Detection rules › Splunk

Log4Shell JNDI Payload Injection Attempt

Status
production
Severity
low
Group by
action, category, dest, destination_port, http_content_type, http_method, http_referrer, http_user_agent, site, src, url, url_domain, user
Author
Jose Hernandez
Source
github.com/splunk/security_content

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.

MITRE ATT&CK coverage

Rule body splunk

name: Log4Shell JNDI Payload Injection Attempt
id: c184f12e-5c90-11ec-bf1f-497c9a704a72
version: 9
creation_date: '2021-12-13'
modification_date: '2026-05-13'
author: Jose Hernandez
status: production
type: Anomaly
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 `${jndi:ldap://` in raw web event data, including HTTP headers. This activity is significant because it targets vulnerabilities in Java web applications using Log4j, such as Apache Struts and Solr. If confirmed malicious, this could allow attackers to execute arbitrary code, potentially leading to full system compromise. Immediate investigation is required to determine if the attempt was successful and to mitigate any potential exploitation.
data_source:
    - Nginx Access
search: |-
    | from datamodel Web.Web
    | regex _raw="[jJnNdDiI]{4}(\:|\%3A|\/|\%2F)\w+(\:\/\/|\%3A\%2F\%2F)(\$\{.*?\}(\.)?)?"
    | fillnull
    | stats count by action, category, dest, dest_port, http_content_type, http_method, http_referrer, http_user_agent, site, src, url, url_domain, user
    | `log4shell_jndi_payload_injection_attempt_filter`
how_to_implement: This detection requires the Web datamodel to be populated from a supported Technology Add-On like Splunk for Apache or Splunk for Nginx.
known_false_positives: If there is a vulnerablility scannner looking for log4shells this will trigger, otherwise likely to have low false positives.
references:
    - https://www.lunasec.io/docs/blog/log4j-zero-day/
drilldown_searches:
    - name: View the detection results for - "$user$" and "$dest$"
      search: '%original_detection_search% | search  user = "$user$" dest = "$dest$"'
      earliest_offset: $info_min_time$
      latest_offset: $info_max_time$
    - name: View risk events for the last 7 days for - "$user$" and "$dest$"
      search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$", "$dest$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
      earliest_offset: 7d
      latest_offset: "0"
intermediate_findings:
    entities:
        - field: user
          type: user
          score: 20
          message: CVE-2021-44228 Log4Shell triggered for host $dest$
        - field: dest
          type: system
          score: 20
          message: CVE-2021-44228 Log4Shell triggered for host $dest$
analytic_story:
    - Log4Shell CVE-2021-44228
    - CISA AA22-257A
    - CISA AA22-320A
asset_type: Endpoint
cve:
    - CVE-2021-44228
mitre_attack_id:
    - T1190
    - T1133
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: web
security_domain: threat
tests:
    - name: True Positive Test
      attack_data:
        - data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1190/log4j_proxy_logs/log4j_proxy_logs.log
          source: nginx
          sourcetype: nginx:plus:kv
      test_type: unit

Stages and Predicates

Stage 1: search

| from datamodel Web.Web

Stage 2: regex

| regex _raw="[jJnNdDiI]{4}(\:|\%3A|\/|\%2F)\w+(\:\/\/|\%3A\%2F\%2F)(\$\{.*?\}(\.)?)?"

Stage 3: fillnull

| fillnull

Stage 4: stats

| stats count by action, category, dest, dest_port, http_content_type, http_method, http_referrer, http_user_agent, site, src, url, url_domain, user

Stage 5: search

| `log4shell_jndi_payload_injection_attempt_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.

FieldKindValues
_rawregex_match
  • "[jJnNdDiI]{4}(\:|\%3A|\/|\%2F)\w+(\:\/\/|\%3A\%2F\%2F)(${.*?}(.)?)?"

Search terms

Bare-string tokens in the SPL search body. Splunk matches each token against _raw (the untyped raw event text) anywhere it appears, not against a specific field. These don't surface in the Indicators table because they aren't predicates on a known field.

StageTerm
1from
1datamodel
1Web.Web