Standard Fields

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Standard Fields
Panther's log analysis applies normalization fields (IPs, domains, etc) to all log records. These fields provide standard names for attributes across all data sources enabling fast and easy data correlation.
For example, each data source has a time that an event occurred, but each data source will likely not name the attribute the same, nor is it guaranteed that the associated time has a timezone consistent with other data sources.
The Panther attribute p_event_time is mapped to each data source's corresponding event time and normalized to UTC. This way you can query over multiple data sources joining and ordering by p_event_time to properly align and correlate the data despite the disparate schemas of each data source.
All appended standard fields begin with p_
Required Fields
The fields below are appended to all log records:
Field Name
Type
Description
p_log_type
string
The type of log.
p_row_id
string
Unique id (UUID) for the row.
p_event_time
timestamp
The associated event time for the log type is copied here and normalized to UTC.
p_parse_time
timestamp
The current time when the event was parsed normalized to UTC.
p_source_id
string
The Panther generated internal id for the source integration.
p_source_label
string
The user supplied label for the source integration (may change if edited).
If an event does not have a timestamp, then p_event_time will be set to p_parse_time, which is the time the event was parsed.
The p_source_id and p_source_label fields are very useful for knowing where the data originated. For example, you might have multiple CloudTrail sources registered with Panther, each with a unique name (e.g., "Dev Accounts", "Producttion Accounts", "HR Accounts", etc.). These fields allow you to easily separate data based on the source which can be very useful to use in Panther rules as well as business intelligence (BI) reporting.
In addition, the fields below are appended to log records of all tables in the panther_rule_matches database:
Field Name
Type
Description
p_alert_id
string
Id of alert related to row.
p_alert_creation_time
timestamp
Time of alert creation related to row.
p_alert_context
object
A JSON object returned from the rule's alert_context() function.
p_alert_severity
string
The severity level of the rule at the time of the alert. This could be different from the default severity as it can be dynamically set.
p_alert_update_time
timestamp
Time of last alert update related to row.
p_rule_id
string
The id of the rule that generated the alert.
p_rule_error
string
The error message if there was an error running the rule.
p_rule_reports
map[string]array[string]
List of user defined rule reporting tags related to row.
p_rule_severity
string
The default severity of the rule.
p_rule_tags
array[string]
List of user defined rule tags related to row.
Indicator Fields
A common security question is often of the form of: “was some-indicator ever observed in our logs?”
Notice that the relationship of the indicator is not a concern initially, simply the presence or absence of activity is of interest.
To allow this question to be answered over all data sources, the any fields below are appended to rows of data as appropriate.
The all_logs view is provided over all data sources to make queries easy for users to find activity for an indicator in a single query.
Each indicator name implies a data extraction into one or more p_any fields.
Please see the Indicator Fields and their corresponding Indicator Strings here: Log Schema Reference: Indicators.
Enrichment Fields
The Panther rules engine will take the looked up matches from Lookup Tables (BETA) and append that data to the event using the key p_enrichment in the following JSON structure:
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{ 
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 'p_enrichment': {
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 <name of lookup table>: { 
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 <key in log that matched>: <matching row looked up>,
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 ...
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 <key in log that matched>: <matching row looked up>,
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 } }
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} 
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Field Name
Type
Description
p_enrichment
array[object]
List of lookup results where matching rows were found.
The "all_logs" View
Panther manages a view over all data sources with standard fields.
This allows you to ask questions such as "was there any activity from some-bad-ip and if so where?".
The query below will show how many records (by log type) are associated with IP address 95.123.145.92:
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SELECT
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 p_log_type, count(1) AS row_count
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FROM panther_views.all_logs
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WHERE year=2020 AND month=1 AND day=31 AND contains(p_any_ip_addresses, '95.123.145.92')
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GROUP BY p_log_type
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From these results, you can pivot to the specific logs where activity is indicated.
Standard Fields in Rules
The Panther standard fields can be used in rules. For example, this rule triggers when any GuardDuty alert is on a resource tagged as 'critical':
Example Panther Rule
Data Analytics
Indicator Search
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Standard Fields in Rules