Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects unauthorized write, modification, or rename operations within Linux Pluggable Authentication Module (PAM) directories (/lib/security, /lib64/security, /usr/lib/security, /etc/pam.d). The rule identifies activity performed by processes that are not recognized package managers (e.g., apt, yum, dpkg), which is a common technique used by threat actors to inject malicious authentication modules or backdoors (e.g., pam_unix.so replacement) to hijack authentication processes.
Detects potential SSRF or local file read attempts by identifying requests to sensitive system or application file paths (e.g., /proc/self/environ, /etc/passwd) that result in an unusually large response body compared to the historical baseline for that endpoint.
Detects incoming HTTP requests that use URL-encoding (e.g., %2e%2e, %2f) to obfuscate path traversal sequences targeting sensitive operating system or container application files, such as /proc/self/environ or /etc/passwd. This technique is often used to bypass security filters or URL validation mechanisms in web applications.
Detects the creation or modification of shared object (.so) files within critical Linux PAM library directories (/lib/security/, /lib64/security/, /usr/lib/security/) by processes other than identified system package managers. This behavior is indicative of an adversary replacing legitimate authentication modules with malicious versions to capture credentials or establish persistence, such as the activity documented in Operation Highland (Velvet Ant).
Detects the execution of Perl-based SOCKS proxy tunneling activity on Linux systems, as observed in Velvet Ant operations. The rule identifies Perl processes that contain socket/fork/daemonization indicators when spawned by web server processes like Nginx, Apache, or common shells used in CGI contexts, suggesting the exploitation of a web application to establish an internal network pivot.
This rule detects potential JDY botnet activity characterized by host fingerprinting and data exfiltration patterns. It looks for repeated POST requests to specific URI patterns ('/gate', '/report', '/scan') accompanied by a significant volume of outbound data, indicative of automated C2 communication or data staging. The rule aggregates metrics per host to identify high-volume exfiltration patterns and calculates a risk score based on the frequency of requests and the diversity of destination IPs.
Detects the execution of Python-based SMB server implementations commonly associated with the Impacket toolset. Impacket is frequently used by attackers to facilitate lateral movement, credential relay, and remote file manipulation.
Detects user-space processes masquerading as critical Linux kernel threads (kworker, kthreadd, ksoftirqd). The rule identifies potential impersonation by monitoring for suspicious parent processes (e.g., shells, interpreters), anomalous parent PIDs (not 1 or 2), or unexpected network socket activity generated by these kernel-named processes.
This rule identifies potential use of the Tor network by detecting network connections to common Tor relay ports (9001, 9030, 9050, 9051, 9150) that are external to internal subnets, or by identifying DNS requests for .onion domains.
Detects high-frequency POST requests originating from outside internal network ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16) that contain suspicious payloads in the request body (such as shell commands, downloading utilities, or busybox) or target common CGI-BIN paths, indicating a potential attempt to exploit a public-facing web server.
This rule detects the execution of common Python-based network relay and exploitation tools such as Impacket's ntlmrelayx, smbserver.py, and PetitPotam. These tools are frequently utilized by adversaries to conduct NTLM relay attacks, perform remote service execution, or facilitate credential dumping.
Detects network connection attempts directed toward RFC 1918 private IP address spaces (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16) and localhost (127.0.0.0/8) that do not involve common Windows file sharing ports (TCP/445 and TCP/139). This behavior may indicate lateral movement, internal reconnaissance, or the use of non-standard protocols for internal communication.
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 path traversal attempts in web server access logs by searching for dot-dot-slash (../), dot-dot-backslash (..\), or their URL-encoded equivalents (..). These patterns are indicative of efforts to access files or directories outside the intended web root.
Detects instances where common web server processes initiate command interpreters or system utilities. This behavior is a common indicator of web shell execution, where an adversary uses a web application vulnerability to gain remote code execution on the underlying server.
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.
Detects multiple failed SSH authentication attempts against a server from a single source within a short timeframe, which is indicative of a brute force password attack.
Detects incoming HTTP POST requests directed at PHP, ASPX, or JSP files that contain suspicious command execution patterns (such as cmd=, exec=, system(, or eval()). This behavior is highly indicative of an attacker interacting with a web shell to execute unauthorized commands on the server.
Detects repeated SSH connection attempts to a server over a short duration (10+ attempts in 60 seconds), which is characteristic of credential stuffing or brute-force password guessing attacks against the SSH service.
Detects multiple TCP connection attempts to port 22 (SSH) from the same source within a 60-second window, which is indicative of a brute-force or password guessing attack against SSH services.
Detects multiple failed SSH authentication attempts originating from a single source IP within a short timeframe, which is indicative of a brute-force or credential-stuffing attack against SSH services.
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