Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

2,303 detections

This rule detects potential command and control (C2) activity related to the Qakbot malware. It specifically monitors for established outbound TLS traffic over non-standard ports (ports other than 443) where the Server Name Indication (SNI) field contains a numeric IPv4 address instead of a domain name, which is a characteristic behavior of Qakbot C2 infrastructure.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects TLS/SSL traffic patterns characteristic of Metasploit Meterpreter reverse HTTPS command-and-control communication, specifically targeting the use of default, self-signed certificates with a subject line containing a bare wildcard (CN=*) in the common name field, a common artifact of unconfigured Metasploit payloads.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects inbound HTTP requests containing common Cross-Site Scripting (XSS) patterns, such as the <script> HTML tag or the 'javascript:' URI scheme, which are indicative of attempts to execute arbitrary client-side code.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
This rule detects repeated path traversal sequences (../ or ..%2F) in the HTTP URI. This behavior is indicative of an attacker attempting to escape the intended web directory to access sensitive files or configuration files on the underlying filesystem.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects outbound HTTP POST requests characterized by a specific URL pattern consisting of two segments of 4-16 alphanumeric characters, typically observed in Emotet C2 traffic. The rule specifically matches requests with a Content-Type header set to application/octet-stream, which is indicative of malicious binary payload transfer or communication.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
This rule detects network traffic originating from internal hosts to external destinations consistent with default Cobalt Strike HTTP Beacon communication patterns. It specifically looks for GET requests containing URI paths commonly associated with default Cobalt Strike profiles (ca, submit.php, updates.rss) combined with a specific, hardcoded User-Agent string associated with Cobalt Strike's default configuration.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
This rule monitors incoming DNS traffic for A record responses containing RFC1918 private IP addresses (10.0.0.0/8, 172.16.0.0/12, or 192.168.0.0/16). This behavior is characteristic of DNS rebinding attacks, where a malicious web service resolves to a victim's internal network address to bypass browser same-origin policies.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects the transmission of the 'UserInitMprLogonScript' registry value name over SMB traffic in plaintext. This registry key is commonly used by adversaries to establish persistence by executing a logon script whenever a user logs in.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects attempts to disable the Windows Firewall using the netsh command-line utility or PowerShell cmdlets, as well as registry modifications related to firewall profiles. Adversaries often perform this action to impair host-based security controls and facilitate unauthorized inbound or outbound network traffic.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
This rule detects suspicious HTTP request bodies containing the 'LD_PRELOAD' environment variable assignment, targeting common temporary or writable directories. This behavior is indicative of an attempt to perform dynamic linker hijacking on a Linux system to inject malicious shared libraries into target processes.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects DNS queries for 14-character alphanumeric .org domains characteristic of Bumblebee malware's Domain Generation Algorithm (DGA).
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Duo Tech@duotech
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Detections.ai Community
4 months ago
000
Detects outbound HTTP requests exhibiting a User-Agent string hardcoded to mimic Firefox 20.0 (Mozilla/5.0 (Windows NT 6.2; rv:20.0) Gecko/20121202 Firefox/20.0), which is characteristic of the Adaptix C2 framework. This pattern is commonly used by adversaries for command-and-control communication.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
000
Detects network traffic associated with known Cobalt Strike Beacon request URI patterns. This rule utilizes network signature inspection to flag outbound connections containing URI fragments commonly used by Cobalt Strike default profiles.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Detects network traffic associated with known Cobalt Strike Beacon request URI patterns. This rule utilizes network signature inspection to flag outbound connections containing URI fragments commonly used by Cobalt Strike default profiles.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
001
This rule detects a high volume of HTTP POST requests to known SMS API providers (Twilio, Nexmo, Vonage) from a single source IP address within a short timeframe. This pattern is indicative of a 'pumping attack' or SMS fraud, where an attacker attempts to generate a large number of SMS messages, often to premium rate numbers, to incur charges or exploit vulnerabilities in billing systems. The threshold is set to 20 requests within 60 seconds from the same source.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
0010
This rule detects potential bandwidth hijacking activity associated with peer-to-peer botnet traffic. It triggers an alert when a high volume of TCP traffic (more than 200 packets within 60 seconds) with a packet size greater than 1000 bytes is observed originating from the home network to any destination. The 'flow:to_server,established' indicates that the rule is looking for established connections where the traffic is flowing from the internal network to an external server. The 'threshold' keyword ensures that only sustained high-volume traffic triggers the alert, reducing noise from legitimate, short bursts of activity. The 'classtype:policy-violation' suggests that this activity is considered a violation of network usage policies.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
0010
This rule detects a potential HTTP POST flood Distributed Denial of Service (DDoS) attack. It triggers an alert when a single source IP address sends 100 or more HTTP POST requests to the server within a 10-second window. This behavior is indicative of an attempt to overwhelm the server with requests, consuming resources and potentially leading to service disruption.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
0012
This rule detects NTP Reflection Amplification DDoS attacks by looking for specific content in UDP packets destined for the home network on port 123 (NTP). The rule triggers if 50 such packets are observed from the same destination within 5 seconds, indicating a high volume of NTP traffic potentially used for amplification.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
007
This rule detects a potential DNS Reflection Amplification Distributed Denial of Service (DDoS) attack. It triggers an alert when UDP traffic targeting port 53 (DNS) on the home network has a data size greater than 512 bytes and occurs at a rate of 100 or more packets within a 5-second window from the same destination.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
007
This rule detects a direct ICMP Flood Denial of Service (DoS) attack. It triggers when more than 500 ICMP echo request (type 8) packets are sent to a single destination within a 5-second interval. This high volume of ICMP traffic is characteristic of an attempt to overwhelm a target system or network with ping requests, leading to service disruption.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
007
This rule detects network traffic on TCP port 445 (SMB) containing the strings "Winlogon" and "Userinit" (case-insensitive). This pattern is indicative of a potential modification to the Winlogon Helper DLL for persistence, as Winlogon and Userinit are key components in the Windows logon process. An attacker might modify a helper DLL to execute malicious code during system startup.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
008
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