Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of a ScreenConnect installer executable followed by the deployment or startup of its associated client components (WindowsClient.exe or ClientService.exe) within a 30-minute window on the same device. This rule is designed to identify the unauthorized installation or deployment of remote access software.
Detects the execution of a ScreenConnect installer executable followed by the deployment or startup of its associated client components (WindowsClient.exe or ClientService.exe) within a 30-minute window on the same device. This rule is designed to identify the unauthorized installation or deployment of remote access software.
This rule detects the execution of common remote access and management (RMM) tools from non-standard directories such as user profiles, temp folders, or other locations outside of standard application installation paths (e.g., Program Files or ProgramData). Such activity is often indicative of unauthorized remote access setup or the use of portable RMM binaries by an adversary to maintain persistent access.
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
The following analytic identifies when the SID of a privileged user is added to the SID History attribute of another user. It leverages Windows Security Event Codes 4742 and 4738, combined with identity lookups, to detect this activity. This behavior is significant as it may indicate an attempt to abuse SID history for unauthorized access across multiple domains. If confirmed malicious, this activity could allow an attacker to escalate privileges or maintain persistent access within the environment, posing a significant security risk.
The following analytic detects DNS queries initiated by the Windows AI Platform to domains associated with Hugging Face, OpenAI, and other popular providers of machine learning models and services. Monitoring these DNS requests is important because it can reveal when systems are accessing external AI platforms, which may indicate the use of third-party AI resources or the transfer of sensitive data outside the organization’s environment. Detecting such activity enables organizations to enforce data governance policies, prevent unapproved use of external AI services, and maintain visibility into potential data exfiltration risks. Proactive monitoring provides better control over AI model usage and helps safeguard organizational data flows.
The following analytic detects attempts to bypass application restrictions by identifying Windows AppLocker policy violations. It leverages Windows AppLocker event logs, specifically EventCodes 8007, 8004, 8022, 8025, 8029, and 8040, to pinpoint blocked actions. This activity is significant for a SOC as it highlights potential unauthorized application executions, which could indicate malicious intent or policy circumvention. If confirmed malicious, this activity could allow an attacker to execute unauthorized applications, potentially leading to further system compromise or data exfiltration.
This detection searches for ASR audit events that are generated when a process or application attempts to perform an action that would be blocked by an ASR rule, but is allowed to proceed for auditing purposes.
The following analytic identifies potential Kerberos ticket forging attacks, specifically the Diamond Ticket attack. This is detected when a user logs into a host and the GroupMembership field in event 4627 indicates a privileged group (e.g., Domain Admins), but the user does not actually belong to that group in the directory service. The detection leverages Windows Security Event Log 4627, which logs account logon events. The analytic cross-references the GroupMembership field from the event against a pre-populated lookup of actual group memberships. Its crucial to note that the accuracy and effectiveness of this detection heavily rely on the users diligence in populating and regularly updating this lookup table. Any discrepancies between the events GroupMembership and the lookup indicate potential ticket forging. Kerberos ticket forging, especially the Diamond Ticket attack, allows attackers to impersonate any user and potentially gain unauthorized access to resources. By forging a ticket that indicates membership in a privileged group, an attacker can bypass security controls and gain elevated privileges. Detecting such discrepancies in group memberships during logon events can be a strong indicator of this attack in progress, making it crucial for security teams to monitor and investigate. If validated as a true positive, this indicates that an attacker has successfully forged a Kerberos ticket and may have gained unauthorized access to critical resources, potentially with elevated privileges.
The following analytic detects the creation of a Windows Service with a known suspicious or malicious name using Windows Event ID 7045. It leverages logs from the `wineventlog_system` to identify these services installations. This activity is significant as adversaries, including those deploying Clop ransomware, often create malicious services for lateral movement, remote code execution, persistence, and execution. If confirmed malicious, this could allow attackers to maintain persistence, execute arbitrary code, and potentially escalate privileges, posing a severe threat to the environment.
The following analytic identifies DNS queries from internal hosts to dynamic domain providers. It leverages DNS query logs from the `Network_Resolution` data model and cross-references them with a lookup file containing known dynamic DNS providers. This activity is significant because attackers often use dynamic DNS services to host malicious payloads or command-and-control servers, making it crucial for security teams to monitor. If confirmed malicious, this activity could allow attackers to bypass firewall blocks, evade detection, and maintain persistent access to the network.
This rule performs indicator-based detection for the SectopRAT malware. It monitors network activity for connections to known command-and-control (C2) IP addresses and backup domains, as well as file and process creation events matching known malicious SHA256 hashes associated with the malware.
Detects the use of legitimate archival utilities (such as 7-Zip, WinRAR, tar) or scripting engines (PowerShell) to compress or package sensitive browser profile artifacts like 'Login Data', 'Cookies', or 'Local State'. This behavior is a common indicator of credential harvesting and data staging activity by infostealers prior to exfiltration.
This rule detects typical behavior associated with infostealers targeting browser data, specifically the creation of compressed archives (.zip, .rar) in temporary directories (Temp or AppData) and the subsequent exfiltration of data via known webhook services (e.g., Discord, Telegram, Pastebin) or direct IP connections. It filters out common signed backup and synchronization software to minimize noise.
Detects network connections or DNS resolutions to known anonymous file-sharing, cloud storage, and messaging-bot API endpoints (e.g., transfer.sh, Telegram Bot API, Discord CDN) commonly abused by adversaries for data staging and exfiltration. This rule specifically targets non-browser processes that attempt to communicate with these endpoints, helping identify potentially malicious exfiltration activities.
This analytic detects network connections initiated by binaries that are not typically associated with network communication,
such as 'notepad.exe', 'calc.exe' or 'write.exe'.
It leverages Cisco Network Visibility Module logs to correlate network flow activity with process context, including command-line arguments, process path, and parent process information.
These applications are normally used for locally and do not require outbound network access. When they do initiate such connections, it may indicate process hollowing, code injection, or proxy execution, where adversaries abuse a trusted process to mask malicious activity.
such as 'notepad.exe', 'calc.exe' or 'write.exe'.
It leverages Cisco Network Visibility Module logs to correlate network flow activity with process context, including command-line arguments, process path, and parent process information.
These applications are normally used for locally and do not require outbound network access. When they do initiate such connections, it may indicate process hollowing, code injection, or proxy execution, where adversaries abuse a trusted process to mask malicious activity.
This detection identifies execution of the file synchronization utility "rclone".
It leverages Cisco Network Visibility Module logs, specifically flow data in order to capture process executions
initiating network connections.
While rclone is a legitimate command-line tool for syncing data to cloud storage providers, it has been widely abused by threat actors for data exfiltration.
This analytic inspects process name and arguments for rclone and flags usage of suspicious flags.
If matched, this could indicate malicious usage for stealthy data exfiltration or cloud abuse.
It leverages Cisco Network Visibility Module logs, specifically flow data in order to capture process executions
initiating network connections.
While rclone is a legitimate command-line tool for syncing data to cloud storage providers, it has been widely abused by threat actors for data exfiltration.
This analytic inspects process name and arguments for rclone and flags usage of suspicious flags.
If matched, this could indicate malicious usage for stealthy data exfiltration or cloud abuse.
This analytic detects system binaries that are commonly abused in process injection techniques but are observed without any command-line arguments.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
Binaries such as `rundll32.exe`, `regsvr32.exe`, `dllhost.exe`, `svchost.exe`, and others are legitimate Windows processes that are often injected into by malware or post-exploitation frameworks (e.g., Cobalt Strike) to hide execution.
When these processes are seen initiating a network connection with an empty or missing command line, it can indicate
potential injection and communication with a command and control server.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
Binaries such as `rundll32.exe`, `regsvr32.exe`, `dllhost.exe`, `svchost.exe`, and others are legitimate Windows processes that are often injected into by malware or post-exploitation frameworks (e.g., Cobalt Strike) to hide execution.
When these processes are seen initiating a network connection with an empty or missing command line, it can indicate
potential injection and communication with a command and control server.
This analytic identifies the use of `msxsl.exe` initiating a network connection to a non-private IP address.
Although `msxsl.exe` is a legitimate Microsoft utility used to apply XSLT transformations, adversaries can abuse it
to execute arbitrary code or load external resources in an evasive manner.
This detection leverages Cisco NVM telemetry to identify potentially malicious use of `msxsl.exe` making network connections
that may indicate command and control (C2) or data exfiltration activity.
Although `msxsl.exe` is a legitimate Microsoft utility used to apply XSLT transformations, adversaries can abuse it
to execute arbitrary code or load external resources in an evasive manner.
This detection leverages Cisco NVM telemetry to identify potentially malicious use of `msxsl.exe` making network connections
that may indicate command and control (C2) or data exfiltration activity.
This analytic detects the use of `curl.exe` with insecure flags such as `-k`, `--insecure`, `--proxy-insecure`, or `--doh-insecure`
which disable TLS certificate validation.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
This behavior may indicate an attempt to bypass certificate validation to connect to potentially untrusted or malicious endpoints,
a common tactic in red team operations, malware staging, or data exfiltration over HTTPS.
which disable TLS certificate validation.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
This behavior may indicate an attempt to bypass certificate validation to connect to potentially untrusted or malicious endpoints,
a common tactic in red team operations, malware staging, or data exfiltration over HTTPS.
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