Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,138 detections
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Detects the execution of suspicious child processes (e.g., cmd.exe, powershell.exe, bash, wget) spawned by processes associated with public-facing appliances like Fortinet SSL-VPN, Veeam Backup & Replication, Citrix ADC, and cPanel/WHM. This behavior is often indicative of exploitation of public-facing applications (T1190) for initial access, frequently associated with ransomware actors targeting unpatched infrastructure.
Detects the execution of suspicious child processes (e.g., cmd.exe, powershell.exe, bash, wget) spawned by processes associated with public-facing appliances like Fortinet SSL-VPN, Veeam Backup & Replication, Citrix ADC, and cPanel/WHM. This behavior is often indicative of exploitation of public-facing applications (T1190) for initial access, frequently associated with ransomware actors targeting unpatched infrastructure.
Detects the execution of rclone.exe or renamed binaries with command-line flags indicative of data exfiltration to cloud storage providers such as S3, Mega, OneDrive, or Google Drive. This behavior is frequently associated with ransomware actors, including Akira, Qilin, and Storm-2570, who use Rclone to perform mass exfiltration of sensitive file share data prior to encryption (double extortion).
Detects a multi-stage extortion tactic where a host is targeted by a mass creation of initial decryption-style ransom notes across multiple directories, followed by a subsequent drop of distinct follow-up 'press release' or 'threat' notes within a 30-minute window, indicative of INC Ransom behavior.
Detects usage of the 'gem' command (install, build, push, publish) that includes naming patterns or specific command strings associated with the GemStuffer supply chain compromise campaign. This targets attempts to introduce malicious dependencies into the environment using RubyGems.
Detects instances where a process attempts to delete its own executable file image shortly after being launched. This behavior is often associated with malware attempting to minimize its forensic footprint, such as self-deleting installers or RAT (Remote Access Trojan) components that move to a different location or execute from memory.
Detects a multi-stage loader execution chain, potentially named GHAPPIER, by identifying sequential stages of execution. These stages include initial marker file checks, shell-based command dispatching via curl/wget, renaming and execution of secondary payloads, Node.js-based runtime staging, and the eventual creation of implant artifacts in common paths such as VSCode extensions or hidden directories.
Detects the use of 'terraform init' where the command line arguments reference known typosquatted HashiCorp registry domains. This behavior is indicative of a supply chain attack attempting to pull malicious providers or modules from an adversary-controlled source.
Detects modifications to the .zshrc configuration file followed by shell commands interacting with the file, or the execution of commands that source the .repair-run script within a shell environment. This pattern is indicative of potential persistence mechanisms where an adversary modifies startup scripts to maintain access or execute malicious code upon shell initialization.
This rule detects modifications or creation of Git hooks ('pre-commit', 'post-checkout') within local repository directories. Attackers can leverage these hooks as an execution trigger for arbitrary code whenever standard Git actions occur, facilitating persistence or privilege escalation on compromised developer machines.
This rule identifies Linux-based devices that are vulnerable to specific security flaws tracked under CVE-2026-64507 and CVE-2026-64508. It correlates vulnerability assessment data with device inventory to highlight exposed systems.
Detects the execution of the 'sckit' Go-based implant when spawned by Node.js or Python processes using the command-line arguments 'stage0 --config64'. This pattern is associated with malicious npm and PyPI supply chain packages (memtensor) designed to harvest credentials and establish persistence.
Detects the SCKit Go-based credential-stealing implant found in compromised npm and PyPI packages. The detection logic focuses on unique build-info module paths, specific C2 encryption protocol headers, and embedded campaign identifiers related to 'memos-cloud-openclaw-plugin' and 'MemoryOS' supply chain compromises.
Detects the creation of files or directories under specific paths (/.openclaw/ and /.sckit/) used by the sckit Go-based worm. This worm, distributed via compromised npm and PyPI packages, uses these directories to track state and coordinate execution on infected Linux systems.
This rule monitors application, build system, and dependency scanning logs for references to known-malicious versions of the @memtensor/memos-cloud-openclaw-plugin (npm) and MemoryOS (PyPI) packages. These versions contain the sckit Go worm and are associated with automated supply chain attacks involving the reuse of stolen credentials, indicated by the 'exact-ref-one-use-NPM_TOKEN' marker.
Detects npm package publish events that lack 'gitHead' provenance metadata. The absence of this field indicates that the package was likely published from a developer's local machine rather than through an authorized CI/CD pipeline, a technique used in supply chain attacks to bypass CI-gated controls.
Detects a suspicious sequence where a Go toolchain is used to fetch dependencies, followed by a 'go run' execution that spawns a child process which initiates an outbound network connection shortly thereafter. This behavior is indicative of a 'hidden entry point' pattern where legitimate development tools are abused to download, compile, and execute a second-stage remote access trojan (RAT) or malicious payload.
Detects network connections to the Slack API (api.slack.com) initiated by processes executing from temporary directories commonly used by the Go build system ('go-build'). This pattern is indicative of a second-stage RAT or malicious payload compiled on-the-fly using 'go run' or similar mechanisms, utilizing Slack's infrastructure for C2 communication.
Detects instances where common scripting or development language runtimes (Go, Node.js, WScript, CScript) access sensitive configuration or credential files, such as AWS credentials, Kubernetes configs, SSH keys, or environment files. This activity is often indicative of credential harvesting or unauthorized access to sensitive secrets by potentially malicious scripts or processes.
Detects a successful login attempt by the user account 'p2pwn' targeting port 37777. Port 37777 is commonly associated with DVR/NVR surveillance equipment and is frequently targeted by brute-force attacks and botnets attempting to gain unauthorized access to embedded devices.
Detects a successful login attempt by the user account 'p2pwn' targeting port 37777. Port 37777 is commonly associated with DVR/NVR surveillance equipment and is frequently targeted by brute-force attacks and botnets attempting to gain unauthorized access to embedded devices.
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