Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects network activity associated with the DragonForce backdoor, specifically the use of MQTT for command and control. The rules monitor for unique 16-character client IDs used during registration on non-standard ports, subsequent command retrieval structures containing 'cmdnum', and DNS queries for the hardcoded broker 'broker.emqx.io'.
Detects network activity associated with the DragonForce backdoor, specifically the use of MQTT for command and control. The rules monitor for unique 16-character client IDs used during registration on non-standard ports, subsequent command retrieval structures containing 'cmdnum', and DNS queries for the hardcoded broker 'broker.emqx.io'.
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 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.
Detects DNS queries originating from NetScaler appliances that exhibit algorithmically generated domain (DGA) characteristics or utilize top-level domains (TLDs) frequently associated with malicious command and control infrastructure. This rule aims to identify potential post-exploitation C2 communication following a compromise of a NetScaler ADC or Gateway appliance.
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 network traffic directed towards known public DNS over HTTPS (DoH) resolvers, such as Cloudflare, Google, and Quad9. Adversaries often abuse DoH to tunnel Command and Control (C2) communication, effectively blending in with legitimate web traffic to evade traditional DNS monitoring.
Detects anomalous network behavior where a source host initiates a high volume of DNS TXT record queries to an external domain within a short timeframe. Such patterns are indicative of data exfiltration or C2 communication tunneling through DNS protocol.
This rule detects potential DNS tunneling or DNS-based command and control (C2) beaconing. It analyzes DNS query logs for characteristics typical of C2 traffic, such as high subdomain entropy, frequent use of TXT or NULL records, and a high volume of unique subdomains originating from a single source IP address within a 5-minute window.
This rule performs a retrospective sweep for indicators of compromise (IOCs) associated with the 'CSuite' phishing and RMM (Remote Monitoring and Management) campaign. It monitors network, DNS, proxy, email, URL click, and file creation telemetry over the past 24 hours to identify interactions with known-malicious IP addresses, domains, URLs, and file hashes related to the campaign.
This rule performs a retrospective sweep for indicators of compromise (IOCs) associated with the 'CSuite' phishing and RMM (Remote Monitoring and Management) campaign. It monitors network, DNS, proxy, email, URL click, and file creation telemetry over the past 24 hours to identify interactions with known-malicious IP addresses, domains, URLs, and file hashes related to the campaign.
This rule monitors network traffic, DNS queries, and user web clicks to detect interactions with known malicious domains associated with credential harvesting and phishing campaigns, specifically those impersonating security or SSO portals.
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
This rule detects various malicious indicators of compromise (IOCs) across multiple telemetry sources, including DNS queries, web network traffic, file executions, process creation, and email activity. It monitors for interactions with known malicious domains, URLs, file hashes, and specific sender email addresses to identify potential malware distribution or C2 activity.
IOC hunt across DNS, network, and file-hash telemetry for the Ledger Google Ads phishing campaign. Vercel redirect domains are matched by exact hostname (DNS query name / parsed URL host) rather than substring, eliminating false positives from unrelated strings that merely contain a look-alike domain fragment. GCS bucket and Google Sites path IOCs remain substring-matched since the bucket IDs and page slugs are already highly specific.
Detects DNS query activity from processes commonly used as AI agent runtimes (e.g., python.exe, node.exe) toward domains characterized by DGA-like patterns, such as long alphanumeric strings or high-consonant density, which may indicate command-and-control communication.
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.
This rule detects potentially malicious Command and Control (C2) traffic utilizing DNS over HTTPS (DoH) to interact with public resolvers like Cloudflare, Google, and Quad9. It identifies both high-frequency, repeated direct-to-resolver TLS sessions and specific HTTP requests to these resolvers that resolve domains associated with known C2 infrastructure, such as the ClickFix campaign.
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