Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
115 detections
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Detects potential Linux privilege escalation and persistence activities by monitoring for the creation of persistence scripts in post_boot.d, modifications to the sudoers.template file appending NOPASSWD, or system configuration rebuilds shortly after sudoers template changes.
Detects potential Linux privilege escalation and persistence activities by monitoring for the creation of persistence scripts in post_boot.d, modifications to the sudoers.template file appending NOPASSWD, or system configuration rebuilds shortly after sudoers template changes.
Detects potential Linux privilege escalation and persistence activities by monitoring for the creation of persistence scripts in post_boot.d, modifications to the sudoers.template file appending NOPASSWD, or system configuration rebuilds shortly after sudoers template changes.
Detects potential Linux privilege escalation and persistence activities by monitoring for the creation of persistence scripts in post_boot.d, modifications to the sudoers.template file appending NOPASSWD, or system configuration rebuilds shortly after sudoers template changes.
Detects potential Linux privilege escalation and persistence activities by monitoring for the creation of persistence scripts in post_boot.d, modifications to the sudoers.template file appending NOPASSWD, or system configuration rebuilds shortly after sudoers template changes.
Detects creation of sitecustomize.py, usercustomize.py, or .pth path configuration files inside a site-packages or dist-packages directory by a python or pip process. These files are automatically loaded by Python's site module on every subsequent interpreter start, allowing a malicious package installer to establish persistence that re-executes on every future Python invocation without further victim interaction.
Detects the creation or modification of Python configuration files (.pth, sitecustomize.py, usercustomize.py) within site-packages or dist-packages directories when not initiated by recognized Python package managers. Such files can be abused to achieve arbitrary code execution upon Python interpreter startup, a common method for persistence or local privilege escalation in Python environments.
This rule detects potentially malicious activity on Android devices where the 'shell' user is performing silent application installations using 'pm install' and subsequently granting accessibility permissions via 'settings put secure'. This sequence is indicative of malware attempting to gain elevated control over the device by bypassing user-interactive prompts for installation and permission authorization.
This rule detects potential backdoor deployment or persistence mechanisms in AI coding assistants like Claude Code and Cursor. It identifies when specific configuration or hook files (e.g., settings.json, hooks.js) are modified, followed within a two-hour window by the execution of suspicious child processes (e.g., powershell.exe, curl.exe, python) initiated by the coding assistant's CLI tool.
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.
Detects the registration of the 'gitlab-runner' Windows Event Log provider on hosts that are not recognized as legitimate CI/CD build servers. This can indicate unauthorized installation of GitLab runner agents or persistence mechanisms leveraging service-related event logging.
Detects instances where processes associated with Claude or Codex modify or create files within a plugin directory without a preceding legitimate installation or session command (such as 'install' or 'plugin add'). This behavior may indicate unauthorized plugin installation, persistence establishment, or malicious code injection into the development environment.
Detects the creation of persistence mechanisms on Linux systems using APT Pre/Post-Invoke hooks (e.g., /etc/apt/apt.conf.d/99sys-update) or user profile initialization scripts (e.g., /etc/profile.d/sys-init.sh). The rule monitors for these files containing suspicious command strings such as curl downloads, xmrig mining configurations, or specific init-hook markers often used by cryptomining botnets.
Detects instances where node, npm, or bun package installation processes modify the Claude AI settings.json file. This could indicate potential supply chain compromise or unauthorized configuration changes to the Claude application environment via malicious packages or scripts.
Rileva la presenza di stringhe riconducibili a un toolkit di persistenza Linux (pid file di monitoraggio, binari grub typo-squattati) all'interno del contenuto di script eseguiti sull'host.
Detects instances where node, npm, or bun package installation processes modify the Claude AI settings.json file. This could indicate potential supply chain compromise or unauthorized configuration changes to the Claude application environment via malicious packages or scripts.
The following analytic detects the creation of a Python path configuration (`.pth`) file in conjunction with a package installation process.
Path configuration files placed under `site-packages` or `dist-packages` are executed with every subsequent invocation of Python, allowing adversaries to achieve persistence on the victim endpoint regardless of build method or distribution type.
This technique was used by the threat actor group TeamPCP during the supply chain compromise of the `litellm` package.
If confirmed malicious, this could result in arbitrary code execution every time Python is invoked on the compromised host.
Path configuration files placed under `site-packages` or `dist-packages` are executed with every subsequent invocation of Python, allowing adversaries to achieve persistence on the victim endpoint regardless of build method or distribution type.
This technique was used by the threat actor group TeamPCP during the supply chain compromise of the `litellm` package.
If confirmed malicious, this could result in arbitrary code execution every time Python is invoked on the compromised host.
The following analytic detects the creation of a Python site hook file (`sitecustomize.py` or `usercustomize.py`) within a `site-packages`/`dist-packages` directory in conjunction with a package installation process.
Python's `site` module loads these hooks from directories on `sys.path` before Python is executed.
If an adversary manipulates or plants one of these files, they can hijack the Python environment and execute their payload with every Python invocation, achieving persistence on the victim endpoint.
The VIPERTUNNEL backdoor was reported to abuse site hooks in order to import and trigger DLL execution.
If confirmed malicious, this could result in arbitrary code execution every time Python is invoked on the compromised host.
Python's `site` module loads these hooks from directories on `sys.path` before Python is executed.
If an adversary manipulates or plants one of these files, they can hijack the Python environment and execute their payload with every Python invocation, achieving persistence on the victim endpoint.
The VIPERTUNNEL backdoor was reported to abuse site hooks in order to import and trigger DLL execution.
If confirmed malicious, this could result in arbitrary code execution every time Python is invoked on the compromised host.
Detects Shai-Hulud / ChainDrop activity by correlating known malicious hashes, npm/Node/Bun execution, payload artifacts, IDE persistence, credential discovery, cloud metadata access, GitHub exfiltration, C2 domains, Ethereum RPC activity, staging files, persistence artifacts, and known IOC IP connections.
Detects Shai-Hulud / ChainDrop activity by correlating known malicious hashes, npm/Node/Bun execution, payload artifacts, IDE persistence, credential discovery, cloud metadata access, GitHub exfiltration, C2 domains, Ethereum RPC activity, staging files, persistence artifacts, and known IOC IP connections.
Detects a Node or Bun process writing to Claude Code or VS Code autostart configuration. The
keyv/cacheable campaign plants a SessionStart hook in .claude/settings.json and a folderOpen
task in .vscode/tasks.json inside the trojanised source repository. Both execute the stage-1
loader when a developer or an AI coding agent opens the cloned repo, with no npm install
required - so lockfile pinning and registry blocking do not cover this path.
Note: this is the highest-value rule in the set for the agentic AI estate. It is also the one
most likely to need tuning, since tasks.json is legitimately written by many tools.
keyv/cacheable campaign plants a SessionStart hook in .claude/settings.json and a folderOpen
task in .vscode/tasks.json inside the trojanised source repository. Both execute the stage-1
loader when a developer or an AI coding agent opens the cloned repo, with no npm install
required - so lockfile pinning and registry blocking do not cover this path.
Note: this is the highest-value rule in the set for the agentic AI estate. It is also the one
most likely to need tuning, since tasks.json is legitimately written by many tools.
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