Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects processes accessing or enumerating multiple cryptocurrency wallet files or directories across common storage paths (e.g., Exodus, Electrum, Coinomi, Ethereum, Atomic, Guarda) within a short timeframe, which is often indicative of wallet theft or credential harvesting malware.
Detects a specific sequence of behavior associated with Gryxa data collection and exfiltration. A single process queries system state or logs (scheduled tasks, WMI, event logs), creates an archive file (.zip, .7z, .rar), and establishes an outbound public network connection shortly thereafter.
Detects processes accessing or enumerating multiple cryptocurrency wallet files or directories across common storage paths (e.g., Exodus, Electrum, Coinomi, Ethereum, Atomic, Guarda) within a short timeframe, which is often indicative of wallet theft or credential harvesting malware.
Detects processes accessing sensitive files and configurations associated with multiple AI coding assistants (such as Claude, Codex, Grok, and Cursor) within a short time window, potentially indicating unauthorized access or credential theft from AI tools.
Detects when a dialog user reads a restricted SAP table using generic table browser transactions such as SE11, SE16, or SE16N.
Detects unauthorized process activity that reads, copies, archives, or transmits the NetScaler ns.conf configuration file. This file contains highly sensitive information, including AAA/LDAP bind credentials and certificates. Adversaries may stage or exfiltrate this file following the exploitation of vulnerabilities (such as CVE-2026-88771 or CVE-2026-88772) on NetScaler appliances to facilitate further network compromise.
Detects a suspicious pattern where a user authenticates to a remote access portal (like Citrix or VPN) without multi-factor authentication (MFA) or with an existing risk flag, followed by a surge in file activity (creation, modification, or renaming of >500 files or >200 distinct files) on the same account within a 24-hour window, potentially indicating compromised credential usage for staging data for exfiltration or ransomware.
Detects the use of legitimate archival utilities (such as 7-Zip, WinRAR, tar) or scripting engines (PowerShell) to compress or package sensitive browser profile artifacts like 'Login Data', 'Cookies', or 'Local State'. This behavior is a common indicator of credential harvesting and data staging activity by infostealers prior to exfiltration.
Detects unauthorized access to or generation of Citrix NetScaler core dump files, trace outputs, or memory diagnostic artifacts. These artifacts are high-value targets for attackers, such as those exploiting CVE-2026-88772, who attempt to extract session tokens, credentials, and sensitive data residing in memory via these diagnostic mechanisms.
Detects unauthorized access or modification attempts to common web browser credential storage files (such as 'Login Data' or 'key4.db') by processes other than standard, trusted web browsers (e.g., Chrome, Edge, Firefox). This behavior is indicative of credential harvesting, where an adversary attempts to steal saved login information from browser data stores.
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 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 unauthorized access, reading, or downloading of sensitive NetScaler system files, including configuration files (ns.conf), licensing files, and cryptographic material (private keys/certificates). This activity often indicates post-exploitation reconnaissance, staging, or data theft attempts following initial access.
Detects the use of legitimate data transfer utilities (s5cmd, rclone) configured to exfiltrate sensitive document types (.doc, .pdf, .sql, etc.) to S3-compatible cloud storage. The rule correlates this activity with recent access to files containing sensitive credentials or configuration data, a pattern observed in double-extortion campaigns.
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.
Detects unauthorized processes attempting to read sensitive session files or databases associated with messaging applications like Telegram, Signal, and Discord. Accessing these files (such as 'tdata', 'db.sqlite', or 'leveldb') allows for full account takeover by extracting session tokens, enabling attackers to bypass authentication and 2FA.
Detects a suspicious pattern where a user authenticates to a remote access portal (like Citrix or VPN) without multi-factor authentication (MFA) or with an existing risk flag, followed by a surge in file activity (creation, modification, or renaming of >500 files or >200 distinct files) on the same account within a 24-hour window, potentially indicating compromised credential usage for staging data for exfiltration or ransomware.
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 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 unauthorized processes attempting to read sensitive wallet extension storage files or desktop application wallet data folders, a behavior characteristic of the Psychedelic Stealer malware designed to harvest cryptocurrency credentials prior to exfiltration.
Detects the use of 'findstr' or PowerShell to query sensitive configuration files (such as web.config or applicationHost.config) for credential-related keywords like 'connectionString', 'AccountKey', or 'machineKey'. This behavior is indicative of an adversary attempting to harvest credentials or sensitive configuration data stored in cleartext on the filesystem.
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