Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Node.js or Electron processes executing from suspicious paths (e.g., Temp, Roaming) while interacting with web browser credential files or executing commands consistent with automated credential dumping tools.
Detects access to Firefox profile database files (cookies.sqlite, places.sqlite, permissions.sqlite) by suspicious processes that are masquerading as legitimate system maintenance or update utilities. This rule specifically targets known masquerading process names (UpdateAssistant.exe, AppUpdateHelper.exe, SysMaintenance.exe) while excluding the legitimate firefox.exe process and its installation directory.
Detects credential harvesting behavior originating from known malicious RubyGems packages (pwnp999, exfiltestwand3, hacksvn1778554764) observed in RubyDoc.info build environments. The rule monitors process execution and file access activity involving these packages where the command line or file path includes patterns associated with credential theft (e.g., 'api_key', 'Authorization'), scoped to Ruby-related tooling such as 'ruby', 'gem', or 'bundle'.
Detects credential harvesting behavior originating from known malicious RubyGems packages (pwnp999, exfiltestwand3, hacksvn1778554764) observed in RubyDoc.info build environments. The rule monitors process execution and file access activity involving these packages where the command line or file path includes patterns associated with credential theft (e.g., 'api_key', 'Authorization'), scoped to Ruby-related tooling such as 'ruby', 'gem', or 'bundle'.
This rule detects the process 'ShieldCrash.exe' accessing or interacting with the Windows ELAM (Early Launch Anti-Malware) configuration directory. ELAM drivers are critical components for secure boot and early malware detection; unauthorized access or manipulation by unknown processes may indicate an attempt to tamper with security tools or evade endpoint protection.
Detects access to sensitive credential stores (KeePass databases, Firefox logins, SSH keys, VPN configuration files) by suspicious processes, specifically those associated with potential credential harvesting tools or unauthorized update binaries.
Detects unauthorized processes attempting to access sensitive application data files such as browser cookies, local state, or data stored by applications like Discord, Telegram, and Steam, which are frequent targets for credential-stealing malware.
Detects unauthorized processes attempting to access sensitive application data files such as browser cookies, local state, or data stored by applications like Discord, Telegram, and Steam, which are frequent targets for credential-stealing malware.
This rule detects processes accessing sensitive credential, configuration, or environment files typically stored in locations like .aws, .ssh, .kube, or application user directories. It alerts when a non-standard or unexpected process touches multiple sensitive folders, or when specific suspicious process names or known malicious tools (such as 'NeedleStealer') are observed interacting with these files. This is indicative of potential credential harvesting or reconnaissance activities.
This rule detects processes accessing sensitive credential, configuration, or environment files typically stored in locations like .aws, .ssh, .kube, or application user directories. It alerts when a non-standard or unexpected process touches multiple sensitive folders, or when specific suspicious process names or known malicious tools (such as 'NeedleStealer') are observed interacting with these files. This is indicative of potential credential harvesting or reconnaissance activities.
This rule detects processes accessing sensitive credential, configuration, or environment files typically stored in locations like .aws, .ssh, .kube, or application user directories. It alerts when a non-standard or unexpected process touches multiple sensitive folders, or when specific suspicious process names or known malicious tools (such as 'NeedleStealer') are observed interacting with these files. This is indicative of potential credential harvesting or reconnaissance activities.
This rule detects processes accessing sensitive credential, configuration, or environment files typically stored in locations like .aws, .ssh, .kube, or application user directories. It alerts when a non-standard or unexpected process touches multiple sensitive folders, or when specific suspicious process names or known malicious tools (such as 'NeedleStealer') are observed interacting with these files. This is indicative of potential credential harvesting or reconnaissance activities.
This rule monitors Microsoft Graph API audit logs for suspicious patterns indicative of automated discovery or enumeration of SharePoint and OneDrive environments. It detects high-frequency access to sensitive API endpoints (such as /sites, /drives, or /children) and the use of pagination parameters (skiptoken, top) within short time intervals, which are common techniques used to crawl and inventory organizational data at scale.
This rule monitors Microsoft Graph API audit logs for suspicious patterns indicative of automated discovery or enumeration of SharePoint and OneDrive environments. It detects high-frequency access to sensitive API endpoints (such as /sites, /drives, or /children) and the use of pagination parameters (skiptoken, top) within short time intervals, which are common techniques used to crawl and inventory organizational data at scale.
Detects instances where a user or entity accessing a file (download, access, or preview) originates from an IP address identified as an anonymous proxy. This rule is designed to be used with a downstream aggregation tool to identify potentially unauthorized data exfiltration or access via anonymization services.
This rule detects anomalous, high-volume file access or download activity across cloud applications and file storage services. It tracks users over a period of time, flagging individuals whose daily activity consistently contributes to a large total volume of data access (exceeding 500MB) over at least five days, specifically looking for sustained behavior that deviates from sudden, single-day spikes.
Detects automated file access and download operations in SharePoint or OneDrive performed by the 'python-httpx' library. This behavior may indicate an attacker using scripts or automated tools to perform unauthorized data collection or exfiltration, often observed in automated cloud compromise scenarios.
This rule detects high-volume file access, preview, or download activity from SaaS applications (SharePoint, OneDrive, Exchange Online) originating from IP addresses classified as anonymous proxies. The threshold is set to 1000 events within a 2-hour window, which is indicative of automated, high-speed data exfiltration rather than standard user behavior.
Detects anomalous, high-volume file access (downloading, accessing, or previewing) in cloud applications that originates from an IP address identified as an anonymous proxy. This behavior is indicative of potential data exfiltration or unauthorized mass data collection.
Detects instances where a process attempts to directly open or access the Active Directory domain database file (NTDS.dit). Direct access to this file is a strong indicator of credential dumping attempts, as the file contains sensitive password hashes and domain information.
This rule detects potentially unauthorized access or large-scale extraction of sensitive RADIUS server configuration and credential databases. It monitors for common database management tools and commands used in conjunction with RADIUS-specific paths, particularly when executed by unexpected processes, during off-hours, or in a manner indicative of bulk data export.
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