Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,139 detections
Filters
Last updated
All Time
Detection languages
3,217
1,086
504
478
469
Contributors
1,824
1,607
872
505
300
Categories
2,971
2,471
1,060
1,026
908
Platforms
39,762
7,139
6,517
3,851
3,599
Products / Services
1,324
1,067
970
657
487
MITRE Techniques
2,228
1,317
1,314
873
871
CVEs
66
65
33
32
28
IDS Classtypes
81
80
56
27
10
IDS Protocols
149
98
6
5
4
Detects suspicious child processes spawned from AutoGen Studio or mcp.py Python processes, which could indicate a WebSocket command injection vulnerability (AutoJack - CWE-78). The rule looks for common shell or command execution binaries and keywords in the process command line.
Detects attempts to restore or extract files containing path traversal characters ('../' or '..\') commonly associated with the ZipSlip vulnerability. This technique was utilized in Operation Escaneo (via the mkzip34.py tool) to deploy webshells automatically upon legitimate archive restoration. The rule specifically looks for file creation or modification events where the initiating process is a common archive extraction tool (unzip, tar) or a Java application server (java, tomcat), the file extension is for a Java web application (.jsp, .jspx), and the resulting folder path contains path traversal sequences.
Detects vLLM establishing outbound network connections to fetch external media files (e.g., .mov, .mp4, .jp2) from non-private IP addresses. This activity may indicate exploitation of CVE-2026-22778, allowing for remote code execution by fetching malicious content.
Detects workstations establishing multiple connections to non-standard, internal management ports (SSH, Telnet, SNMP). This behavior is often associated with lateral movement or unauthorized network scanning using tools that leverage management protocols.
This rule monitors Cisco Unified Communications Manager (UCM) environments for multiple stages of an attack chain, including potential Server-Side Request Forgery (SSRF) attempts against administrative interfaces, suspicious file modifications by service accounts, indicators of privilege escalation, and anomalous outbound network connections from core Cisco processes.
This rule detects the presence and execution of known FortiBleed malware components based on their filenames and SHA256 hashes. It monitors both process creation events and file events to identify the malware.
This rule detects the presence and execution of known FortiBleed malware components based on their filenames and SHA256 hashes. It monitors both process creation events and file events to identify the malware.
Detects a shell script containing 'fanout' in its name, created or modified in common temporary directories like /tmp or /var/tmp, matching a reported propagation workflow. This activity is indicative of lateral movement attempts.
Detects Python or Node.js processes executing command-line interpreters (e.g., cmd.exe, bash) while simultaneously performing network connections. This behavior is indicative of a post-exploitation activity where an attacker leverages language-specific package paths to execute shell commands and establish command-and-control communication.
This rule detects suspicious command execution patterns on Linux systems that could indicate an adversary attempting to execute arbitrary commands or escalate privileges. It looks for specific command-line arguments used with common utilities like `find`, `vim`, `python`, `perl`, `bash`, `awk`, and `cp` that are often abused for malicious purposes. The rule also excludes processes commonly associated with legitimate system automation to reduce false positives.
This rule detects the creation, modification, or renaming of the `authorized_keys` file within the `.ssh` directory by processes other than common SSH key management or shell utilities. This activity could indicate an adversary attempting to establish persistence or elevate privileges by adding their own public key for SSH access.
This rule detects various methods of establishing a reverse shell on Linux systems. It looks for process creation events involving common shell interpreters (bash, sh) attempting to connect to network devices via /dev/tcp or /dev/udp. It also identifies the use of network utilities like netcat (nc, ncat, netcat, nc.traditional) and socat when used with command execution flags (-e, -c, EXEC) and shell interpreters. Additionally, it flags direct outbound network connections initiated by these shell interpreters or network utilities, which could indicate a reverse shell communication channel.
This rule detects the creation, modification, or renaming of the `authorized_keys` file within the `.ssh` directory by processes other than common SSH key management or shell utilities. This activity could indicate an adversary attempting to establish persistence or elevate privileges by adding their own public key for SSH access.
This rule detects suspicious command execution patterns on Linux systems that could indicate an adversary attempting to execute arbitrary commands or escalate privileges. It looks for specific command-line arguments used with common utilities like `find`, `vim`, `python`, `perl`, `bash`, `awk`, and `cp` that are often abused for malicious purposes. The rule also excludes processes commonly associated with legitimate system automation to reduce false positives.
Detects Python loading a .pyd or .so extension from common user-controlled directories like AppData, Temp, Downloads, or project directories, rather than from a trusted package installation. This behavior is indicative of the InvisibleFerret malware.
This rule detects the use of 'curl' to perform HTTP PUT requests with binary data, a technique often employed by malware like Amos Stealer for data exfiltration. It specifically looks for command-line arguments '-X', 'PUT', and '--data-binary' in 'curl' process executions.
This rule detects the execution of iptables or xtables commands to create a network redirection rule. Specifically, it looks for commands that use 'REDIRECT', '--to-ports', and either 'PREROUTING' or 'nat' in the command line, indicating an attempt to redirect network traffic, potentially for proxying or other malicious network manipulation.
This rule detects potentially malicious software supply chain attacks by identifying suspicious child processes spawned by package managers (pip, npm) or Python scripting engines within a short timeframe. It specifically looks for shells (cmd, powershell, bash, etc.) being invoked immediately after a package installation or script execution, and correlates this activity with suspicious outbound network connections originating from these processes.
Detects BPFDoor-style iptables NAT REDIRECT rules used to tunnel traffic from a
legitimate service port to a high ephemeral shell port (42391-43390) without
disrupting the real service for other clients. BPFDoor activates on magic packets, spawns a
bind shell, inserts short-lived PREROUTING redirects for the controller IP, then deletes them.
legitimate service port to a high ephemeral shell port (42391-43390) without
disrupting the real service for other clients. BPFDoor activates on magic packets, spawns a
bind shell, inserts short-lived PREROUTING redirects for the controller IP, then deletes them.
Detects fileless Linux malware execution patterns that run payloads from anonymous memory files (memfd_create) or inherited file descriptors under /proc/self/fd without touching disk. Used by Linux backdoors and miners to evade filesystem-based detection.
Detects shell/script execution from .git/hooks/ paths, especially when spawning network-connected or unusual child processes. This activity is indicative of Lazarus Group exploiting Git Hooks for persistence and credential theft within developer environments.
Page 238 of 340