Internal Vulnerability Scan

Status: experimental
Severity: medium
Group by: IDS_Attacks.dest, IDS_Attacks.dest_port, IDS_Attacks.severity, IDS_Attacks.signature, IDS_Attacks.src, IDS_Attacks.transport, _time, gtime, severity, signature, src
Author: Dean Luxton
Source: github.com/splunk/security_content

This analytic detects internal hosts triggering multiple IDS signatures, which may include either more than 25 signatures against a single host or a single signature across over 25 destination IP addresses. Such patterns can indicate active vulnerability scanning activities within the network. By monitoring IDS logs, this detection helps identify and respond to potential vulnerability scanning attempts, enhancing the network's security posture and preventing potential exploits.

MITRE ATT&CK coverage

Tactic	Techniques
Reconnaissance	`T1595.002` Active Scanning: Vulnerability Scanning
Discovery	`T1046` Network Service Discovery

Rule body splunk

name: Internal Vulnerability Scan
id: 46f946ed-1c78-4e96-9906-c7a4be15e39b
version: 8
creation_date: '2024-07-01'
modification_date: '2026-05-13'
author: Dean Luxton
status: experimental
type: TTP
description: This analytic detects internal hosts triggering multiple IDS signatures, which may include either more than 25 signatures against a single host or a single signature across over 25 destination IP addresses. Such patterns can indicate active vulnerability scanning activities within the network. By monitoring IDS logs, this detection helps identify and respond to potential vulnerability scanning attempts, enhancing the network's security posture and preventing potential exploits.
data_source: []
search: |-
    | tstats `security_content_summariesonly` values(IDS_Attacks.action) as action values(IDS_Attacks.src_category) as src_category values(IDS_Attacks.dest_category) as dest_category count FROM datamodel=Intrusion_Detection.IDS_Attacks
      WHERE IDS_Attacks.src IN (10.0.0.0/8,192.168.0.0/16,172.16.0.0/12) IDS_Attacks.severity IN (critical, high, medium)
      BY IDS_Attacks.src IDS_Attacks.severity IDS_Attacks.signature
         IDS_Attacks.dest IDS_Attacks.dest_port IDS_Attacks.transport
         span=1s _time
    | `drop_dm_object_name("IDS_Attacks")`
    | eval gtime=_time
    | bin span=1h gtime
    | eventstats count as sevCount
      BY severity src
    | eventstats count as sigCount
      BY signature src
    | eval severity=severity +"("+sevCount+")"
    | eval signature=signature +"("+sigCount+")"
    | eval dest_port=transport + "/" + dest_port
    | stats min(_time) as _time values(action) as action dc(dest) as destCount dc(signature) as sigCount values(signature) values(src_category) as src_category values(dest_category) as dest_category values(severity) as severity values(dest_port) as dest_ports
      BY src gtime
    | fields - gtime
    | where destCount>25 OR sigCount>25
    | `internal_vulnerability_scan_filter`
how_to_implement: For this detection to function effectively, it is essential to ingest IDS/IPS logs that are mapped to the Common Information Model (CIM). These logs provide the necessary security-related telemetry and contextual information needed to accurately identify and analyze potential threats.
known_false_positives: Internal vulnerability scanners will trigger this detection.
references: []
finding:
    title: Large volume of IDS signatures triggered by $src$
    entity:
        field: src
        type: system
        score: 50
analytic_story:
    - Network Discovery
    - Scattered Lapsus$ Hunters
asset_type: Endpoint
mitre_attack_id:
    - T1595.002
    - T1046
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: network
security_domain: network

Stages and Predicates

Stage 1: `tstats`

| tstats `security_content_summariesonly` values(IDS_Attacks.action) as action values(IDS_Attacks.src_category) as src_category values(IDS_Attacks.dest_category) as dest_category count FROM datamodel=Intrusion_Detection.IDS_Attacks
  WHERE IDS_Attacks.src IN (10.0.0.0/8,192.168.0.0/16,172.16.0.0/12) IDS_Attacks.severity IN (critical, high, medium)
  BY IDS_Attacks.src IDS_Attacks.severity IDS_Attacks.signature
     IDS_Attacks.dest IDS_Attacks.dest_port IDS_Attacks.transport
     span=1s _time

Stage 2: `search`

| `drop_dm_object_name("IDS_Attacks")`

Stage 3: `eval`

| eval gtime=_time

Stage 4: `bucket`

| bin span=1h gtime

Stage 5: `eventstats`

| eventstats count as sevCount
  BY severity src

Stage 6: `eventstats`

| eventstats count as sigCount
  BY signature src

Stage 7: `eval`

| eval severity=severity +"("+sevCount+")"

Stage 8: `eval`

| eval signature=signature +"("+sigCount+")"

Stage 9: `eval`

| eval dest_port=transport + "/" + dest_port

Stage 10: `stats`

| stats min(_time) as _time values(action) as action dc(dest) as destCount dc(signature) as sigCount values(signature) values(src_category) as src_category values(dest_category) as dest_category values(severity) as severity values(dest_port) as dest_ports
  BY src gtime

Stage 11: `fields`

| fields - gtime

Stage 12: `where`

| where destCount>25 OR sigCount>25

Stage 13: `search`

| `internal_vulnerability_scan_filter`

Indicators

Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.

Field	Kind	Values
`IDS_Attacks.severity`	in	`"critical"` `"high"` `"medium"`
`IDS_Attacks.src`	in	`"10.0.0.0/8"` `"172.16.0.0/12"` `"192.168.0.0/16"`
`destCount`	gt	`25`
`sigCount`	gt	`25`

`j` / `k`	Scroll down / up
`d` / `u`	Half-page down / up
`gg` / `G`	Top / bottom
`h` / `l`	History back / forward
`f`	Follow link (`Shift` = new tab)
`/`	Focus search
`?`	Toggle this help
`↑` / `↓`	Navigate search results
`Enter`	Open highlighted result
`Esc`	Close results / dialog

`type:`	`events` / `rules` / `providers`
`vendor:`	`sigma` / `elastic` / `splunk` / `kusto` / `chronicle` (vendor name alone also works: `sigma:`, `kql:`, `secops:`…)
`tactic:`	TA-id, slug, or name: `credential_access`, `TA0006`
`technique:`	technique or sub-technique ID: `T1003`, `T1003.001` (alias `tech:`)
`severity:`	`critical` / `high` / `medium` / `low` / `informational` (alias `sev:`)
`risk_score`	Numeric comparison on the Elastic risk score (0 to 100): `risk_score>50`, `risk_score<=20`, `risk_score=99` (alias `risk`; Elastic rules only)
`stages:`	Rules with exactly N pipeline stages
`correlation:`	`single_event` / `sequence` / `alternatives` / `alternatives_cross_log` / `all_required` / `correlated`
`with:`	Co-occurrence event-id; stacks (`with:4624 with:4769`) to require all, while a comma list in one occurrence (`with:4624,4769`) is an either-or group. Implies multi-event
`like:`	Structural neighbors of a rule slug (equivalents + subsumption stricter / broader): `like:comsvcs_lsass_memory_dump-splunk-sysmon`
`groupby:`	Entity-grouping substring match against `group_by_keys`: `groupby:user`, `groupby:host`
`uses:`	Rules whose predicate tree touches the field (any kind, any value): `uses:CommandLine`
`excludes:`	Rules with top-level `not()` clauses on the field (FP whitelists): `excludes:ParentImage`
`field:` / `value:`	Predicate search; narrows rule cards to those with a matching leaf and drives the indicator tier. Unquoted = substring, wildcards allowed (`value:mimikatz`)
`indicator:`	Shorthand for `field:F value:V`: `indicator:Image=*\powershell.exe`
`kind:`	Filter by predicate kind. Narrows rule cards to those carrying a matching predicate leaf (`vendor:elastic kind:cidr_match`) and drives the indicator tier: `contains` / `starts_with` / `ends_with` / `regex` / `cidr` / `eq` / `in` … (operator aliases `op:`/`match:`)
`has:` / `no:`	`sample`, `field`, `notes`, `refs`, `trace`, `thirdparty`, `rule`, `pattern`, `timewindow`, `threshold`, `newterms`, `sigma`/`elastic`/`splunk`/`kusto`/`chronicle`
`-op:val`	Exclude matches; works on most operators but not `type:`/`like:`/`has:`/`no:` (use `no:<flag>` to exclude a rule flag): `tactic:execution -vendor:splunk`. Standalone `-kind:`/`-field:`/`-value:` drop every rule carrying a matching predicate leaf (`type:rules -kind:is_null`)
`field:"…"` / `value:"…"`	Quoted value = anchored exact match (also allows spaces): `value:"net user"`
`a,b`	Comma = OR inside one operator (`vendor:sigma,elastic`, `severity:high,critical`); repeating a facet merges the same way. `field:`/`value:` never split (literal commas)
`vendors:` / `stage:`	Singular and plural spellings fold to the canonical operator and value: `tactics:` = `tactic:`, `type:event` = `type:events`, `correlation:sequences` = `correlation:sequence`, `has:thresholds` = `has:threshold`
`"quoted phrase"`	Exact-match a multi-word phrase (free text)

Internal Vulnerability Scan

MITRE ATT&CK coverage

Rule body splunk

Stages and Predicates

Stage 1: `tstats`

Stage 2: `search`

Stage 3: `eval`

Stage 4: `bucket`

Stage 5: `eventstats`

Stage 6: `eventstats`

Stage 7: `eval`

Stage 8: `eval`

Stage 9: `eval`

Stage 10: `stats`

Stage 11: `fields`

Stage 12: `where`

Stage 13: `search`

Indicators

Keyboard shortcuts

Search operators

Internal Vulnerability Scan

MITRE ATT&CK coverage

Rule body splunk

Stages and Predicates

Stage 1: tstats

Stage 2: search

Stage 3: eval

Stage 4: bucket

Stage 5: eventstats

Stage 6: eventstats

Stage 7: eval

Stage 8: eval

Stage 9: eval

Stage 10: stats

Stage 11: fields

Stage 12: where

Stage 13: search

Indicators

Stage 1: `tstats`

Stage 2: `search`

Stage 3: `eval`

Stage 4: `bucket`

Stage 5: `eventstats`

Stage 6: `eventstats`

Stage 7: `eval`

Stage 8: `eval`

Stage 9: `eval`

Stage 10: `stats`

Stage 11: `fields`

Stage 12: `where`

Stage 13: `search`