PingID Multiple Failed MFA Requests For User
Description
The following analytic identifies multiple failed multi-factor authentication (MFA) requests for a single user within a PingID environment. It triggers when 10 or more MFA prompts fail within 10 minutes, using JSON logs from PingID. This activity is significant as it may indicate an adversary attempting to bypass MFA by bombarding the user with repeated authentication requests. If confirmed malicious, this could lead to unauthorized access, as the user might eventually accept the fraudulent request, compromising the security of the account and potentially the entire network.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2024-05-29
- Author: Steven Dick
- ID: c1bc706a-0025-4814-ad30-288f38865036
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
- Installation
- Delivery
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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`pingid` "result.status" IN ("FAILURE,authFail","UNSUCCESSFUL_ATTEMPT")
| eval time = _time, src = coalesce('resources{}.ipaddress','resources{}.devicemodel'), user = upper('actors{}.name'), object = 'resources{}.devicemodel', reason = 'result.message'
| bucket span=10m _time
| stats dc(_raw) AS mfa_prompts min(time) as firstTime, max(time) as lastTime values(src) as src by user, reason, _time
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| where mfa_prompts >= 10
| `pingid_multiple_failed_mfa_requests_for_user_filter`
Macros
The SPL above uses the following Macros:
pingid_multiple_failed_mfa_requests_for_user_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- resources{}.ipaddress
- actors{}.name
- result.message
- resources{}.devicemodel
- result.status
How To Implement
Target environment must ingest JSON logging from a PingID(PingOne) enterprise environment, either via Webhook or Push Subscription.
Known False Positives
False positives may be generated by normal provisioning workflows for user device registration.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
50.0 | 100 | 50 | Multiple Failed MFA requests $mfa_prompts$ for user $user$ between $firstTime$ and $lastTime$. |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
- https://therecord.media/russian-hackers-bypass-2fa-by-annoying-victims-with-repeated-push-notifications/
- https://attack.mitre.org/techniques/T1621/
- https://attack.mitre.org/techniques/T1110/
- https://attack.mitre.org/techniques/T1078/004/
- https://docs.pingidentity.com/r/en-us/pingoneforenterprise/p14e_subscriptions?tocId=3xhnxjX3VzKNs3SXigWnQA
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 2