O365 Multiple AppIDs and UserAgents Authentication Spike
Description
This analytic is crafted to identify unusual and potentially malicious authentication activity within an O365 environment. It triggers when a single user account is involved in more than 8 authentication attempts, using 3 or more unique application IDs and more than 5 unique user agents within a short timeframe. This pattern is atypical for regular user behavior and may indicate an adversary's attempt to probe the environment, testing for multi-factor authentication requirements across different applications and platforms. The detection is based on analysis of O365 audit logs, specifically focusing on authentication events. It employs statistical thresholds to highlight instances where the volume of authentication attempts and the diversity of application IDs and user agents associated with a single user account exceed normal parameters. Identifying this behavior is crucial as it provides an early indication of potential account compromise. Adversaries, once in possession of user credentials, often conduct reconnaissance to understand the security controls in place, including multi-factor authentication configurations. Tools like Invoke-MFASweep are commonly used for this purpose, automating the process of testing different user agents and application IDs to bypass MFA. By detecting these initial probing attempts, security teams can swiftly respond, potentially stopping an attack in its early stages and preventing further unauthorized access. This proactive stance is vital for maintaining the integrity of the organization's security posture. If validated as a true positive, this detection points to a compromised account, signaling that an attacker is actively attempting to navigate security controls to maintain access and potentially escalate privileges. This could lead to further exploitation, lateral movement within the network, and eventual data exfiltration. Recognizing and responding to this early stage of an attack is vital for preventing substantial harm and safeguarding sensitive organizational data and systems.
- Type: Anomaly
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2023-10-24
- Author: Mauricio Velazco, Splunk
- ID: 66adc486-224d-45c1-8e4d-9e7eeaba988f
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
- Installation
- Delivery
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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`o365_management_activity` Workload=AzureActiveDirectory (Operation=UserLoggedIn OR Operation=UserLoginFailed)
| bucket span=5m _time
| stats dc(_raw) as failed_attempts dc(ApplicationId) as unique_app_ids dc(UserAgent) as unique_user_agents values(ApplicationId) values(OS) by _time user src_ip
| where failed_attempts > 5 and unique_user_agents > 5 and unique_app_ids > 2
| `o365_multiple_appids_and_useragents_authentication_spike_filter`
Macros
The SPL above uses the following Macros:
o365_multiple_appids_and_useragents_authentication_spike_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
- Workload
- Operation
- ApplicationId
- UserAgent
- OS
How To Implement
You must install the Splunk Microsoft Office 365 Add-on and ingest Office 365 management activity events.
Known False Positives
Rapid authentication from the same user using more than 5 different user agents and 3 application IDs is highly unlikely under normal circumstances. However, there are potential scenarios that could lead to false positives.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
48.0 | 60 | 80 | $user$ authenticated in a short period of time with more than 5 different user agents across 3 or more unique application ids. |
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://attack.mitre.org/techniques/T1078/
- https://www.blackhillsinfosec.com/exploiting-mfa-inconsistencies-on-microsoft-services/
- https://github.com/dafthack/MFASweep
- https://www.youtube.com/watch?v=SK1zgqaAZ2E
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: 1