35 Use Cases using Splunk SIEM to reduce False Positives

Use Case Name	1. BRUTE FORCE ATTACK DETECTION ON WINDOWS SYSTEMS
Goal	Excludes routine status codes (200, 301) to reduce noise and focus on potential issues. Outcome 1 Identify brute force login attempts by monitoring repeated failed login events within a short period, adjusting thresholds to reduce false positives from user error or network latency.
Detection Rule:	index= "web_logs" status_code!=200 status_code!=301 | stats count by status_code
Outcome:	Excludes routine status codes (200, 301) to reduce noise and focus on potential issues.
Use Case Name	2. SUSPICIOUS EMAIL ATTACHMENTS DETECTION IN PROOFPOINT
Goal	Detect emails with potentially malicious attachments using Proofpoint logs and filter out known safe file types.
Detection Rule:	index= "proofpoint" sourcetype= "pp:attachment" | where attachment_malicious= "true" AND NOT (file_extension IN ("pdf", "docx", "xlsx"))
Outcome:	Flags emails with attachments that are likely malicious and have suspicious file types, reducing false positives from commonly used safe file types.
Use Case Name	3. UNAUTHORIZED IAM ROLE CHANGE IN AWS CLOUDTRAIL
Goal	Monitor unauthorized changes to IAM roles to prevent privilege escalation, excluding expected changes from trusted service accounts.
Detection Rule:	index= "aws-cloudtrail" eventName= "UpdateRole" | where NOT userIdentity.arn IN ("arn:aws:iam::123456789012:role/TrustedRole")
Outcome:	Detects suspicious role modifications only from unexpected sources, reducing false positives from known maintenance or automation accounts.
Use Case Name	4. UNUSUAL FILE DELETION ON WINDOWS SERVERS
Goal	Detect suspicious file deletions on critical Windows directories while filtering out regular maintenance events.
Detection Rule:	index= "wineventlog" EventCode=4663 ObjectType= "File" | where Object_Name LIKE "%critical_directory%" AND Access_Mask= "DELETE" | stats count by User, Computer | where count > 3
Outcome:	Alerts when more than three file deletions occur in critical directories by the same user within an hour, minimizing false positives from typical user actions.
Use Case Name	5. HIGH DATA TRANSFER TO EXTERNAL IPS IN CLOUD ENVIRONMENT
Goal	Detect potentially unauthorized data exfiltration by monitoring high data transfer to unknown IP addresses outside the organization.
Detection Rule:	index= "cloud-traffic" direction= "outbound" | stats sum(bytes_sent) as total_data by dest_ip | where total_data > 50000000 AND NOT dest_ip IN ("trusted_ip1", "trusted_ip2")
Outcome:	Identifies large data transfers to untrusted IPs, reducing false positives by excluding known, trusted destinations.
Use Case Name	6. SUSPICIOUS COMMAND EXECUTION IN WINDOWS SYSMON
Goal	Detect execution of potentially malicious commands on Windows systems, filtering out legitimate administrative actions.
Detection Rule:	index= "sysmon" EventID=1 | search CommandLine IN ("*powershell* -enc*", "*cmd.exe /c*") | where NOT Account_Name IN ("admin_user1", "admin_user2")
Outcome:	Flags unusual command-line usage while excluding expected administrative accounts, reducing noise from legitimate actions.
Use Case Name	7. EXCESSIVE FAILED EMAIL LOGINS IN PROOFPOINT
Goal	Identify potential account compromise attempts by tracking repeated failed email login attempts.
Detection Rule:	index= "proofpoint" sourcetype= "pp:login" | stats count by user, src_ip | where count > 10 AND status= "failed"
Outcome:	Detects high-volume failed login attempts to email accounts, with thresholds to avoid alerts from typical user errors.
Use Case Name	8. ABNORMAL CPU USAGE ON CLOUD V
Goal	Identify potential cryptocurrency mining or malware infection by monitoring unusual CPU spikes in cloud VMs.
Detection Rule:	index= "cloud-metrics" metric_name= "cpu_usage" | stats avg(cpu) as avg_cpu by host | where avg_cpu > 90
Outcome:	Flags VMs with unusually high CPU usage, potentially indicating malicious processes while reducing false positives by focusing on high averages.
Use Case Name	9. C2 COMMUNICATION DETECTION IN SURICATA IDS
Goal	Identify Command and Control (C2) traffic by monitoring connections to suspicious domains or IPs flagged by Suricata, excluding known safe domains.
Detection Rule:	index= "suricata" event_type= "alert" | search dest_ip IN ("known_c2_ip1", "known_c2_ip2") | where NOT dest_domain IN ("safe_domain1.com", "safe_domain2.com")
Outcome:	Detects suspected C2 traffic while excluding known safe domains, reducing unnecessary alerts.
Use Case Name	10. MULTIPLE FILE ACCESS FAILURES ON WINDOWS SHARES
Goal	Identify possible unauthorized attempts to access sensitive files by tracking repeated access failures on shared directories.
Detection Rule:	index= "wineventlog" EventCode=4663 Access_Mask= "0x2" | stats count by Object_Name, Account_Name | where count > 5
Outcome:	Triggers alerts when more than five access failures occur on sensitive files, minimizing false positives by focusing on excessive failures.
Use Case Name	11. SUSPICIOUS OUTBOUND NETWORK ACTIVITY FROM CROWDSTRIKE EDR
Goal	Identify potentially malicious outbound connections by monitoring unusual network activity flagged by CrowdStrike, excluding known safe applications.
Detection Rule:	index= "crowdstrike" event_type= "network_activity" direction= "outbound" | where NOT process_name IN ("chrome.exe", "outlook.exe")
Outcome:	Detects unusual outbound connections by unknown processes, reducing noise by filtering out known, legitimate applications.
Use Case Name	12. UNAUTHORIZED ACCESS TO CRITICAL DATABASES
Goal	Monitor unexpected access to critical databases to identify potential insider threats or unauthorized access attempts.
Detection Rule:	index= "db-logs" event_type= "login" | where database_name= "critical_db" AND user NOT IN ("db_admin1", "db_admin2")
Outcome:	Flags unauthorized login attempts to sensitive databases, reducing alerts by excluding expected administrative users.
Use Case Name	13. DETECTION OF LARGE EMAIL ATTACHMENTS WITH SUSPICIOUS CONTENT
Goal	Identify potential data exfiltration or phishing attempts by monitoring large email attachments flagged as suspicious.
Detection Rule:	index= "proofpoint" sourcetype= "pp:email" | where attachment_size > 10485760 AND attachment_malicious= "true"
Outcome:	Detects suspicious large email attachments, reducing false positives by filtering for both size and malicious indicators.
Use Case Name	14. MONITORING FOR ANOMALOUS NETWORK SCANNING BEHAVIOR
Goal	Detect potential recon activity by monitoring for IPs performing a high number of port scans, filtering known vulnerability scanners
Detection Rule:	index= "network-traffic" event= "port_scan" | stats count by src_ip | where count > 50 AND NOT src_ip IN ("trusted_scanner_ip")
Outcome:	Alerts on scanning behavior, reducing noise by excluding trusted network scanners
Use Case Name	15. SUSPICIOUS POWERSHELL COMMANDS WITH BASE64 ENCODING
Goal	Detect potential obfuscation or malware execution through PowerShell commands with encoded payloads
Detection Rule:	index= "wineventlog" EventCode=4104 | where CommandLine IN ("* -enc *") | stats count by User, Computer
Outcome:	Flags encoded PowerShell commands, reducing false positives by focusing on encoding indicators.
Use Case Name	16. UNUSUAL NETWORK ACTIVITY IN SURICATA FOR INTERNAL HOSTS
Goal	Detect internal hosts generating unusual traffic patterns consistent with malware or botnet activity, excluding known backup or scanning IPs.
Detection Rule:	index= "suricata" event_type= "network" | stats count by src_ip | where count > 100 AND NOT src_ip IN ("backup_ip", "scanner_ip")
Outcome:	Flags suspicious network patterns from internal hosts, reducing false positives from known sources.
Use Case Name	17. EXCESSIVE FILE DOWNLOADS FROM CLOUD STORAGE
Goal	Identify potential data exfiltration by monitoring unusual bulk downloads from cloud storage services
Detection Rule:	index= "cloud-storage-logs" action= "download" | stats count by user, bucket | where count > 100 AND NOT user IN ("backup_service", "trusted_user")
Outcome:	Detects high-volume downloads, filtering out trusted services and regular backup activities to minimize false positives.
Use Case Name	18. MULTIPLE FAILED LOGIN ATTEMPTS ON CRITICAL DATABASE FILE DOWNLOADS FROM CLOUD STORAGE
Goal	Detect potential brute force attempts on database logins
Detection Rule:	index= "db-logs" action= "failed_login" | stats count by user, db_name | where count > 5 AND db_name= "critical_db"
Outcome:	Flags account with more than five failed login attempts on critical databases, reducing noise by focusing on high-value assets.
Use Case Name	19. DETECTION OF UNUSUAL SERVICE STARTUP IN WINDOWS SERVERS
Goal	Identify malicious persistence by monitoring unusual service startups on Windows servers.
Detection Rule:	index= "wineventlog" EventCode=7045 | where NOT Service_Name IN ("expected_service1", "expected_service2")
Outcome:	Flags startup of unexpected services, excluding known and safe services to avoid false positives.
Use Case Name	20. LARGE VOLUME OF OUTBOUND DNS REQUESTS FROM A SINGLE HOST
Goal	Detect potential data exfiltration or tunneling by monitoring high volumes of DNS requests from a single host.
Detection Rule:	index= "dns-logs" | stats count by src_ip | where count > 1000 AND NOT src_ip IN ("trusted_dns_ip")
Outcome:	Detects unusually high DNS query volume, excluding known DNS servers to reduce noise.
Use Case Name	21. ANOMALOUS PRIVILEGED COMMAND EXECUTION ON LINUX SERVERS
Goal	Detect potential abuse of sudo commands by monitoring unusual privileged commands on Linux.
Detection Rule:	index= "linux-logs" command= "sudo" | where Command IN ("*netcat*", "*nc*", "*nmap*")
Outcome:	Flags potentially dangerous commands executed with sudo privileges, focusing on network-related tools to avoid false positives.
Use Case Name	22. UNUSUAL DATA TRANSFER IN AWS CLOUD INFRASTRUCTURE
Goal	Identify abnormal data transfer volumes to external IP addresses in AWS, excluding trusted endpoints.
Detection Rule:	index= "aws-logs" action= "Transfer" | stats sum(bytes) as total_bytes by dest_ip | where total_bytes > 50000000 AND NOT dest_ip IN ("trusted_ip1", "trusted_ip2")
Outcome:	Flags large outbound data transfers to unknown IPs, reducing false positives by filtering trusted destinations.
Use Case Name	23. UNAUTHORIZED ACCESS TO S3 BUCKETS
Goal	Detect potential unauthorized access attempts to sensitive S3 buckets in AWS.
Detection Rule:	index= "aws-s3" eventName= "GetObject" OR eventName= "PutObject" | where bucket_name IN ("sensitive_bucket") AND user NOT IN ("trusted_user1", "trusted_user2")
Outcome:	Alerts on access to sensitive S3 buckets by unknown users, reducing alerts from trusted users.
Use Case Name	24. SUSPICIOUS BROWSER ACTIVITY INDICATING PHISHING
Goal	Identify potential phishing activity by monitoring access to known phishing domains.
Detection Rule:	index= "proxy-logs" action= "browse" | search dest_domain IN ("known_phishing_domain1.com", "known_phishing_domain2.com")
Outcome:	Detects access to known phishing sites, with a rule based on threat intelligence sources.
Use Case Name	25. MULTIPLE FAILED FILE ACCESS ATTEMPTS ON LINUX SHARES
Goal	Monitor suspicious activity by tracking failed access attempts on shared Linux directories.
Detection Rule:	index= "linux-logs" event_type= "file_access_failed" | stats count by user, file_path | where count > 5
Outcome:	Alerts on repeated failed file access attempts, indicating possible unauthorized access attempts.
Use Case Name	26. DETECTION OF EXECUTABLE FILES IN EMAIL ATTACHMENTS (PROOFPOINT)
Goal	Identify potentially malicious emails by detecting executable file attachments.
Detection Rule:	index= "proofpoint" sourcetype= "pp:email" | where attachment_file_type= "exe"
Outcome:	Flags emails containing executable attachments, which are more likely to be malicious.
Use Case Name	27. EXCESSIVE PRIVILEGE ESCALATION ATTEMPTS ON WINDOWS SYSTEMS
Goal	Detect suspicious privilege escalation by monitoring repeated attempts to elevate privileges on Windows.
Detection Rule:	index= "wineventlog" EventCode=4674 | stats count by User | where count > 3
Outcome:	Flags users with multiple privilege escalation attempts, reducing noise by focusing on excessive attempts.
Use Case Name	28. UNUSUAL COMMAND LINE ARGUMENTS IN LINUX PROCESSES
Goal	Detect suspicious processes with unexpected command-line arguments, which may indicate malicious activity.
Detection Rule:	index= "linux-logs" event= "process_creation" | where CommandLine IN ("*curl*", "*wget*") | where NOT User IN ("safe_user")
Outcome:	Flags processes with network-related commands, reducing false positives by excluding expected administrative users.
Use Case Name	29. MULTIPLE ACCOUNT LOCKOUTS IN A SHORT PERIOD
Goal	Detect potential brute-force attacks or password spraying by monitoring frequent account lockouts.
Detection Rule:	index= "wineventlog" EventCode=4740 | stats count by Account_Name | where count > 5
Outcome:	Flags accounts that have been locked out multiple times, which may indicate a targeted attack.
Use Case Name	30. SUSPICIOUS PORT SCANNING IN NETWORK TRAFFIC
Goal	Detect internal or external port scans by monitoring for unusual numbers of open port checks.
Detection Rule:	index= "network-traffic" event= "port_scan" | stats count by src_ip | where count > 50
Outcome:	Detects potential recon activity from IPs scanning multiple ports.
Use Case Name	31. DETECTION OF MALWARE FILE HASHES IN CROWDSTRIKE EDR
Goal	Identify potential malware by matching file hashes from CrowdStrike with known malicious hashes.
Detection Rule:	index= "crowdstrike" event_type= "file_event" | where file_hash IN ("malicious_hash1", "malicious_hash2")
Outcome:	Flags files with hashes matching known malware, reducing noise by filtering safe files
Use Case Name	32. UNUSUAL USE OF ENCODING OR OBFUSCATION IN POWERSHELL COMMANDS
Goal	Detect potentially malicious PowerShell activity with obfuscation techniques.
Detection Rule:	index= "sysmon" EventID=4104 | search CommandLine IN ("* -enc *")
Outcome:	Alerts on obfuscated PowerShell commands, typically associated with malicious activities.
Use Case Name	33. DETECTION OF ANOMALOUS NETWORK TRAFFIC IN SURICATA IDS
Goal	Identify suspicious network traffic patterns from known attack vectors in Suricata.
Detection Rule:	index= "suricata" event_type= "alert" | search dest_ip IN ("suspicious_ip1", "suspicious_ip2")
Outcome:	Detects connections to known malicious IPs, filtering out known safe connections.
Use Case Name	34. TRACKING PRIVILEGED FILE ACCESS ATTEMPTS ON WINDOWS
Goal	Monitor sensitive file access by privileged users, excluding administrative operations.
Detection Rule:	index= "wineventlog" EventCode=4663 | where Object_Type= "file" AND Access_Mask= "Write" AND Account_Name NOT IN ("admin_user")
Outcome:	Flags sensitive file access, reducing false positives from known admin activity
Use Case Name	35. DETECTION OF RDP CONNECTIONS FROM EXTERNAL IPS
Goal	Identify unauthorized RDP connections from external sources, excluding known VPN or admin IPs.
Detection Rule:	index= "wineventlog" EventCode=4624 LogonType=10 | where src_ip NOT IN ("vpn_ip1", "vpn_ip2")
Outcome:	Detects unauthorized RDP access, reducing noise by excluding legitimate remote access sources.
Conclusion
These 35 Splunk use cases demonstrate how powerful queries and customized alerts can enhance security monitoring, threat detection, and incident response. Real-Time Visibility: Splunk provides continuous, real-time monitoring across systems and networks. Threat Detection: Custom rules enable precise detection of suspicious behaviors and attack patterns. False Positive Reduction: Fine-tuning alerts helps minimize noise, allowing teams to focus on true threats. Incident Investigation: Correlation rules streamline investigations by linking related security events. Automation & Response: Integrations with other security tools support automated responses to critical events. Comprehensive Coverage: By addressing multiple sources, Splunk ensures thorough monitoring across the security landscape.