Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
483 detections
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This analytic detects modifications to the default Group Policy Objects (GPOs) in an Active Directory environment. It leverages Splunk's Admon to monitor updates to the "Default Domain Policy" and "Default Domain Controllers Policy." This activity is significant because changes to these default GPOs can indicate an adversary with privileged access attempting to gain further control, establish persistence, or deploy malware across multiple hosts. If confirmed malicious, such modifications could lead to widespread policy enforcement changes, unauthorized access, and potential compromise of the entire domain environment.
'Any Alerts that fired related to a given IpAddress during the range of +6h and -3d'
This analytic identifies drivers being loaded across the fleet by leveraging a PowerShell script to capture driver data. It helps monitor for unauthorized or malicious drivers that could compromise system integrity, execute arbitrary code, escalate privileges, or maintain persistence within the environment.
This query was originally published in the threat analytics report, "Exchange Server zero-days exploited in the wild".
In early March 2021, Microsoft released patches for four different zero-day vulnerabilities affecting Microsoft Exchange Server. The vulnerabilities were being used in a coordinated attack. For more information on the vulnerabilities, visit the following links:
1. CVE-2021-26855
2. CVE-2021-26857
3. CVE-2021-26858
4. CVE-2021-27065
The following query detects 7-zip activity associated with this threat. 7-ZIP is a legitimate tool used for file archiving; however, unusual 7-ZIP activity combined with other evidence might indicate that an attacker is compressing data for exfiltration.
More queries related to this threat can be found under the See also section of this page.
Reference - https://msrc-blog.microsoft.com/2021/03/02/multiple-security-updates-released-for-exchange-server/
In early March 2021, Microsoft released patches for four different zero-day vulnerabilities affecting Microsoft Exchange Server. The vulnerabilities were being used in a coordinated attack. For more information on the vulnerabilities, visit the following links:
1. CVE-2021-26855
2. CVE-2021-26857
3. CVE-2021-26858
4. CVE-2021-27065
The following query detects 7-zip activity associated with this threat. 7-ZIP is a legitimate tool used for file archiving; however, unusual 7-ZIP activity combined with other evidence might indicate that an attacker is compressing data for exfiltration.
More queries related to this threat can be found under the See also section of this page.
Reference - https://msrc-blog.microsoft.com/2021/03/02/multiple-security-updates-released-for-exchange-server/
'This detection uses Normalized Process Events to hunt Certutil activities'
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.
Identifies SolarWinds SUNBURST and SUPERNOVA backdoor file hash IOCs in File Events
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimFileEvent)
References:
- https://www.fireeye.com/blog/threat-research/2020/12/evasive-attacker-leverages-solarwinds-supply-chain-compromises-with-sunburst-backdoor.html
- https://gist.github.com/olafhartong/71ffdd4cab4b6acd5cbcd1a0691ff82f
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimFileEvent)
References:
- https://www.fireeye.com/blog/threat-research/2020/12/evasive-attacker-leverages-solarwinds-supply-chain-compromises-with-sunburst-backdoor.html
- https://gist.github.com/olafhartong/71ffdd4cab4b6acd5cbcd1a0691ff82f
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 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 rule detects rare input devices (microphones) used during Zoom meetings. It specifically looks for microphone devices that are not commonly observed, while excluding typical devices like iPhones, FaceTimes, AirPods, and MacBooks. The primary goal is to identify unusual device usage that could be indicative of Remote Employment Fraud (REF), where actors might use non-standard equipment. This is a hunting query designed to flag anomalies for further investigation.
The following analytic detects the suspicious sysmon 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.
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 analytic detects the creation of a cloud compute instance in a region that has not been previously used within the last hour. It leverages cloud infrastructure logs and compares the regions of newly created instances against a lookup file of historically used regions. This activity is significant because the creation of instances in new regions can indicate unauthorized or suspicious activity, such as an attacker attempting to evade detection or establish a foothold in a less monitored area. If confirmed malicious, this could lead to unauthorized resource usage, data exfiltration, or further compromise of the cloud environment.
Alert on downloading a known file hash from a known IP with VT Relationships.
This analytic detects Lumma Stealer download attempts using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where Snort signatures with specific IDs have been triggered. If confirmed malicious, this behavior could indicate an active infection of Lumma Stealer.
This analytic aggregates and summarizes alerts from Microsoft Defender for Endpoint. It extracts details such as source, file name, severity, process command line, IP address, registry key, signature, description, and unique ID. The detection is not intended to identify new activity from raw data but rather to leverage existing Microsoft Defender for Endpoint alerts for correlation and risk-based alerting. It filters out alerts with a 'clean' verdict and dynamically maps MITRE techniques and assigns risk scores based on the alert's severity.
This analytic identifies Snort signatures that have triggered only once in the past 7 days across all Cisco Secure Firewall IntrusionEvent logs. While these rules typically do not trigger in day-to-day network activity, their sudden appearance may indicate early-stage compromise, previously unseen malware, or reconnaissance activity against less commonly exposed services. Investigating these outliers can provide valuable insight into new or low-noise adversary behaviors.
This analytic detects the use of known suspicious SSL certificates by comparing the SHA1 fingerprint from Cisco Secure Firewall logs against a blacklist. This is crucial for identifying malware distribution, C2 infrastructure, or phishing campaigns that reuse or self-sign certificates. Detection of such activity may indicate beaconing, malware download, or data exfiltration over TLS/SSL.
This analytic highlights high-impact intrusion events detected by Cisco Secure Firewall. It leverages Cisco Secure Firewall Threat Defense logs, specifically the IntrusionEvent event type, and focuses on events with an `Impact` score of 1 or 2. If confirmed malicious, these events may indicate a potentially compromised host.
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