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99 lines
3.9 KiB
Text
99 lines
3.9 KiB
Text
[[esql-examples]]
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== {esql} examples
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++++
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<titleabbrev>Examples</titleabbrev>
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++++
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[discrete]
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=== Aggregating and enriching windows event logs
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[source,esql]
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----
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FROM logs-*
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| WHERE event.code IS NOT NULL
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| STATS event_code_count = COUNT(event.code) BY event.code,host.name
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| ENRICH win_events ON event.code WITH event_description
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| WHERE event_description IS NOT NULL and host.name IS NOT NULL
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| RENAME event_description AS event.description
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| SORT event_code_count DESC
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| KEEP event_code_count,event.code,host.name,event.description
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----
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* It starts by querying logs from indices that match the pattern "logs-*".
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* Filters events where the "event.code" field is not null.
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* Aggregates the count of events by "event.code" and "host.name."
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* Enriches the events with additional information using the "EVENT_DESCRIPTION" field.
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* Filters out events where "EVENT_DESCRIPTION" or "host.name" is null.
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* Renames "EVENT_DESCRIPTION" as "event.description."
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* Sorts the result by "event_code_count" in descending order.
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* Keeps only selected fields: "event_code_count," "event.code," "host.name," and "event.description."
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[discrete]
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=== Summing outbound traffic from a process `curl.exe`
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[source,esql]
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----
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FROM logs-endpoint
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| WHERE process.name == "curl.exe"
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| STATS bytes = SUM(destination.bytes) BY destination.address
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| EVAL kb = bytes/1024
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| SORT kb DESC
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| LIMIT 10
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| KEEP kb,destination.address
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----
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* Queries logs from the "logs-endpoint" source.
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* Filters events where the "process.name" field is "curl.exe."
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* Calculates the sum of bytes sent to destination addresses and converts it to kilobytes (KB).
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* Sorts the results by "kb" (kilobytes) in descending order.
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* Limits the output to the top 10 results.
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* Keeps only the "kb" and "destination.address" fields.
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[discrete]
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=== Manipulating DNS logs to find a high number of unique dns queries per registered domain
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[source,esql]
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----
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FROM logs-*
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| GROK dns.question.name "%{DATA}\\.%{GREEDYDATA:dns.question.registered_domain:string}"
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| STATS unique_queries = COUNT_DISTINCT(dns.question.name) BY dns.question.registered_domain, process.name
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| WHERE unique_queries > 10
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| SORT unique_queries DESC
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| RENAME unique_queries AS `Unique Queries`, dns.question.registered_domain AS `Registered Domain`, process.name AS `Process`
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----
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* Queries logs from indices matching "logs-*."
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* Uses the "grok" pattern to extract the registered domain from the "dns.question.name" field.
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* Calculates the count of unique DNS queries per registered domain and process name.
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* Filters results where "unique_queries" are greater than 10.
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* Sorts the results by "unique_queries" in descending order.
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* Renames fields for clarity: "unique_queries" to "Unique Queries," "dns.question.registered_domain" to "Registered Domain," and "process.name" to "Process."
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[discrete]
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=== Identifying high-numbers of outbound user connections
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[source,esql]
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----
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FROM logs-*
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| WHERE NOT CIDR_MATCH(destination.ip, "10.0.0.0/8", "172.16.0.0/12", "192.168.0.0/16")
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| STATS destcount = COUNT(destination.ip) BY user.name, host.name
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| ENRICH ldap_lookup_new ON user.name
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| WHERE group.name IS NOT NULL
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| EVAL follow_up = CASE(destcount >= 100, "true","false")
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| SORT destcount DESC
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| KEEP destcount, host.name, user.name, group.name, follow_up
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----
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* Queries logs from indices matching "logs-*."
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* Filters out events where the destination IP address falls within private IP address ranges (e.g., 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16).
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* Calculates the count of unique destination IPs by "user.name" and "host.name."
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* Enriches the "user.name" field with LDAP group information.
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* Filters out results where "group.name" is not null.
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* Uses a "CASE" statement to create a "follow_up" field, setting it to "true" when "destcount" is greater than or equal to 100 and "false" otherwise.
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* Sorts the results by "destcount" in descending order.
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* Keeps selected fields: "destcount," "host.name," "user.name," "group.name," and "follow_up."
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