Detection: Log4Shell JNDI Payload Injection Attempt

Updated Date: 2024-05-25 ID: c184f12e-5c90-11ec-bf1f-497c9a704a72 Author: Jose Hernandez Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies attempts to inject Log4Shell JNDI payloads via web calls. It leverages the Web datamodel and uses regex to detect patterns like ${jndi:ldap:// in raw web event data, including HTTP headers. This activity is significant because it targets vulnerabilities in Java web applications using Log4j, such as Apache Struts and Solr. If confirmed malicious, this could allow attackers to execute arbitrary code, potentially leading to full system compromise. Immediate investigation is required to determine if the attempt was successful and to mitigate any potential exploitation.

 1
 2| from datamodel Web.Web 
 3| regex _raw="[jJnNdDiI]{4}(\:
 4|\%3A
 5|\/
 6|\%2F)\w+(\:\/\/
 7|\%3A\%2F\%2F)(\$\{.*?\}(\.)?)?" 
 8| fillnull 
 9| stats count by action, category, dest, dest_port, http_content_type, http_method, http_referrer, http_user_agent, site, src, url, url_domain, user 
10| `log4shell_jndi_payload_injection_attempt_filter`

Data Source

Name Platform Sourcetype Source Supported App
Nginx Access N/A 'nginx:plus:kv' '/var/log/nginx/access.log' N/A

Macros Used

Name Value

| log4shell_jndi_payload_injection_attempt_filter | search * |

log4shell_jndi_payload_injection_attempt_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_AE
Cis18Value.CIS_10
APT28
APT29
APT39
APT41
APT5
Axiom
BackdoorDiplomacy
BlackTech
Blue Mockingbird
Cinnamon Tempest
Dragonfly
Earth Lusca
FIN13
FIN7
Fox Kitten
GALLIUM
GOLD SOUTHFIELD
HAFNIUM
Ke3chang
Kimsuky
Magic Hound
Moses Staff
MuddyWater
Rocke
Sandworm Team
Threat Group-3390
ToddyCat
Volatile Cedar
Volt Typhoon
menuPass
APT18
APT28
APT29
APT41
Akira
Chimera
Dragonfly
FIN13
FIN5
GALLIUM
GOLD SOUTHFIELD
Ke3chang
Kimsuky
LAPSUS$
Leviathan
OilRig
Sandworm Team
Scattered Spider
TeamTNT
Threat Group-3390
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 Risk Event True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

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

Known False Positives

If there is a vulnerablility scannner looking for log4shells this will trigger, otherwise likely to have low false positives.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
CVE-2021-44228 Log4Shell triggered for host $dest$ 15 50 30
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 nginx nginx:plus:kv
Integration ✅ Passing Dataset nginx nginx:plus:kv

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: 2