Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects when an AI agent's code execution sandbox (e.g., Python, Node.js, or Shell interpreters) initiates suspicious child processes. This includes the execution of network utilities for potential C2 (e.g., curl, nc, socat), the creation of interactive reverse shells, or the execution of credential harvesting tools (e.g., mimikatz, secretsdump), which suggests the AI agent's sandbox environment has been compromised or abused.
Detects instances where the Windows Explorer process (the parent of the 'Run' dialog) spawns common command-line interpreters. This behavior is indicative of the 'ClickFix' phishing technique, where users are socially engineered to paste malicious commands into the Windows Run dialog.
Detects network activity associated with a malicious NPM package (typosquatting) beaconing to a known C2 server (69.48.229.140) and performing command and control operations, including command polling and data exfiltration, specifically from a Node.js environment.
Detects instances where the Microsoft Edge proxy process (msedge_proxy.exe) initiates command-line interpreters such as cmd.exe, powershell.exe, or pwsh.exe. This behavior is highly suspicious as a browser-related process should not typically be spawning shell interpreters, potentially indicating exploitation of browser vulnerabilities or malicious script execution.
Detects suspicious command execution patterns involving cmd.exe or powershell.exe spawned by services.exe, or involving redirection to temporary files, which are consistent with Impacket-based remote service execution commonly associated with NeedyMantis malware deployment.
This analytic identifies the use of Chromium-based browsers (like Microsoft Edge) running in headless mode with the `--dump-dom` argument.
This behavior has been observed in attack campaigns such as DUCKTAIL, where browsers are automated to stealthily download content from the internet using direct URLs or suspicious hosting platforms.
The detection focuses on identifying connections to known file-sharing domains or direct IPs extracted from command-line arguments and cross-checks those against the destination of the flow.
Since it leverages Cisco Network Visibility Module telemetry, the rule triggers only if a network connection is made.
This behavior has been observed in attack campaigns such as DUCKTAIL, where browsers are automated to stealthily download content from the internet using direct URLs or suspicious hosting platforms.
The detection focuses on identifying connections to known file-sharing domains or direct IPs extracted from command-line arguments and cross-checks those against the destination of the flow.
Since it leverages Cisco Network Visibility Module telemetry, the rule triggers only if a network connection is made.
Detects various indicators of compromise (IOCs) including known malicious file hashes, suspicious file names commonly associated with staging or initialization in web directories, and network communication to known malicious domains or URLs. It also monitors process execution command lines for references to these IOCs, excluding common browser processes.
This rule detects potential unauthorized or suspicious installation of an RMM (Remote Monitoring and Management) agent on a Windows host. It flags cases where a process performs multiple suspicious actions within a 24-hour window, specifically combining the installation or starting of a service related to an RMM agent, the creation of a Windows Firewall rule for the RMM agent executable, and/or the creation of log events related to the installer.
Detects the execution of discovery or credential access utilities (e.g., whoami, net, reg, ldapsearch) spawned by Java-based server processes like java.exe or tomcat.exe. This activity is often indicative of an attacker leveraging a vulnerable web application to perform reconnaissance or credential harvesting on the host system.
Detects instances where a browser extension is installed, followed within a two-hour window by the browser process making network connections to generative AI service domains. This behavior is indicative of potential malicious browser extension activity, such as scraping or exfiltrating session/browsing data to third-party AI backend services.
Detects two distinct suspicious patterns: first, the deletion of executable files residing in common user-writable temporary directories (e.g., Temp, Downloads, AppData) using command-line tools like 'del' or 'erase', which is often indicative of anti-forensic activity after malware execution. Second, it monitors for network traffic involving HTTP POST requests or specific SOAP headers related to 'tempuri.org', which are commonly associated with default .NET WCF service scaffolding and may be used by adversaries for C2 communication or exfiltration.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule monitors for various indicators of compromise (IOCs) including malicious domains, IP addresses, specific URI paths, file names, and file hashes. It aggregates telemetry from network, file, process, and certificate events to detect potential threats interacting with known bad infrastructure or executing suspicious files associated with malware campaigns.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
Detects suspicious child processes such as shell interpreters, download utilities, and base64-decoded commands spawned from core Citrix NetScaler processes (nsppe, httpd, aoacli, nscli). This pattern is often indicative of post-exploitation command execution following an exploitation of remote code execution (RCE) vulnerabilities.
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
Detects instances where the Ivanti Sentry service process spawns suspicious child processes (shells, network utilities, or interpreters) while running with root privileges. This behavior is indicative of exploitation of CVE-2026-10520, an OS command injection vulnerability in Ivanti Sentry that enables unauthenticated remote code execution with root permissions.
Detects when common web server worker processes spawn command-line tools or shell interpreters, which is a common post-exploitation technique used by web shells like Godzilla to execute arbitrary commands.
Detects the use of administrative utilities (psexec.exe, wmic.exe, powershell.exe, cmd.exe) initiating network connections over common remote management ports (135, 139, 445, 3389, 5985, 5986) to internal destinations. This behavior is indicative of lateral movement activity, particularly when initiated from a host that has recently engaged in credential harvesting or infostealer-related activity. The rule excludes common, expected sources to minimize noise.
The following analytic detects file downloads involving executable, archive, or scripting-related file types that are commonly used in malware delivery.
These file types include formats like PE executables, shell scripts, autorun files, installers, and known testing samples such as EICAR.
This detection leverages Cisco Secure Firewall Threat Defense logs and enriches the results using a filetype lookup to provide context.
If confirmed malicious, these downloads could indicate the initial infection vector, malware staging, or scripting abuse.
These file types include formats like PE executables, shell scripts, autorun files, installers, and known testing samples such as EICAR.
This detection leverages Cisco Secure Firewall Threat Defense logs and enriches the results using a filetype lookup to provide context.
If confirmed malicious, these downloads could indicate the initial infection vector, malware staging, or scripting abuse.
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