Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The following analytic identifies Living Off the Land Binaries and Scripts (LOLBAS) that can legitimately initiate public network connections but are communicating over uncommon destination ports.
It leverages the Network Traffic data model and applies per-binary common-port exclusions to reduce false positives while preserving suspicious non-standard communication.
This behavior may indicate payload download, command-and-control, proxy execution, or attempts to blend malicious traffic into trusted Windows binaries.
Join this detection with the Process Execution events to provide context and avoid false positives.
It leverages the Network Traffic data model and applies per-binary common-port exclusions to reduce false positives while preserving suspicious non-standard communication.
This behavior may indicate payload download, command-and-control, proxy execution, or attempts to blend malicious traffic into trusted Windows binaries.
Join this detection with the Process Execution events to provide context and avoid false positives.
Detects outbound network connections to known SectopRAT C2 infrastructure, specifically targeting the hardcoded IP 98.142.252.140 or the non-standard port 15847 often used for encrypted exfiltration.
This analytic detects suspicious python package installations where the package name resembles popular Python libraries but may be typosquatted or slightly altered.
Typosquatting is a common technique used by attackers to trick users into installing malicious packages that mimic legitimate ones.
This detection leverages Cisco NVM flow telemetry and checks for pip or poetry package managers with the "install" or "add" flags, making outbound connections to package repository such as `pypi.org` with known or suspected typo package names.
Typosquatting is a common technique used by attackers to trick users into installing malicious packages that mimic legitimate ones.
This detection leverages Cisco NVM flow telemetry and checks for pip or poetry package managers with the "install" or "add" flags, making outbound connections to package repository such as `pypi.org` with known or suspected typo package names.
The following analytic identifies DNS queries to domains associated with the 3CX supply chain attack. It leverages the Network_Resolution datamodel to detect these suspicious domain indicators. This activity is significant because it can indicate a potential compromise stemming from the 3CX supply chain attack, which is known for distributing malicious software through trusted updates. If confirmed malicious, this activity could allow attackers to establish a foothold in the network, exfiltrate sensitive data, or further propagate malware, leading to extensive damage and data breaches.
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.
This rule detects outbound TLS traffic to the domain 'trace-flow.ru', which is associated with Max Messenger covert telemetry beaconing behavior. The rule inspects the Server Name Indication (SNI) field in the TLS handshake for the specific domain string.
Detects outbound HTTP GET requests to the known malicious domain 'docsportal.in' attempting to retrieve second-stage payloads such as '161.php' or 'com.hta'. This pattern is associated with the SideCopy threat actor's malware delivery infrastructure.
Detects outbound network connections to common TOR entry, guard, or client service ports, or the execution of TOR-related processes. This behavior may indicate an adversary establishing C2 communication channels or attempting to perform anonymized data exfiltration.
Detects network traffic matching the default HTTP check-in pattern of Mythic C2 agents. This rule monitors for POST requests using a specific hardcoded User-Agent string and Content-Type header commonly used in default Mythic agent configurations, indicating a potential active command-and-control session.
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 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 performs a multi-source correlation (network, DNS, file, and process telemetry) to detect artifacts associated with the Coruna campaign. It looks for known malicious file hashes (SHA1), C2 IP addresses, and specific domain/URL patterns in process command lines and network connections.
This rule detects Node.js, NPM, or Yarn processes initiating network connections to common Ethereum JSON-RPC providers such as Infura and Alchemy. This activity, when originating from processes not associated with known development directories (like hardhat, truffle, or web3 projects), may indicate malicious use of build tools for blockchain-based command and control (C2) or unauthorized data exfiltration via RPC endpoints.
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 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 potential browser-based credential and session theft by monitoring for a process that accesses multiple sensitive web browser artifacts (cookies, local state, session storage) across several user profiles in a short timeframe. It correlates this activity with the subsequent creation of a compressed archive in a temporary directory followed by an outbound network connection, indicating a multi-stage exfiltration workflow.
Detects the suspicious combination of a file modification within Magento frontend or checkout JavaScript/template directories followed by an outbound network connection initiated by web server processes (e.g., Apache, Nginx, PHP). This pattern is consistent with the injection of a digital skimmer (e.g., Magecart style) and the subsequent exfiltration of stolen payment card data to an attacker-controlled endpoint.
This rule monitors for known malicious file hashes, command and control (C2) domains, and specific download URLs associated with identified threats. It correlates these indicators across process execution, file activity, and network connection logs to identify potential compromises or malicious activity related to the aware-cr1 infrastructure.
This rule detects known-malicious activity associated with Warlock ransomware and the ToolShell malware campaign (linked to Storm-2603). It monitors for process, file, and image-load events matching identified malicious file hashes, as well as network connection attempts to known malicious domains and URLs. It also includes monitoring for traffic to 'oastify.com', a domain commonly used for Burp Collaborator, which requires correlation with other indicators to confirm malicious intent.
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 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.
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