Detection: Fortinet Appliance Auth bypass

Description

The following analytic detects attempts to exploit CVE-2022-40684, a Fortinet appliance authentication bypass vulnerability. It identifies REST API requests to the /api/v2/ endpoint using various HTTP methods (GET, POST, PUT, DELETE) that may indicate unauthorized modifications, such as adding SSH keys or creating new users. This detection leverages the Web datamodel to monitor specific URL patterns and HTTP methods. This activity is significant as it can lead to unauthorized access and control over the appliance. If confirmed malicious, attackers could gain persistent access, reroute network traffic, or capture sensitive information.

1
2| tstats count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where Web.url IN ("*/api/v2/cmdb/system/admin*")  Web.http_method IN ("GET", "PUT") by Web.http_user_agent, Web.http_method, Web.url, Web.url_length, Web.src, Web.dest, sourcetype 
3| `drop_dm_object_name("Web")` 
4| `security_content_ctime(firstTime)` 
5| `security_content_ctime(lastTime)` 
6| `fortinet_appliance_auth_bypass_filter`

Data Source

Name Platform Sourcetype Source
Palo Alto Network Threat Network icon Network 'pan:threat' 'pan:threat'

Macros Used

Name Value
security_content_ctime convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)
fortinet_appliance_auth_bypass_filter search *
fortinet_appliance_auth_bypass_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1190 Exploit Public-Facing Application Initial Access
T1133 External Remote Services Initial Access
KillChainPhase.DELIVERY
KillChainPhase.INSTALLATION
NistCategory.DE_CM
Cis18Value.CIS_13
APT28
APT29
APT39
APT41
APT5
Agrius
Axiom
BackdoorDiplomacy
BlackTech
Blue Mockingbird
Cinnamon Tempest
Dragonfly
Earth Lusca
Ember Bear
FIN13
FIN7
Fox Kitten
GALLIUM
GOLD SOUTHFIELD
HAFNIUM
INC Ransom
Ke3chang
Kimsuky
Magic Hound
Moses Staff
MuddyWater
Play
Rocke
Sandworm Team
Threat Group-3390
ToddyCat
Volatile Cedar
Volt Typhoon
Winter Vivern
menuPass
APT18
APT28
APT29
APT41
Akira
Chimera
Dragonfly
Ember Bear
FIN13
FIN5
GALLIUM
GOLD SOUTHFIELD
Ke3chang
Kimsuky
LAPSUS$
Leviathan
OilRig
Play
Sandworm Team
Scattered Spider
TeamTNT
Threat Group-3390
Volt Typhoon
Wizard Spider

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Notable Yes
Rule Title %name%
Rule Description %description%
Notable Event Fields user, dest
Creates Risk Event True
This configuration file applies to all detections of type TTP. These detections will use Risk Based Alerting and generate Notable Events.

Implementation

This detection requires the Web datamodel to be populated from a supported Technology Add-On like Splunk for Apache. Splunk for Nginx, or Splunk for Palo Alto.

Known False Positives

GET requests will be noisy and need to be filtered out or removed from the query based on volume. Restrict analytic to known publically facing Fortigates, or run analytic as a Hunt until properly tuned. It is also possible the user agent may be filtered on Report Runner or Node.js only for the exploit, however, it is unknown at this if other user agents may be used.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Potential CVE-2022-40684 against a Fortinet appliance may be occurring against $dest$. 81 90 90
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation Passing N/A N/A N/A
Unit Passing Dataset pan:threat pan:threat
Integration ✅ Passing Dataset pan:threat pan:threat

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: GitHub | Version: 3