The detection rule identifies potential unauthorized HTTP traffic to an Athena service, which could indicate data exfiltration or command and control activity. SOC teams should proactively hunt for this behavior in Azure Sentinel to detect early signs of lateral movement or data compromise in cloud environments.
YARA Rule
rule AthenaHTTP
{
meta:
author = "Brian Wallace @botnet_hunter"
author_email = "[email protected]"
date = "2014-08-09"
description = "Identify Athena HTTP"
strings:
$s1 = "%s(%s)"
$s2 = "type:on_exec"
$s3 = "uid:%s"
$s4 = "priv:%s"
$s5 = "arch:x%s"
$s6 = "gend:%s"
$s7 = "cores:%i"
$s8 = "ver:%s"
$s9 = "net:%s"
condition:
all of them
}
This YARA rule can be deployed in the following contexts:
This rule contains 9 string patterns in its detection logic.
Scenario: Scheduled ETL Job Using AWS Athena
Description: A data engineering team runs a scheduled ETL job that queries AWS Athena for data processing.
Filter/Exclusion: aws_account_id = "123456789012" and query_type = "ETL_job"
Scenario: Admin Task to Monitor Query Logs
Description: A system administrator uses AWS Athena to analyze query logs for performance tuning or troubleshooting.
Filter/Exclusion: user_principal_name = "admin_user", query_type = "log_analysis"
Scenario: Development Environment Query Testing
Description: A developer runs multiple test queries in a development environment to validate query syntax or performance.
Filter/Exclusion: environment = "dev", query_type = "test_query"
Scenario: Automated Reporting Tool Using Athena
Description: A business intelligence tool (e.g., Tableau, Looker) automates report generation by querying AWS Athena.
Filter/Exclusion: tool_name = "Tableau", query_type = "report_generation"
Scenario: Security Team Analyzing Query Patterns
Description: The security team uses AWS Athena to analyze query patterns for potential security threats or compliance checks.
Filter/Exclusion: user_group = "security_team", query_type = "security_analysis"