Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous, bulk file access activity targeting browser credential databases, cryptocurrency wallet data, and application-specific configuration stores, characteristic of the SectopRAT 'DeployBrowserKey' command.
Detects instances where a Claude process accesses a 'SKILL.md' file, followed closely by a suspicious command execution on the same device. The rule specifically targets command-line activity that involves encoding, download-and-execute patterns, staging in sensitive directories, or communication with suspicious domains/IPs, which is indicative of a supply-chain or poisoned agent-skill file attack.
Detects evidence of potential adversarial interference with Windows Defender updates and MRT.exe (Malicious Software Removal Tool). The rule correlates high volumes of temporary file creation in user directories with unauthorized access to MRT.exe by third-party processes and repeated Windows Defender update failures, indicating a potential attempt to disrupt endpoint security operations.
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 unauthorized processes attempting to access sensitive browser profile files, such as login credentials, cookies, and session state files. This behavior is indicative of credential harvesting or session theft by malicious software.
Detects unauthorized processes accessing sensitive credential storage files (e.g., 'Login Data', 'Cookies', 'Local State') from known Chromium-based browser profile directories. This activity is indicative of credential harvesting by infostealer malware attempting to exfiltrate browser data before performing decryption.
Detects potential insider threats or departing employees by correlating abnormal bulk data downloads from cloud repositories (SharePoint/OneDrive/Box/etc.) with subsequent sensitive data access and exfiltration signals. It uses baseline behavioral profiling, requires a threshold of sensitive file interactions, and mandates high-confidence exfiltration indicators (removable media usage, suspicious external domains, or multiple combined destination events) to reduce noise. Archive/staging activity is used as an optional confidence booster.
This rule detects potential data exfiltration by correlating access to files labeled as sensitive (confidential, restricted, etc.) with a subsequent upload to a personal cloud storage provider or transmission via email to a personal domain within a two-hour window.
Detects potential insider threats or departing employees by correlating abnormal bulk data downloads from cloud repositories (SharePoint/OneDrive/Box/etc.) with subsequent sensitive data access and exfiltration signals. It uses baseline behavioral profiling, requires a threshold of sensitive file interactions, and mandates high-confidence exfiltration indicators (removable media usage, suspicious external domains, or multiple combined destination events) to reduce noise. Archive/staging activity is used as an optional confidence booster.
Detects a credential-theft pattern associated with Psychedelic Stealer where a process accesses the 'Login Data' file of common Chromium-based browsers, followed shortly by a network connection to a known stealer exfiltration API endpoint.
Detects attempts to bypass Vite development server file access restrictions by appending query parameters such as ?raw, ?import&raw, or ?import&url&inline to request paths for sensitive files like .env, cloud credentials, and terraform state files.
Detects anomalous, unauthorized access to machine learning model artifacts (e.g., .onnx, .pt, .h5) within object storage or model registries. The rule identifies suspicious patterns including high-volume file reads by non-ML team identities, lack of multi-factor authentication, or access from geolocations outside approved operating regions, indicative of potential model exfiltration or intellectual property theft.
This rule detects potential browser-based credential and session theft by monitoring for a process that accesses multiple sensitive web browser artifacts (cookies, local state, session storage) across several user profiles in a short timeframe. It correlates this activity with the subsequent creation of a compressed archive in a temporary directory followed by an outbound network connection, indicating a multi-stage exfiltration workflow.
This rule correlates events across the end-to-end kill chain of an enterprise intrusion, specifically tracking the progression from initial endpoint-based infostealer activity (credential access), through anomalous or non-interactive sign-in activity, into privilege escalation or mailbox delegation within the cloud environment, and finally to mass data exfiltration or mail access. It detects accounts involved in at least three distinct stages of this progression within a 72-hour window.
This rule detects non-browser processes that simultaneously access a web browser's 'Local State' file and the Windows DPAPI master key storage directory. This behavior is a common precursor to credential dumping, as adversaries must decrypt browser-protected secrets (passwords and cookies) using DPAPI keys stored in the user's profile.
Detects instances where a Claude process accesses a 'SKILL.md' file, followed closely by a suspicious command execution on the same device. The rule specifically targets command-line activity that involves encoding, download-and-execute patterns, staging in sensitive directories, or communication with suspicious domains/IPs, which is indicative of a supply-chain or poisoned agent-skill file attack.
Detects a single process reading browser cookie SQLite database files across multiple distinct browser profile directories or different web browsers within a short time window. This behavior is indicative of infostealer activity attempting to harvest session cookies for session hijacking and MFA bypass.
Detects a suspected infostealer activity chain involving the unauthorized access of credential and session cookie files, followed by the archival of these files into a temporary or staging directory, and concluding with an outbound network connection to an uncommon destination from the archiving process.
Detects a multi-stage activity chain indicative of infostealer malware, including reading the browser 'Local State' file (containing the master key), accessing a browser process (likely for memory dumping or token extraction), and initiating an immediate outbound network connection to an external destination.
Detects the startup or configuration of the WebClient service, commonly associated with WebDAV redirection, followed within 15 minutes by a process (e.g., control.exe, rundll32.exe, svchost.exe) interacting with a WebDAV-style UNC path. This behavioral pattern is indicative of attackers, such as the Star Blizzard group, abusing built-in Windows functionality to facilitate credential theft or remote file execution via malicious WebDAV shares.
Detects a suspicious sequence where a process loads the .NET CLR (clr.dll or mscoree.dll) and shortly thereafter accesses specific low-prevalence file extensions (.raw or .pak) within high-risk directories (AppData/Local/Temp, ProgramData, or Users/Public). This behavior is characteristic of shellcode loaders (such as the WAV-shellcode loader) that decrypt and execute RAT payloads from obfuscated containers in memory. The rule intentionally excludes common desktop applications to minimize false positives.
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