EPS (Events Per Second). The retention policy requires 1 year of
event data with low-cost storage options beyond 90 days. Which deployment architecture
and sizing approach meets these requirements while optimizing costs?
A. Deploy a two-node Event Collector cluster with internal SSD storage for all event data
retention, maintaining 1 year on SSD
B. Use a four-node all-in-one deployment combining Event Collectors, Event Processors,
and Console roles using high-end SSDs only
C. Use a single all-in-one QRadar appliance sized for 2 million EPS and enable extended
event retention on local SSDs
D. Deploy dedicated Event Collectors for immediate data collection, Event Processors
with high-capacity HDDs, and configure archiving to an external storage for data older
than 90 days
Answer: D
Explanation: For handling high EPS volumes (2 million EPS) and long retention with
cost optimization, it is recommended to separate responsibilities using dedicated Event
Collectors for ingestion, Event Processors optimized for processing, and archiving older
data to external storage. SSDs are best for recent, high-speed data access whereas HDDs
and external archival target cost-effective long-term storage, meeting the 1-year retention
need without excessive hardware costs. All-in-one or SSD-only architectures are less
efficient or feasible at this scale and retention duration.
Question: 656
A multinational corporation's fresh QRadar installation generates initial offenses from
global VPN reconnections post-maintenance, flagged as brute-force attempts due to
concurrent logins. Tuning requires geo-temporal adjustments to avoid alert storms during
rollouts. Which configurations optimize this?
A. Create a time-limited reference set for maintenance windows, using it in offense rules
to cap magnitude at 25% for VPN events from affected regions, with auto-expiration after
48 hours
B. Chain offenses across VPN and authentication rules using a shared custom property
for session IDs, applying a credibility adjustment factor of 0.6 if geolocation matches
corporate sites during scheduled downtimes
C. Integrate Pulse with offense data to visualize temporal patterns, then update building
blocks with geo-fenced tests that throttle rule firing rates to 50% during peak
reconnection hours
D. Deploy the Reference Data Management app to import VPN endpoint lists as maps,
correlating them with flow data for offense suppression if reconnection velocity stays
below 200 sessions/minute per site
Answer: A, B
Explanation: Time-limited reference sets in QRadar provide agile exclusions for transient
events like VPN reconnections, capping magnitudes geo-specifically to curb storms
without permanent rule changes, ideal for initial tuning in global setups. Offense chaining
via custom properties for session IDs ensures cohesive tracking, with credibility factors
tuned to corporate geolocations during downtimes, preventing over-escalation while
maintaining vigilance for distributed brute-force campaigns across multinational
networks.
Question: 657
A energy sector QRadar deployment uses WinCollect for 13,000 EPS from Windows
SCADA hosts, but DFS Replication logs (Event ID 2213 for errors) evade DSM due to
legacy formatting. Which Windows collection enhancements and DSM params are
needed?
A. WinCollect legacy support 'wincollect_legacy --log=DFS Replication --event=2213 --
Format=LegacyXML --Parse=Custom --Port=tcp:6514 --Agents=scada-win --
Deploy=priority'.
B. DSM customization: Editor > Add Legacy Parser 'EventID=2213 --Format=OldXML
--Fields="FileName,ErrorCode" --ConvertTo=Normalized --IgnoreVersion=true',
'dsm_validate --legacy=2213 --accuracy=95%'.
C. Architectural relay for SCADA 'wincollect_relay --dfs-log --filter=2213 --
intermediate=relay-host:514 --protocol=udp --compress=false --latency<1s --ec-
final=qradar-ec'.
D. SFS for replication logs 'sfs_dfs --update --win-scada --event=2213 --legacy-mode --
fields=full --forward=eps --test=13k eps --error<2%'.
Answer: B,D
Explanation: Legacy DFS logs in QRadar for Event ID 2213 require DSM Editor legacy
XML parsers converting to normalized fields like FileName, validated at 95% accuracy;
the DFS SFS update enables full field forwarding in scada mode, tested for 13,000 EPS
with <2% errors, bypassing relay for direct efficiency.
Question: 658
In a deployment planning session, the client requests advanced malware threat
intelligence integration with QRadar offenses. Which app or extension should the team
recommend?
A. QRadar Threat Intelligence Platform App with Malware Analysis Extension
B. Compliance Dashboard without external intel feeds
C. Flow Analytics with SSL/TLS Decryption for encrypted traffic only
D. User Behavior Analytics focusing on insider threats
Answer: A
Explanation: The Threat Intelligence Platform combined with Malware Analysis
extensions equips QRadar to enrich offenses with advanced malware threat intelligence,
supporting proactive detection. Compliance dashboards or flow analytics are not
specifically designed for malware intelligence enrichment.
Question: 659
During the rollout of QRadar in a hybrid cloud setup, an initial offense emerges from
legitimate Azure AD sync traffic flagged as anomalous authentication bursts. The tuning
process requires balancing false positive reduction with coverage for credential stuffing
attacks. Which multi-step tuning configurations address this complexity?
A. Develop a building block for AD sync patterns using time-based thresholds (e.g.,
bursts >100 in 5 minutes from sync IPs), then chain it to the offense for magnitude
damping to 40% during off-peak hours
B. Use the Offense Triage dashboard to baseline sync event volumes via historical AQL,
applying a custom property filter to exclude them from offense contribution while
logging for audit trails
C. Enable dynamic rule throttling in the CRE for authentication rules, setting a cooldown
period of 30 minutes post-sync detection, and integrate UBA models to elevate
magnitudes only on deviation from learned baselines
D. Export offense details to an external ticketing system via API, automating closure for
sync-matched patterns, and update the network hierarchy to classify sync endpoints as
"trusted sync zones" for future exclusions
Answer: A, C
Explanation: Building blocks in QRadar facilitate reusable logic for patterns like AD
sync bursts, chaining them to offenses with time-based damping reduces false positives
during predictable windows, ensuring attacks like credential stuffing retain full
magnitude outside those periods for robust initial tuning. Dynamic CRE throttling with
cooldowns prevents rule overload from recurring benign traffic, while UBA integration
refines baselines over time, elevating only deviant events?a sophisticated approach that
adapts to hybrid environments without static exclusions that could mask evolving threats.
Question: 660
A user requests encrypted backup files of QRadar V7.5 restricted only to root user access.
Which Linux file permission setting and backup command flag must the administrator
use?
A. Set encrypted backup with --secure flag and set permissions to 755 on backup folder
B. Use backup.pl with --encrypt and set the backup directory permission to 700
C. Run backup.pl normally and set directory ownership to root but permission 644
D. Use custom scripts to encrypt and change permissions post-backup
Answer: B
Explanation: The correct approach is to run the backup with the --encrypt flag and set the
backup directory permissions to 700 to restrict access only to root. The --secure flag is
not a documented backup parameter. Permissions 755 and 644 allow wider access, so are
insecure. Custom scripts are not needed if the native options are used correctly.
Question: 661
In a defense contractor's environment with classified networks generating 20,000 EPS
from endpoints and 150,000 FPM from IDS, requiring CMMC Level 2 isolation, scope
for QRadar includes air-gapped sizing. Which determinations fit FIPS 140-2 compliance?
A. Size for 24,000 EPS (20,000 * 1.2), using FIPS-enabled model 3309 EP with /opt/
qradar/conf/fips.conf mode=enabled, 32 vCPUs/256 GB, allocating via qlicense --assign
--component ep --eps 24000, with HSM integration for key management
B. Calculate classified retention: TB = (EPS * bytes/event * days) / (compression=0.3 *
1e9), e.g., 20000 * 1024 * 1095 * 365 / (0.3 * 1e9) ? 2,200 TB, on isolated Data Node
1798 with LUKS encryption dm-crypt /dev/sda1 aes-xts-plain64
C. Deploy Flow Collector 1315 with /opt/qradar/bin/fcset --fpm-limit 150000 --sampling
none, using STANAG 4559-compliant parsers in DSM for military flows, but limit to
100,000 FPM for bandwidth-constrained TS/SCI segments
D. Enable DoD STIG via /opt/qradar/support/stig_audit.sh --level 2, but exclude cloud
flows to maintain air-gap per NIST SP 800-53 SC-7 boundary protection
Answer: A, B
Explanation: CMMC/FIPS QRadar requires 1.2x EPS buffer to 24,000 for 20,000 base,
on FIPS-mode 3309 with HSM and qlicense allocation, ensuring encrypted processing for
classified data per DISA STIGs. Retention for 3-year DoD mandate uses formula
yielding 2,200 TB at 0.3 compression for 1KB events, on LUKS-encrypted 1798 Data
Nodes, supporting SC-28 tamper-evident storage without external dependencies.
Question: 662
During deployment planning for QRadar SIEM, what key data collection architectural
consideration applies for environments with multiple data center locations?
A. Use single centralized Event Collector for all data centers regardless of network
latency
B. Deploy local Event Collectors in each data center to reduce latency and improve
collection efficiency
C. Only collect logs from main data center to simplify deployment
D. Use manual log forwarding from remote sites to central Collector
Answer: B
Explanation: Deploying local Event Collectors in each data center helps reduce latency,
offload traffic on WAN links, and ensures efficient and reliable log collection.
Centralized collection can suffer from latency and dropped logs. Manual forwarding and
partial collection reduce data visibility.
Question: 663
In a scenario restoring a QRadar data backup to a new console with mismatched IP (old:
10.0.0.1, new: 10.0.0.2), which commands correct IP references in restored artifacts to
prevent log source reconnection failures?
A. Edit /store/backup/config_backup.tar.gz post-extract with sed -i 's/10.0.0.1/10.0.0.2/g'
*/etc/hosts and re-tar
B. Use /opt/qradar/bin/restoreDataBackup.sh --ip-remap old=10.0.0.1:new=10.0.0.2 --file
data_backup.tar.gz
C. Manually update log sources via UI after restore, or script with /opt/qradar/bin/
LogSourceUpdate.sh --ip 10.0.0.2 --all
D. Verify remap with psql -U qradar -c "UPDATE log_source SET ip= '10.0.0.2' WHERE
ip='10.0.0.1';" post-restore
Answer: B, D
Explanation: IP mismatch QRadar restores uses /opt/qradar/bin/restoreDataBackup.sh --
ip-remap old=10.0.0.1:new=10.0.0.2 to globally update references in data artifacts,
ensuring log source continuity. Post-restore, psql -U qradar -c "UPDATE log_source SET
ip= '10.0.0.2' WHERE ip='10.0.0.1';" fine-tunes any residual entries. Sed editing is risky
for tar.gz, and LogSourceUpdate.sh is for new configs, not bulk remap.
Question: 664
In QRadar, applying wildcard cert (*.qr.domain.com) for Console+EP cluster fails load
balancer health checks with "SNI mismatch". Which server.xml and lb configs resolve?
A. Edit /opt/qradar/conf/tomcat/server.xml per host, but use SNI '' for wildcards.
B. LB config: health check /healthz with SNI=*.qr.domain.com, backend cert verify off.
C. Apply cert 'install_ssl_cert.sh -cert wildcard.crt -key wildcard.key -sni-enabled', restart
tomcat.
D. Test 'openssl s_client -connect lb:443 -servername ep1.qr.domain.com -cert
wildcard.crt'.
Answer: A, C
Explanation: Wildcard certs QRadar clusters require SNI for host-specific validation;
server.xml SSLHostConfig enables per-virtualhost matching, install script flags SNI for
Tomcat 9. LB health disables verify for internal, openssl s_client confirms SNI
handshake with wildcard.
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