Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
219 detections
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Detects SMB traffic targeting the IPC$ share within the internal network, which is a common behavior of PIVOTPIPE lateral movement techniques using SMB named pipes for peer-to-peer (P2P) beacon communication.
Detects a sequence of Tox P2P protocol packets consisting of a Cookie Request, Cookie Response, and Crypto Handshake within a single network flow. This pattern is indicative of the Tox P2P protocol, which is sometimes abused by malware (e.g., AvisLoader) for command-and-control (C2) communications to evade traditional network inspection.
This rule detects network traffic patterns indicative of Xray-core C2 tunnels using a spoofed 'dl.google.com' TLS SNI value. This activity is associated with the Aur0ra/Black Basta playbook, where Xray-core is sideloaded into legitimate processes to exfiltrate or tunnel traffic while mimicking Chrome browser TLS behavior.
This rule identifies network connections or event logs originating from known residential and anonymous proxy providers, including Nodemaven, DataImpulse, Luminati (Bright Data), ProxyRack, Shifter, SOAX, and Yilu. Adversaries frequently use these proxy services to mask their true origin, evade IP-based geolocation blocks, and conduct malicious activity while blending in with legitimate traffic.
Detects a specific network handshake pattern characterized by the string 'REVERSE_PROXY|' within the first 16 bytes of an established TCP connection, consistent with the x47.c Fast-Flux botnet command and control (C2) communication protocol.
Detects PIVOTPIPE malware beaconing activity indicative of peer-to-peer (P2P) lateral movement between internal hosts. The rule monitors for sustained established TCP traffic with specific small packet size characteristics, suggesting command-and-control heartbeats or tunneled traffic within the internal network.
Detects network beaconing activity associated with the Sauron Loader malware. The rule monitors HTTPS traffic for specific domain patterns and suspicious TLV (Type-Length-Value) protocol structures, as well as recurring beaconing cadence to identified C2 infrastructure.
This analytic identifies instances where an internal host has attempted to communicate with 250 or more destination IP addresses using on of the NMAP top 20 ports. Horizontal port scans from internal hosts can indicate reconnaissance or scanning activities, potentially signaling malicious intent or misconfiguration. By monitoring network traffic logs, this detection helps detect and respond to such behavior promptly, enhancing network security and preventing potential threats.
This rule monitors outbound network traffic for the inclusion of a Windows-style hostname pattern (e.g., 'DESKTOP-XXXXXX'), which is often used by stealer malware or RATs to identify victim machines during C2 communication. It explicitly excludes Microsoft licensing traffic to reduce false positives.
Detects network traffic associated with PIVOTPIPE Cobalt Strike beacon activity communicating with a known suspicious external IP address on port 8088. This includes generic TCP, HTTP-based beaconing, and TLS-encrypted C2 sessions.
Detects sustained outbound TCP communication patterns indicative of Xray-core proxy or tunneling activity. The rule monitors for high-frequency established TCP sessions originating from the internal network, which is a common behavior for tools used to maintain persistent network tunnels or proxy command-and-control traffic.
Detects a sequence of Tox P2P protocol packets consisting of a Cookie Request, Cookie Response, and Crypto Handshake within a single network flow. This pattern is indicative of the Tox P2P protocol, which is sometimes abused by malware (e.g., AvisLoader) for command-and-control (C2) communications to evade traditional network inspection.
Detects a sequence of Tox P2P protocol packets consisting of a Cookie Request, Cookie Response, and Crypto Handshake within a single network flow. This pattern is indicative of the Tox P2P protocol, which is sometimes abused by malware (e.g., AvisLoader) for command-and-control (C2) communications to evade traditional network inspection.
Detects high-volume POST requests containing HEIF, HEIC, or AVIF image content types, indicative of automated fuzzing or exploitation attempts against an image-processing endpoint targeting CVE-2026-32882.
In DeviceNetworkEvents, we can find both JA4 and JA4S inside AdditionalFields for some TLS connections. This is interesting because we can look at both sides of the same TLS communication. We can compare clients, servers and JA4/JA4S combinations, and look for patterns or connections that behave differently from what we normally see. The following KQL extracts and decodes both fingerprints from the same network event.
Detects periodic outbound network connections (beaconing) to rare remote destinations initiated by processes running from non-standard or user-writable locations. The rule calculates the interval coefficient of variation (CV) between successful connections to identify regular, consistent patterns indicative of command and control communication while excluding known legitimate update and service traffic.
Detects network communications between internal hosts and known malicious infrastructure associated with SpiceRAT, including TLS-based command channels and HTTP requests for decoy pages.
This rule detects network traffic indicative of N0va Phishkit verification or session initialization. It looks for specific GET request URI parameters (/api/verification/init?session=, flow=, prompt_profile=) that align with the initial handshake phase of this phishing kit, which is often used for credential and session cookie theft.
This rule monitors network and event logs to detect instances where a single user account, logged into a specific host, initiates connections to two or more distinct, potentially suspicious remote IP addresses. This pattern of multi-destination connection activity may indicate command and control communication, scanning behavior, or data staging.
Detects high-volume POST requests containing HEIF, HEIC, or AVIF image content types, indicative of automated fuzzing or exploitation attempts against an image-processing endpoint targeting CVE-2026-32882.
Detects high-volume POST requests containing HEIF, HEIC, or AVIF image content types, indicative of automated fuzzing or exploitation attempts against an image-processing endpoint targeting CVE-2026-32882.
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