Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects network communication, DNS queries, email interactions, and URL clicks associated with known TA419 threat actor infrastructure. It monitors multiple telemetry sources to identify indicators of compromise (IOCs) such as specific domains, IP addresses, and email addresses.
This rule detects network communication, DNS queries, email interactions, and URL clicks associated with known TA419 threat actor infrastructure. It monitors multiple telemetry sources to identify indicators of compromise (IOCs) such as specific domains, IP addresses, and email addresses.
Detects the first-ever observed network connection from a device to WhatsApp Web or Telegram Web within a 30-day lookback period. This behavior is used to identify potentially unauthorized companion-device linking to a user's messenger account, which could indicate credential theft or unauthorized access.
This rule monitors endpoint telemetry for indicators of compromise (IOCs) associated with known malicious activity. It checks for file creation, process execution, and network connections that match a defined list of malicious file hashes (SHA256, SHA1, MD5), C2 IP addresses, and malicious domains or URL patterns.
Detects anomalous process execution and loopback network activity associated with the Model Context Protocol (MCP) 'exec_in_session' method. This pattern indicates an adversary potentially abusing the AI coding assistant's MCP server capabilities to execute arbitrary commands as a C2 channel.
Detects outbound network connections to domains, URLs, and IP:Port combinations identified as malicious in the ThreatFox OSINT feed. This rule covers various commodity malware C2 and payload delivery infrastructure.
Detects the first-ever observed network connection from a device to WhatsApp Web or Telegram Web within a 30-day lookback period. This behavior is used to identify potentially unauthorized companion-device linking to a user's messenger account, which could indicate credential theft or unauthorized access.
Detects outbound HTTP requests to a known C2 domain (letsdiskuss.com) and a specific URI path, characteristic of the 'Lorem Ipsum' malware loader's dead-drop resolver lookup.
Detects activity associated with the MALFEX npm supply-chain campaign (also known as Overlord/movinlike). This rule performs a sweep for known malicious file hashes, suspicious process command lines, outbound network connections to malicious domains or IPs, and email communications from identified adversary-controlled accounts.
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.
This rule detects network communication with known malicious infrastructure (C2 IPs and URLs), presence of malicious files identified by SHA256 hashes on disk, and execution of known malicious files. It also correlates these activities with specific operator email addresses involved in the malicious campaign.
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.
Detects a sequential pattern where a browser process (Chrome, Edge, or Safari) accesses an AI chat platform's conversation API, followed within 5 minutes by a network connection to a known unauthorized exfiltration destination (api.pbapi.xyz). This pattern suggests the potential use of a browser-based tool or extension (e.g., Poper Blocker or similar) to intercept and exfiltrate AI chat history.
Detects P7 DarkSword implant C2 beaconing: HTTP/1.0 JSON POSTs to /beacon, /event or /a with the hardcoded iPhone OS 18_5 Safari 18.5 User-Agent. Requires the full combination of protocol version, method, URI, UA and content type, and alerts only after 3 matching requests from one source within 120 seconds (detection_filter) to suppress one-off matches.
Detects malicious command-and-control (C2) activity targeting Citrix NetScaler appliances (tracked as CVE-2026-88772). The rules identify specific malformed HTTP headers (NSC_LDAP, NSC_CLIENTTYPE, X-UX) used to establish a command channel, as well as potential webshell masquerading through ico-to-sig URI patterns in the /vpn/media/ path.
This Splunk query analyzes web logs to identify and categorize user agents, detecting various types of c2 frameworks. This activity can signify malicious actors attempting to interact with hosts on the network using known default configurations of command and control tools.
This Splunk query analyzes web access logs to identify and categorize non-browser user agents, detecting various types of security tools, scripting languages, automation frameworks, and suspicious patterns. This activity can signify malicious actors attempting to interact with web endpoints in non-standard ways.
This rule monitors endpoint telemetry for indicators of compromise (IOCs) associated with known malicious activity. It checks for file creation, process execution, and network connections that match a defined list of malicious file hashes (SHA256, SHA1, MD5), C2 IP addresses, and malicious domains or URL patterns.
Detects a multi-stage compromise sequence involving anomalous authentication followed by VPN session establishment and a burst of outbound connections from Citrix ADC/Gateway appliances. Tightened to reduce false positives from legitimate admin access, routine VPN sessions, and authorized appliance telemetry/updates.
Detects TLS connections to a specific, potentially adversary-controlled ScreenConnect relay infrastructure endpoint. Adversaries frequently abuse legitimate remote access tools like ScreenConnect for command and control purposes.
Detects potential Cobalt Strike or Sliver command and control (C2) beaconing behavior by analyzing network proxy, firewall, and flow logs for common C2 URI patterns, known malicious JA3/JA3S TLS fingerprints, and consistent periodic communication intervals (low jitter) characteristic of automated beacons.
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