Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the creation of specific RabbitMQ AMQP exchanges and bindings often associated with C2 communication patterns, such as the use of 'fanout' or 'topic' exchange types paired with common internal naming conventions or payload keywords.
Detects the creation of specific RabbitMQ AMQP exchanges and bindings often associated with C2 communication patterns, such as the use of 'fanout' or 'topic' exchange types paired with common internal naming conventions or payload keywords.
Detects outbound network traffic containing the string 'Secret: ', which indicates potential sensitive data exfiltration. The rule specifically targets the use of netcat-like behavior directed toward external endpoints, which are commonly associated with tunneling services like ngrok used to bypass network egress restrictions.
Detects outbound web requests to OpenAI, Anthropic, or Google Gemini API endpoints that contain suspected API keys (OpenAI 'sk-proj-', Anthropic 'sk-ant-', or Google 'AIza' prefixes) in the request stream, potentially indicating hardcoded credentials, malicious script activity, or data exfiltration.
This rule identifies endpoints that have transferred a total of more than 50MB of data to a single external, non-private IP address. The detection filters out RFC1918 private subnets and local loopback traffic, aggregating byte counts and connection attempts per endpoint, computer, and destination. This is indicative of potential data staging or exfiltration activities.
Detects large outbound network transmissions occurring on a host shortly after the creation of staged or archive files. This behavior is indicative of an attacker consolidating sensitive data (such as credentials or intelligence) into an archive and subsequently exfiltrating it over a Command and Control (C2) or other established network channel.
Detects periodic, low-variance network beaconing behavior indicative of the SnappyClient RAT, specifically monitoring for simultaneous connections to control (port 3333) and data (port 3334) ports. The detection utilizes statistical analysis of inter-arrival times (low coefficient of variation) and restricts alerts to rare destination IP addresses contacted by a limited number of internal hosts.
This rule detects potentially malicious network traffic that suggests command and control or data exfiltration. It identifies connections using non-standard ports (above 1024, excluding common ports) or abnormally long DNS queries, often associated with DNS tunneling. The rule aggregates these events by host and destination to identify persistent or high-volume patterns indicative of covert channels.
Detects the execution of 'FortiGateSniffer', a tool identified as Golang-based, used to perform passive network packet capture on compromised FortiGate devices. The rule also analyzes captured traffic for sensitive authentication protocols including RADIUS, Kerberos, and NTLM.
Detects unusually large outbound network data transfers (over 1TB) from a single process account within an hour. This could indicate data exfiltration, unauthorized bulk data synchronization, or other malicious activity where large volumes of data are being moved out of the environment.
Detects a specific network handshake pattern indicative of the Cavern Manticore malware establishing a SOCKS5-over-WebSocket tunnel. The rule monitors for a WebSocket upgrade request followed by the initial SOCKS5 connection authentication byte sequence.
Detects an unusually large data transfer (greater than 5MB) from an internal MySQL server to an external network, which may indicate unauthorized database record exfiltration or data dumping.
Detects outbound network communication to an IP address (64.20.53.230) identified as a staging server associated with the JadePuffer activity. This activity involves potential data exfiltration following self-narrated deletion payloads.
Detects high-volume data access or exfiltration from Azure/Office 365 cloud environments via common scripting/automation user-agents. The rule monitors API requests to users, mail, drive, or files endpoints by non-standard clients (e.g., python, curl, Go) from previously unseen locations, calculating a risk score based on the number of endpoints accessed and the total data volume.
This rule detects suspicious large file transfers over the network, specifically looking for connections where more than 100MB (104857600 bytes) of data has been sent or received. It then aggregates these transfers by device and remote IP within one-hour bins and flags if five or more such large transfers occur within that hour. This behavior can be indicative of data exfiltration, often associated with ransomware attacks or other malicious data theft activities.
Detects high-volume outbound network connections (exceeding 10MB) originating from processes associated with AI-driven chatbot or productivity applications (e.g., ChatGPT, Perplexity). This rule identifies potential data exfiltration occurring over legitimate, expected software channels.
Detects anomalous ICMP Echo Request packets (Type 8) directed towards external networks that contain a payload size greater than 128 bytes. Such anomalies are often indicative of ICMP tunneling, which may be leveraged by adversaries for command and control (C2) communication or data exfiltration.
Detects high volume HTTPS outbound traffic (greater than 50MB within a 5-minute window) from a host that does not show evidence of preceding file encryption or volume shadow copy deletion activity. This rule is designed to identify potential unauthorized data exfiltration that deviates from typical ransomware-associated behavior patterns.
Detects anomalous ICMP Echo Request packets (type 8, code 0) that contain payloads exceeding 64 bytes. ICMP Echo requests with large, non-standard payloads are a classic indicator of ICMP tunneling, which can be used to bypass network firewalls and encapsulate non-ICMP traffic for command and control (C2) or data exfiltration. The rule includes a threshold to reduce noise by alerting only when multiple such packets are seen from the same source.
Detects network activity over port 1313 containing Socket.IO payloads with keywords 'control' and 'escape', indicative of a command and control or remote access channel often associated with interactive shells or administrative backdoors.
This rule identifies potential Command and Control (C2) beaconing activity by detecting recurring, consistent HTTP(S) requests from internal hosts to unknown or newly seen external destinations, characterized by stable time intervals and low variance in response sizes. The detection logic filters out common User-Agents, indicating non-browser or automated traffic often associated with malware communication.
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