Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic identifies non-browser processes reaching out to public IP lookup or geolocation services,
such as `ipinfo.io`, `icanhazip.com`, `ip-api.com`, and others.
These domains are commonly used by legitimate tools, but their usage outside of browsers may indicate
network reconnaissance, virtual machine detection, or staging by malware.
This activity is observed in post-exploitation frameworks, stealer malware, and advanced threat actor campaigns.
The detection relies on Cisco Network Visibility Module (NVM) telemetry and excludes known browser
processes to reduce noise.
such as `ipinfo.io`, `icanhazip.com`, `ip-api.com`, and others.
These domains are commonly used by legitimate tools, but their usage outside of browsers may indicate
network reconnaissance, virtual machine detection, or staging by malware.
This activity is observed in post-exploitation frameworks, stealer malware, and advanced threat actor campaigns.
The detection relies on Cisco Network Visibility Module (NVM) telemetry and excludes known browser
processes to reduce noise.
Detects DNS lookups and outbound network connections to known command and control (C2) and staging domains associated with the STAC4924 campaign. The rule performs strict matching on domain names to ensure that subdomains are identified while avoiding false positives from partial string matches within URLs.
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 post-exploitation activity where a web server process spawns a command shell, executes system discovery commands, and immediately initiates an outbound network connection. This behavior is indicative of a web-based exploit leading to interactive command execution and subsequent C2 communication.
Detects an suspicious progression of activities originating from identified AI assistant/agent processes. The rule monitors for a chain of behaviors occurring within a 15-minute window: execution of an AI agent/tool, followed by host discovery (network/system enumeration), access to sensitive local credential files, archival of data, and outbound network communication to common file-sharing/exfiltration platforms.
Detects activity associated with Everest ransomware by matching known file hashes (in DeviceFileEvents/DeviceProcessEvents) and known C2/leak-site domains (in DeviceNetworkEvents).
Detects a suspicious sequence of events involving NetScaler ADC or Gateway appliances: anomalous account authentication, followed by the establishment of a VPN or remote access session, and subsequent unusual outbound network activity indicating potential lateral movement or C2 communication from the appliance.
This rule monitors for indicators of compromise (IOCs) associated with known malware and C2 infrastructure, including specific IP:port combinations, malicious domains, URLs for file downloads, and SHA256 hashes of known malware. The rule correlates data across device network events, file events, and process execution events to identify potential infections or communication with malicious infrastructure.
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 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 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.
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 high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects instances where a process contacts multiple distinct AI-provider domains within a short time frame while simultaneously performing suspicious operations, such as accessing the LSASS memory, executing process injection, or establishing WMI persistence. This pattern is indicative of a potential 'ClosedQuorum' adversary behavior involving data exfiltration or AI-assisted malicious activity.
Detects network connections from common web browsers to domains associated with the BragJack threat actor infrastructure. This activity potentially indicates an end-user accessing malicious sites used for credential harvesting, malware delivery, or C2 communication.
Detects outbound HTTP traffic from internal hosts directed toward a known IP address identified as hosting AdaptixC2 infrastructure, specifically associated with the distribution of a trojanized 'mscopilot.exe' executable.
This rule monitors for network connections and process activities associated with known malicious indicators, including file hashes, C2 IP addresses, domains, and specific URLs. It maps these activities to identify potential command and control communication or other malicious network activity occurring on endpoints.
This rule detects established TLS connections to external domains that exhibit characteristics often associated with phishing campaigns. Specifically, it looks for domain names in the SNI field that contain common brand names (e.g., microsoft, google, paypal) combined with typical login-related keywords (e.g., login, verify, auth) on high-churn or suspicious Top-Level Domains (TLDs) such as .top, .xyz, or .icu.
Detects the installation of unauthorized AI-related browser extensions followed by outbound network communication from the browser process to known external AI service API endpoints within one hour. This behavior is indicative of potential data exfiltration via shadow AI tools, bypassing standard enterprise DLP controls.
Detects the installation of unauthorized AI-related browser extensions followed by outbound network communication from the browser process to known external AI service API endpoints within one hour. This behavior is indicative of potential data exfiltration via shadow AI tools, bypassing standard enterprise DLP controls.
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