Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
260 detections
Filters
Last updated
All Time
Detection languages
141
60
21
18
11
Contributors
80
44
20
19
11
Categories
77
69
67
49
37
Platforms
203
56
30
13
11
Products / Services
10,683
9,759
6,695
4,421
3,750
260
MITRE Techniques
75
73
53
41
40
CVEs
8
4
4
3
3
IDS Classtypes
4
1
1
1
IDS Protocols
4
1
'This query helps identify rare DNS connections and resulting data transfer to/from the associated domain. It can help identify unexpected large data transfers to or from internal systems which may indicate data exfil or malicious tool download.'
The analytic detects outbound SMB (Server Message Block) connections from internal hosts to external servers. It identifies this activity by monitoring network traffic for SMB requests directed towards the Internet, which are unusual for standard operations. This detection is significant for a SOC as it can indicate an attacker's attempt to retrieve credential hashes through compromised servers, a key step in lateral movement and privilege escalation. If confirmed malicious, this activity could lead to unauthorized access to sensitive data and potential full system compromise.
'Matches domain name IOCs related to Forest Blizzard group activity published July 2019 with CommonSecurityLog, DnsEvents and VMConnection dataTypes.
References: https://blogs.microsoft.com/on-the-issues/2019/07/17/new-cyberthreats-require-new-ways-to-protect-democracy/.'
References: https://blogs.microsoft.com/on-the-issues/2019/07/17/new-cyberthreats-require-new-ways-to-protect-democracy/.'
'This query combines different SQL alerts with CommonSecurityLogs and AuditLogs helping analysts /investigate any possible SQL related attacks faster
thus reducing Mean Time To Respond'
thus reducing Mean Time To Respond'
'Identifies a match across various data feeds for domains, hashes and IP IOC related to Mercury
Reference: https://www.microsoft.com/security/blog/2022/08/25/mercury-leveraging-log4j-2-vulnerabilities-in-unpatched-systems-to-target-israeli-organizations/'
Reference: https://www.microsoft.com/security/blog/2022/08/25/mercury-leveraging-log4j-2-vulnerabilities-in-unpatched-systems-to-target-israeli-organizations/'
'CreepyDrive uses OneDrive for command and control, however, it makes regular requests to predicatable paths.
This detecton will alert when over 20 sequences are observed in a single day.'
This detecton will alert when over 20 sequences are observed in a single day.'
'This detection will identify network requests in HTTP proxy data that contains Base64 encoded IP addresses. After identifying candidates the query joins with DeviceNetworkEvents to idnetify any machine within the network using that IP address. Alerts indicate that the IP address of a machine within your network was seen with it's IP address base64 encoded in an outbound web request. This method of egressing the IP was seen used in POLONIUM's RunningRAT tool, however the detection is generic.'
The analytic detects instances where network traffic, identified by port and transport layer protocol as prohibited in the "lookup_interesting_ports" table, is allowed. It uses the Network_Traffic data model to cross-reference traffic data against predefined security policies. This activity is significant for a SOC as it highlights potential misconfigurations or policy violations that could lead to unauthorized access or data exfiltration. If confirmed malicious, this could allow attackers to bypass network defenses, leading to potential data breaches and compromising the organization's security posture.
'This detection will alert when RunningRAT URI parameters or paths are detect in an HTTP request.
Id the device blocked this communication presence of this alert means the RunningRAT implant is likely still executing on the source host.'
Id the device blocked this communication presence of this alert means the RunningRAT implant is likely still executing on the source host.'
'Identifies a match across various data feeds for domains related to an actor tracked by Microsoft as Star Blizzard.'
'This detection will identify network requests in HTTP proxy data that contains Base64 encoded usernames from machines in the DeviceEvents table.
This technique was seen usee by POLONIUM in their RunningRAT tool.'
This technique was seen usee by POLONIUM in their RunningRAT tool.'
'CreepyDrive uses OneDrive for command and control. This detection identifies URLs specific to CreepyDrive.'
This rule identifies 'improbable travel' scenarios where a user successfully logs in from two geographically distant locations within a short time frame, suggesting potential account compromise or abuse, possibly related to Remote Employment Fraud (REF). It calculates the speed of travel required between consecutive login locations and flags events where the speed and distance exceed predefined thresholds. It also checks if the login country differs from the user's known work country.
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 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.
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.
The following analytic detects the creation of EC2 instances with previously unseen instance types. It leverages Splunk's tstats command to analyze data from the Change data model, identifying instance types that have not been previously recorded. This activity is significant for a SOC because it may indicate unauthorized or suspicious activity, such as an attacker attempting to create instances for malicious purposes. If confirmed malicious, this could lead to unauthorized access, data exfiltration, system compromise, or service disruption. Immediate investigation is required to determine the legitimacy of the instance creation.
The analytic identifies DNS queries to domains associated with the 3CX supply chain attack. This activity is significant because it can indicate a potential compromise stemming from the 3CX supply chain attack, which is known for distributing malicious software through trusted updates. If confirmed malicious, this activity could allow attackers to establish a foothold in the network, exfiltrate sensitive data, or further propagate malware, leading to extensive damage and data breaches.
Page 10 of 13