Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
79 detections
Filters
Last updated
All Time
Detection languages
40
20
9
7
1
Contributors
40
16
14
3
2
Categories
22
14
13
12
11
Platforms
46
24
15
4
2
Products / Services
10,650
9,755
6,688
4,418
3,745
MITRE Techniques
26
25
14
11
11
CVEs
1
1
1
1
1
IDS Classtypes
6
2
1
IDS Protocols
8
1
Detects malicious activities associated with the SilkParasite campaign targeting Redis servers. The rules identify the initiation of a 'SLAVEOF' command to a rogue replication host, subsequent handshake (PSYNC/REPLCONF) with an external attacker-controlled node, and the modification of server configuration ('CONFIG SET dbfilename') to potentially facilitate unauthorized file persistence or data exfiltration through the Redis replication mechanism.
Detects malicious activities associated with the SilkParasite campaign targeting Redis servers. The rules identify the initiation of a 'SLAVEOF' command to a rogue replication host, subsequent handshake (PSYNC/REPLCONF) with an external attacker-controlled node, and the modification of server configuration ('CONFIG SET dbfilename') to potentially facilitate unauthorized file persistence or data exfiltration through the Redis replication mechanism.
This rule detects the creation of cron jobs in /etc/cron.d/ that are associated with known miner file names (e.g., redis-miner, xminer). It explicitly looks for instances where the initiating process or its parent process is associated with Redis, suggesting a compromise or exploitation of a Redis service to establish persistence for a crypto miner.
This rule detects the creation of cron jobs in /etc/cron.d/ that are associated with known miner file names (e.g., redis-miner, xminer). It explicitly looks for instances where the initiating process or its parent process is associated with Redis, suggesting a compromise or exploitation of a Redis service to establish persistence for a crypto miner.
This rule detects a high volume of inbound network connection attempts to the default Redis port (6379) originating from local loopback or local host addresses, excluding known legitimate Redis and web server processes. This activity is indicative of potential unauthorized access attempts or exploitation of local Redis instances.
This rule detects a high volume of inbound network connection attempts to the default Redis port (6379) originating from local loopback or local host addresses, excluding known legitimate Redis and web server processes. This activity is indicative of potential unauthorized access attempts or exploitation of local Redis instances.
This rule detects a high volume of inbound network connection attempts to the default Redis port (6379) originating from local loopback or local host addresses, excluding known legitimate Redis and web server processes. This activity is indicative of potential unauthorized access attempts or exploitation of local Redis instances.
This rule detects a high volume of inbound network connection attempts to the default Redis port (6379) originating from local loopback or local host addresses, excluding known legitimate Redis and web server processes. This activity is indicative of potential unauthorized access attempts or exploitation of local Redis instances.
This rule detects a high volume of inbound network connection attempts to the default Redis port (6379) originating from local loopback or local host addresses, excluding known legitimate Redis and web server processes. This activity is indicative of potential unauthorized access attempts or exploitation of local Redis instances.
This rule detects potentially unauthorized content injection within Redis or Memcached application logs. It monitors for specific keywords indicating WordPress post data ('WP_Post') being processed by these caching services, which is often an indicator of object injection or application-level exploitation attempts aimed at manipulating application data.
Detects anomalous Redis network traffic containing structures associated with GigaWiper, specifically monitoring for 'cmd.Result' fields used by the malware to exfiltrate command output from compromised systems to a C2 server.
Detects anomalous Redis network traffic containing structures associated with GigaWiper, specifically monitoring for 'cmd.Result' fields used by the malware to exfiltrate command output from compromised systems to a C2 server.
Detects anomalous Redis network traffic containing structures associated with GigaWiper, specifically monitoring for 'cmd.Result' fields used by the malware to exfiltrate command output from compromised systems to a C2 server.
Detects post-exploitation activities related to the PHP 8.5.7 CVE-2025-15661 StreamBucket SOAP vulnerability. This rule monitors for PHP worker processes spawning shells, writing executable files to suspicious directories, executing system binaries on Windows, or initiating outbound network connections on non-standard ports, including specific proof-of-concept markers.
This rule detects network connections to common messaging and data store ports (RabbitMQ, Redis, MinIO) initiated by PowerShell, redis-cli, or minio.exe, where the process command line also contains the string "encrypt". This combination suggests potential malicious activity such as data encryption by ransomware or other malware targeting these services.
This rule detects network connections to common messaging and data store ports (RabbitMQ, Redis, MinIO) initiated by PowerShell, redis-cli, or minio.exe, where the process command line also contains the string "encrypt". This combination suggests potential malicious activity such as data encryption by ransomware or other malware targeting these services.
The following analytic detects the use of default or publicly known named pipes associated with Cobalt Strike. It leverages Sysmon EventID 17 and 18 to identify specific named pipes commonly used by Cobalt Strike's Artifact Kit and Malleable C2 Profiles. This activity is significant because Cobalt Strike is a popular tool for adversaries to conduct post-exploitation tasks, and identifying its named pipes can reveal potential malicious activity. If confirmed malicious, this could indicate an active Cobalt Strike beacon, leading to unauthorized access, data exfiltration, or further lateral movement within the network.
This analytic detects suspicious data transfer activities involving the use of the `split` syscall with the `-b` option, which specifies the size of each output file. This technique can be used by attackers to evade detection by breaking large files into smaller parts, bypassing size-based security controls, and facilitating covert exfiltration of sensitive data. By monitoring for unusual or unauthorized use of the `split` syscall with a specified block size, this analytic helps identify potential data exfiltration attempts.
This analytic identifies the bulk creation of ransomware notes (e.g., .txt, .html, .hta files) on an infected machine. It leverages Sysmon EventCode 11 to detect multiple instances of these file types being created within a short time frame (10 seconds). A detection is triggered if 15 or more unique readme paths are observed. This activity is a strong indicator of an active ransomware attack, where the attacker is notifying the victim of the encryption. If confirmed malicious, this behavior could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
The following analytic detects suspicious attempts to find credentials stored in password stores, indicating a potential attacker's effort to access sensitive login information. Password stores are critical repositories that contain valuable credentials, and unauthorized access to them can lead to significant security breaches. By monitoring for unusual or unauthorized activities related to password store access, this analytic helps identify potential credential theft attempts, allowing security teams to respond promptly and prevent unauthorized access to critical systems and data.
The following analytic identifies the execution of RAR utilities to archive files on a system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, GUIDs, and command-line arguments. This activity is significant as threat actors, including red-teamers and malware like DarkGate, use RAR archiving to compress and exfiltrate collected data from compromised hosts. If confirmed malicious, this behavior could lead to the unauthorized transfer of sensitive information to command and control servers, posing a severe risk to data confidentiality and integrity.
Page 2 of 4




