Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 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 performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
This rule performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
This rule performs a retrospective search across device file and network events for indicators of compromise associated with the UNC6240/ShinyHunters actor's activity against PeopleSoft, specifically linked to CVE-2026-35273. It monitors for known malicious file hashes (JSP webshells and executables), connections to known C2 infrastructure, and DNS lookups for specific malicious domains.
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 traffic indicators associated with Cobalt Strike beaconing activity, specifically focusing on common default or near-default Malleable C2 HTTP profile patterns. This includes hardcoded URI paths often used in default configurations (e.g., jQuery library names, pixel gifs) and specific combinations of HTTP headers and user-agent strings commonly observed in adversary C2 frameworks.
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.
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 monitors for network communication with known malicious infrastructure (IPs/domains) and the execution of specific suspicious file names. It correlates device network events, file system activity, and process execution, specifically flagging attempts to execute MSI installers or other binaries associated with the identified threat indicators.
This rule detects successful network connections to known malicious IP addresses or the domain 'forgitlab.com', which are associated with the Azazel malware threat infrastructure.
This rule performs a sweep across device file and network events for indicators of compromise (IOCs) associated with the UAT-11587/Antino campaign. It detects malicious file hashes, specific C2 domain connections, and known lure URLs (HTA/WSF) identified by Cisco Talos.
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 network connections initiated by common web browsers (chrome.exe, msedge.exe, brave.exe) to known domains associated with a specific VPN proxy service or subscription-based proxy farm infrastructure. The rule flags endpoints communicating with URLs involved in proxy beaconing, fallback hosting, and subscription API calls.
Detects the RatHat ADB self-pairing sequence on Android devices, where an application uses shell-level access gained via ADB to stage and execute malicious binaries (such as Go Agents or FRP clients) from /data/local/tmp. The rule correlates the staging and execution of these specific binaries with subsequent network communication indicative of C2 or data exfiltration.
Detects network activity associated with the RatHat Android malware, specifically tracking device registration, log uploads to '/api/node/', and subsequent WebSocket protocol upgrades used for command-and-control communications.
This rule detects instances where Python package management processes (pip or python) perform build or installation tasks, immediately followed by an outbound network connection initiated by the same process tree to a non-PyPI domain. This behavior is indicative of a supply chain attack where a malicious package contains code (e.g., in setup.py) that beacons to an attacker-controlled server upon installation.
Detects outbound network traffic from internal hosts to external destinations containing a specific, hard-coded User-Agent string (firefox/21.0). This behavior is characteristic of the NeedyMantis malware family, which utilizes this string to identify its own C2 communications, and is a strong indicator of compromise.
Detects HTTP GET requests to raw.githubusercontent.com that include an 'Authorization: token' header, indicating the potential use of a GitHub Personal Access Token (PAT) for command and control or data exfiltration by the Kimsuky threat group.
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.
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