Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
734 detections
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This rule detects when AWS Config service components, specifically delivery channels or configuration recorders, are disabled. Adversaries may disable these services to impair an organization's ability to monitor and audit changes within their AWS environment, thereby hindering detection of malicious activities.
This rule detects critical changes to AWS CloudTrail configurations, specifically when a CloudTrail is stopped (StopLogging), updated (UpdateTrail), or deleted (DeleteTrail). These actions can indicate an attempt by an attacker to evade detection by disabling or modifying logging capabilities to obscure their activities within the AWS environment.
This rule detects the creation of new network Access Control List (ACL) entries within an AWS route table. Such an event could indicate that new network access vectors have been opened, potentially allowing unauthorized access or facilitating malicious activities within the AWS environment. This is a critical security event as it directly impacts network segmentation and access control.
Looks for potential enumeration of AWS buckets via ListBuckets.
SPL Query from file: AWS CreateAccessKey
KQL Query
KQL Query from file: AWS NoSuchBucket Check
Detects suspicious AWS API calls to DeactivateMFADevice and DeleteVirtualMFADevice, which may indicate attempts to disable MFA and evade detection.
The following analytic identifies anomalous GetObject API activity in AWS, indicating potential data exfiltration attempts. It leverages AWS CloudTrail logs and uses the `anomalydetection` command to detect unusual patterns in the frequency of GetObject API calls by analyzing fields such as "count," "user_type," and "user_arn" within a 10-minute window. This activity is significant as it may indicate unauthorized data access or exfiltration from S3 buckets. If confirmed malicious, attackers could exfiltrate sensitive data, leading to data breaches and compliance violations.
'Malware authors will sometimes hardcode user agent string values when writing the network communication component of their malware. Malformed user agents can be an indication of such malware.'
'This query determines rare activity by a high-value account on a system or service. If any account with rare activity is found, the query retrieves related activity from that account on the same day and summarizes the information.'
'Identifies a list of IP addresses with a minimum number (default of 5) of failed logon attempts to AWS Console.
Uses that list to identify any successful Microsoft Entra ID logons from these IPs within the same timeframe.'
Uses that list to identify any successful Microsoft Entra ID logons from these IPs within the same timeframe.'
'Identifies a list of IP addresses with a minimum number (defualt of 5) of failed logon attempts to Microsoft Entra ID.
Uses that list to identify any successful AWS Console logons from these IPs within the same timeframe.'
Uses that list to identify any successful AWS Console logons from these IPs within the same timeframe.'
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
The following analytic detects attempts to stop a service on Linux systems. It leverages data from Linux Auditd. This activity is significant as adversaries often stop or terminate security or critical services to disable defenses or disrupt operations, as seen in malware like Industroyer2. If confirmed malicious, this could lead to the disabling of security mechanisms, allowing attackers to persist, escalate privileges, or deploy destructive payloads, severely impacting system integrity and availability.
The following analytic detects the suspicious auditd service stop. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.
The analytic detects a spike in the number of API calls made to cloud infrastructure by a user. It leverages cloud infrastructure logs and compares the current API call volume against a baseline probability density function to identify anomalies. This activity is significant because an unusual increase in API calls can indicate potential misuse or compromise of cloud resources. If confirmed malicious, this could lead to unauthorized access, data exfiltration, or disruption of cloud services, posing a significant risk to the organization's cloud environment.
The analytic detects cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
The analytic detects the creation of cloud compute instances using previously unseen image IDs. It leverages cloud infrastructure logs to identify new image IDs that have not been observed before. This activity is significant because it may indicate unauthorized or suspicious activity, such as the deployment of malicious payloads or unauthorized access to sensitive information. If confirmed malicious, this could lead to data breaches, unauthorized access, or further compromise of the cloud environment. Immediate investigation is required to determine the legitimacy of the instance creation and to mitigate potential threats.
This analytic detects AWS console login events by users who have not previously logged into the AWS console. It uses AWS CloudTrail events and compares them against a baseline of known users. A new user logging into the AWS console could indicate the creation of new accounts or potential unauthorized access, which could lead to unauthorized access to AWS resources, data exfiltration, or further exploitation within the cloud environment.
The following analytic detects a spike in the number of API calls made to cloud security groups by a user. It leverages data from the Change data model, focusing on successful firewall-related changes. This activity is significant because an abnormal increase in security group API calls can indicate potential malicious activity, such as unauthorized access or configuration changes. If confirmed malicious, this could allow an attacker to manipulate security group settings, potentially exposing sensitive resources or disrupting network security controls.
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