Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of macOS command interpreters (osascript, sh, bash, zsh) where the command line arguments reference specific timezones (e.g., Moscow, Minsk) or locale settings (e.g., RU, BY, KZ, AM, AZ). This pattern is often associated with adversary attempts to detect or evade sandbox environments based on regional settings or to align with specific target geographic profiles.
Detects the creation of a .plist file in a user LaunchAgents directory within 300 seconds of the process loading the ServiceManagement framework. This pattern is often used by macOS applications to establish persistence or perform background tasks, but can be indicative of malicious activity if associated with unauthorized or masquerading binaries.
Detects execution of 'npm install' or 'npm ci' commands that explicitly include '@marketfront' or '@tqm-mfe' scopes. This detection is designed to identify potential dependency confusion attacks where malicious actors publish public packages with the same names as internal private packages to trick build systems into downloading malicious code instead of legitimate internal modules.
Detects the use of Git commands (filter-branch, rebase -i, or force-push) that rewrite local or remote commit history. These operations are often used by adversaries to hide malicious code injections, remove evidence of unauthorized changes, or manipulate developer repository integrity.
Detects HTTP POST requests directed to the 'avenger-sync.live' domain by the PamStealer malware. The rule identifies specific C2 or exfiltration traffic patterns, including the '/api/sync' URI and a specific JSON-formatted data envelope in the request body, commonly used by the malware for communication.
Detects file system artifacts indicating installation of the malicious 'ascii-fetcher' VS Code extension (v1.0.0) from the Open VSX marketplace, which bundles the malicious npm dependency '@jaymara/jsononifier' to hide its logic from static analysis.
Detects instances where the same file (identified by SHA256) with common lure names like 'resume', 'headshot', or 'faceswap' is being created or modified by multiple different users across the environment. This behavior is often indicative of an adversary distributing malicious files or a coordinated effort to access sensitive or tempting filenames, potentially related to social engineering or lateral movement.
Detects execution of Node.js applications that utilize specific Jscrambler obfuscation versions or the presence of these versions in package.json files, which may indicate the use of compromised or unauthorized supply chain dependencies.
Detects processes attempting to interact with the macOS NSPasteboard (clipboard) that are not typically associated with standard clipboard utility operations like Maccy, pbcopy, or pbpaste. This may indicate unauthorized data collection or exfiltration of sensitive information copied to the system clipboard.
This rule detects the execution of mitmproxy, mitmweb, or mitmdump in reverse-proxy mode configured specifically to target login.microsoftonline.com. This behavior is highly characteristic of an adversary setting up an Adversary-in-the-Middle (AiTM) platform to perform TLS interception on authentication traffic, potentially leading to credential and session cookie theft.
This rule monitors for the creation of files containing the string 'readme_ransom' or the execution of processes that reference 'readme_ransom', specific known ransomware wallet addresses, or associated contact email addresses, which are indicative of post-encryption ransomware activity.
Detects enumeration of local system accounts on MacOS systems.
This can be used by attackers to identify accounts for lateral movement or privilege escalation.
This can be used by attackers to identify accounts for lateral movement or privilege escalation.
This rule identifies endpoints that have transferred a total of more than 50MB of data to a single external, non-private IP address. The detection filters out RFC1918 private subnets and local loopback traffic, aggregating byte counts and connection attempts per endpoint, computer, and destination. This is indicative of potential data staging or exfiltration activities.
Detects large outbound network transmissions occurring on a host shortly after the creation of staged or archive files. This behavior is indicative of an attacker consolidating sensitive data (such as credentials or intelligence) into an archive and subsequently exfiltrating it over a Command and Control (C2) or other established network channel.
Detects network connection events where the requested URL contains 'dogleash' and includes common architecture suffixes (mips, arm, x64) or shell script extensions (.sh), often indicative of downloading stage payloads associated with the Dogleash malware family.
Detects the download of a Mach-O executable file over unencrypted HTTP. The rule identifies the Mach-O magic byte header ('CF FA ED FE') within the first few bytes of the HTTP response body, indicating a file download originating from an external network source.
Detects the execution of an AppleScript file via the osascript utility that initiates a network connection within a 5-minute window of execution. This behavior is often indicative of automated script-based network activity, such as command-and-control communication or data exfiltration.
Detects PamStealer's embedded helper binary dropped to /private/tmp/System Settings and used to establish legacy login item persistence via osascript System Events
Detects file creation, modification, or renaming events within sensitive macOS Application Support directories that mimic core system components such as Finder or Software Update. This behavior is indicative of potential masquerading or persistence techniques where an attacker replaces legitimate application resources with malicious ones.
Detects the Finder application on macOS loading authentication modules (libpam.dylib) from within the 'Application Support' directory. The rule further correlates this by checking if common system utility tools (dscl, security, osascript) were initiated by the same Finder process path, flagging cases where legitimate system activity is absent, which may indicate potential dylib hijacking or suspicious process behavior.
Detects processes that execute commands involving SQL database operations, specifically those related to AES encryption functions or table management (create/drop operations) on configurations. This activity is often associated with potential database manipulation or data destruction attempts by an attacker.
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