Detection of tools built by NirSoft: endpointEndpointNoneversion:11
The following analytic identifies the execution of tools built by NirSoft by detecting specific command-line arguments such as "/stext" and "/scomma". It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line executions. This activity is significant because NirSoft tools, while legitimate, can be exploited by attackers for malicious purposes such as credential theft or system reconnaissance. If confirmed malicious, this activity could lead to unauthorized access, data exfiltration, or further compromise of the affected system.
Suspicious Email Attachment Extensions: networkEndpointNoneversion:12
The following analytic detects emails containing attachments with suspicious file extensions. It leverages the Email data model in Splunk, using the tstats command to identify emails where the attachment filename is not empty. This detection is significant for SOC analysts as it highlights potential phishing or malware delivery attempts, which are common vectors for data breaches and malware infections. If confirmed malicious, this activity could lead to unauthorized access to sensitive information, system compromise, or data exfiltration. Immediate review and analysis of the identified emails and attachments are crucial to mitigate these risks.
Email Attachments With Lots Of Spaces: networkEndpointNoneversion:11
The following analytic detects email attachments with an unusually high number of spaces in their file names, which is a common tactic used by attackers to obfuscate file extensions. It leverages the Email data model to identify attachments where the ratio of spaces to the total file name length exceeds 10%. This behavior is significant as it may indicate an attempt to bypass security filters and deliver malicious payloads. If confirmed malicious, this activity could lead to the execution of harmful code or unauthorized access to sensitive information within the recipient's environment.
SMB Traffic Spike: networkEndpointNoneversion:11
The following analytic detects spikes in Server Message Block (SMB) traffic connections, which are used for sharing files and resources between computers. It leverages network traffic logs to monitor connections on ports 139 and 445, and SMB application usage. By calculating the average and standard deviation of SMB connections over the past 70 minutes, it identifies sources exceeding two standard deviations from the average. This activity is significant as it may indicate potential SMB-based attacks, such as ransomware or data theft. If confirmed malicious, attackers could exfiltrate data or spread malware within the network.
Prohibited Software On Endpoint: endpointEndpoint2024-11-14version:5
This search looks for applications on the endpoint that you have marked as prohibited.
Detect Use of cmd exe to Launch Script Interpreters: endpointEndpointNoneversion:16
The following detects the execution of cscript.exe or wscript.exe processes spawned by cmd.exe, leveraging Endpoint Detection and Response (EDR) telemetry mapped to the Endpoint data model, with additional contextual filtering to improve fidelity and reduce false positives.
It focuses on executions originating from user-writable directories such as Users, AppData, Temp, and Downloads, which are commonly abused by attackers to stage and execute malicious scripts, while excluding trusted system paths like C:\Windows\System32\ and C:\Program Files\ that are typically associated with legitimate activity.
The detection also filters out service accounts (e.g., accounts ending with $ or known naming conventions) to minimize noise from automated processes and incorporates command-line context to better assess script execution patterns and identify potentially suspicious behavior.
SMB Traffic Spike - MLTK: networkEndpoint2026-03-10version:11
The following analytic identifies spikes in the number of Server Message Block (SMB) connections using the Machine Learning Toolkit (MLTK). It leverages the Network_Traffic data model to monitor SMB traffic on ports 139 and 445, applying a machine learning model to detect anomalies. This activity is significant because sudden increases in SMB traffic can indicate lateral movement or data exfiltration attempts by attackers. If confirmed malicious, this behavior could lead to unauthorized access, data theft, or further compromise of the network.
Registry Keys Used For Persistence: endpointEndpointNoneversion:35
The following analytic identifies modifications to registry keys commonly used for persistence mechanisms. It leverages data from endpoint detection sources like Sysmon or Carbon Black, focusing on specific registry paths known to initiate applications or services during system startup. This activity is significant as unauthorized changes to these keys can indicate attempts to maintain persistence or execute malicious actions upon system boot. If confirmed malicious, this could allow attackers to achieve persistent access, execute arbitrary code, or maintain control over compromised systems, posing a severe threat to system integrity and security.
