Okta Multiple Failed Requests to Access Applications

Status: experimental
Group by: "actor.alternateId", "authenticationContext.externalSessionId", "client.ipAddress", targets
Author: John Murphy, Okta, Michael Haag, Splunk
Source: github.com/splunk/security_content

The following analytic detects multiple failed attempts to access applications in Okta, potentially indicating the reuse of a stolen web session cookie. It leverages Okta logs to evaluate policy and SSO events, aggregating data by user, session, and IP. The detection triggers when more than half of the app sign-on attempts are unsuccessful across multiple applications. This activity is significant as it may indicate an attempt to bypass authentication mechanisms. If confirmed malicious, it could lead to unauthorized access to sensitive applications and data, posing a significant security risk.

MITRE ATT&CK coverage

Tactic	Techniques
Discovery	`T1538` Cloud Service Dashboard
Lateral Movement	`T1550.004` Use Alternate Authentication Material: Web Session Cookie

Rules detecting the same action

Other rules on this platform that filter on the same API call or operation.

First Occurrence of Okta User Session Started via Proxy (Elastic)
High-Risk Admin Activity (Kusto)
Okta AiTM Session Cookie Replay (Elastic)
Okta Multiple Failed Requests To Access Applications (YARA-L)
Okta New Admin Console Behaviours (Sigma)
Okta Potentially Stolen Session (Panther)
Okta Suspicious Use Of A Session Cookie (YARA-L)
Okta Suspicious Use of a Session Cookie (Splunk)

Rule body splunk

name: Okta Multiple Failed Requests to Access Applications
id: 1c21fed1-7000-4a2e-9105-5aaafa437247
version: 6
creation_date: '2023-04-11'
modification_date: '2026-05-13'
author: John Murphy, Okta, Michael Haag, Splunk
status: experimental
type: Hunting
description: The following analytic detects multiple failed attempts to access applications in Okta, potentially indicating the reuse of a stolen web session cookie. It leverages Okta logs to evaluate policy and SSO events, aggregating data by user, session, and IP. The detection triggers when more than half of the app sign-on attempts are unsuccessful across multiple applications. This activity is significant as it may indicate an attempt to bypass authentication mechanisms. If confirmed malicious, it could lead to unauthorized access to sensitive applications and data, posing a significant security risk.
data_source:
    - Okta
search: "`okta` target{}.type=AppInstance (eventType=policy.evaluate_sign_on outcome.result=CHALLENGE) OR (eventType=user.authentication.sso outcome.result=SUCCESS) | eval targets=mvzip('target{}.type', 'target{}.displayName', \": \") | eval targets=mvfilter(targets LIKE \"AppInstance%\") | stats count min(_time) as _time values(outcome.result) as outcome.result dc(eval(if(eventType=\"policy.evaluate_sign_on\",targets,NULL))) as total_challenges sum(eval(if(eventType=\"user.authentication.sso\",1,0))) as total_successes by authenticationContext.externalSessionId targets actor.alternateId client.ipAddress | search total_challenges > 0 | stats min(_time) as _time values(*) as * sum(total_challenges) as total_challenges sum(total_successes) as total_successes values(eval(if(\"outcome.result\"=\"SUCCESS\",targets,NULL))) as success_apps values(eval(if(\":outcome.result\"!=\"SUCCESS\",targets,NULL))) as no_success_apps by authenticationContext.externalSessionId actor.alternateId client.ipAddress | fillnull | eval ratio=round(total_successes/total_challenges,2), severity=\"HIGH\", mitre_technique_id=\"T1538\", description=\"actor.alternateId\". \" from \" . \"client.ipAddress\" . \" seen opening \" . total_challenges . \" chiclets/apps with \" . total_successes . \" challenges successfully passed\" | fields - count, targets | search ratio < 0.5 total_challenges > 2 | `okta_multiple_failed_requests_to_access_applications_filter`"
how_to_implement: This analytic is specific to Okta and requires Okta:im2 logs to be ingested.
known_false_positives: False positives may be present based on organization size and configuration of Okta.
references:
    - https://attack.mitre.org/techniques/T1538
    - https://attack.mitre.org/techniques/T1550/004
analytic_story:
    - Okta Account Takeover
asset_type: Okta Tenant
mitre_attack_id:
    - T1550.004
    - T1538
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: application
security_domain: access

Stages and Predicates

Stage 1: `search`

`okta` target{}.type=AppInstance (eventType=policy.evaluate_sign_on outcome.result=CHALLENGE) OR (eventType=user.authentication.sso outcome.result=SUCCESS)

Stage 2: `eval`

| eval targets=mvzip('target{}.type', 'target{}.displayName', ": ")

Stage 3: `eval`

| eval targets=mvfilter(targets LIKE "AppInstance%")

Stage 4: `stats`

| stats count min(_time) as _time values(outcome.result) as outcome.result dc(eval(if(eventType="policy.evaluate_sign_on",targets,NULL))) as total_challenges sum(eval(if(eventType="user.authentication.sso",1,0))) as total_successes by authenticationContext.externalSessionId targets actor.alternateId client.ipAddress

Stage 5: `search`

| search total_challenges > 0

Stage 6: `stats`

| stats min(_time) as _time values(*) as * sum(total_challenges) as total_challenges sum(total_successes) as total_successes values(eval(if("outcome.result"="SUCCESS",targets,NULL))) as success_apps values(eval(if(":outcome.result"!="SUCCESS",targets,NULL))) as no_success_apps by authenticationContext.externalSessionId actor.alternateId client.ipAddress

Stage 7: `fillnull`

| fillnull

Stage 8: `eval`

| eval ratio=round(total_successes/total_challenges,2), severity="HIGH", mitre_technique_id="T1538", description="actor.alternateId". " from " . "client.ipAddress" . " seen opening " . total_challenges . " chiclets/apps with " . total_successes . " challenges successfully passed"

Stage 9: `fields`

| fields - count, targets

Stage 10: `search`

| search ratio < 0.5 total_challenges > 2

Stage 11: `search`

| `okta_multiple_failed_requests_to_access_applications_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
`eventType`	eq	`policy.evaluate_sign_on` `user.authentication.sso`
`outcome.result`	eq	`CHALLENGE` `SUCCESS`
`ratio`	lt	`0.5`
`sourcetype`	eq	`OktaIM2:log`
`target{}.type`	eq	`AppInstance`
`total_challenges`	gt	`0` `2`

`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)

Okta Multiple Failed Requests to Access Applications

MITRE ATT&CK coverage

Rules detecting the same action

Rule body splunk

Stages and Predicates

Stage 1: `search`

Stage 2: `eval`

Stage 3: `eval`

Stage 4: `stats`

Stage 5: `search`

Stage 6: `stats`

Stage 7: `fillnull`

Stage 8: `eval`

Stage 9: `fields`

Stage 10: `search`

Stage 11: `search`

Indicators

Keyboard shortcuts

Search operators

Okta Multiple Failed Requests to Access Applications

MITRE ATT&CK coverage

Rules detecting the same action

Rule body splunk

Stages and Predicates

Stage 1: search

Stage 2: eval

Stage 3: eval

Stage 4: stats

Stage 5: search

Stage 6: stats

Stage 7: fillnull

Stage 8: eval

Stage 9: fields

Stage 10: search

Stage 11: search

Indicators

Stage 1: `search`

Stage 2: `eval`

Stage 3: `eval`

Stage 4: `stats`

Stage 5: `search`

Stage 6: `stats`

Stage 7: `fillnull`

Stage 8: `eval`

Stage 9: `fields`

Stage 10: `search`

Stage 11: `search`