Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the initialization of cloud synchronization tools like rclone or MEGAsync, accompanied by the creation of configuration files and subsequent high-volume network activity directed toward common cloud storage providers, indicative of unauthorized data exfiltration.
This rule monitors for unauthorized changes to GitHub Actions workflows that involve release or publishing processes, specifically looking for indicators of supply chain compromise like the introduction of 'id-token: write' or changes to publish scripts. It correlates these modifications with subsequent workflow executions and npm registry publish events attributed to the same actor to identify potential account takeover and malicious package distribution.
KQL Query
Detects potential poisoning of machine learning training data by identifying unauthorized file modifications to datasets, DVC repositories, or model registries that occur outside of authorized ETL or CI/CD windows.
Detects the creation or writing of disk image files (.iso, .img, .vhd, .vhdx) followed by the execution of suspicious file types (.lnk, .exe, .js, .vbs, .cmd, .bat, .scr) by explorer.exe within a 10-minute window. This behavior is indicative of an adversary using container files to bypass security controls or execute malicious payloads from mounted images.
Detects anomalous mass file modification or renaming activity often associated with ransomware, combined with the deletion of Windows Volume Shadow Copies using native utilities like vssadmin or wmic, and the presence of suspicious ransom note filenames.
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
This rule detects multiple suspicious file write operations on a Linux host, specifically targeting directories often used for persistence such as /etc/apt/apt.conf.d, /etc/profile.d, and /etc/cron.d. The rule flags hosts where at least two of these specific persistence techniques are utilized within a 24-hour window, which is indicative of an automated, redundant persistence strategy often employed by cryptocurrency miners like XMRig.
This rule detects suspicious activity associated with Redis server processes attempting to write to SSH 'authorized_keys' files or executing commands (such as BGREWRITEAOF or directory reconfiguration) commonly used by attackers to inject malicious SSH public keys into a Redis installation for persistent remote access.
Detects the creation or modification of a file within the /etc/cron.d/ directory, followed shortly by a Bash process invocation using /dev/tcp redirection. This pattern is commonly used by attackers to achieve persistence via cron and establish reverse shells, bypassing potential limitations of default system shells that do not support /dev/tcp syntax.
Detects the Redis server process writing or modifying files within cron configuration directories. This is a common persistence technique used by attackers to gain recurring execution after exploiting vulnerable or misconfigured Redis instances.
This rule detects suspicious activity involving macOS LaunchAgents and files within the 'Application Support/System' directory, often associated with persistence or malicious background execution. The detection looks for the creation or modification of specific plist files (e.g., com.apple.finder.agent.plist) or git-related files in Application Support, correlated with process execution of commands like 'sysnotif-repair', 'launchctl' manipulating agents, or git operations involving custom hooks paths.
Detects the creation, modification, or renaming of common JSP web shell filenames (x.jsp, u.jsp, u2.jsp) within known web application directories (e.g., webapps, Peoplesoft, WebLogic). This pattern is indicative of an adversary attempting to establish a web shell for persistent access or command execution on a vulnerable web server.
Detects execution of shell commands (cmd, powershell) by processes associated with AvisLoader (e.g., 78324.exe, VLCAssistant.exe, auto.exe), followed by the creation or modification of files in suspicious user-writable directories (e.g., appdata, temp) within a 10-minute window, suggesting potential C2 activity and secondary payload staging.
Detects anomalous activity from IDEs or AI coding assistant extension host processes (e.g., VS Code, Cursor, JetBrains). The rule alerts when these processes spawn children that access sensitive local credential files, perform network connections to non-standard/unexpected domains, or modify critical CI/CD build script configuration files, which is indicative of a supply chain compromise within the developer environment.
Detects suspicious file create or write operations within the domain SYSVOL Policies directory. This pattern is commonly associated with attackers attempting to deploy malicious payloads, such as ransom notes or configuration changes, via Group Policy Objects (GPO). The rule monitors Windows Event ID 4663 to identify unauthorized modification attempts by non-system accounts.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
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