Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the creation or renaming of files to a .aspx extension within specific web application directories (member file-upload). The rule specifically filters for file operations initiated by the IIS worker process (w3wp.exe) and requires a non-zero file size, identifying potential web shell deployment attempts.
Detects the creation or renaming of files to a .aspx extension within specific web application directories (member file-upload). The rule specifically filters for file operations initiated by the IIS worker process (w3wp.exe) and requires a non-zero file size, identifying potential web shell deployment attempts.
This rule performs a point-in-time sweep for known Indicators of Compromise (IOCs) associated with the NeedyMantis threat actor group. The detection logic searches for specific file, process, and image-load SHA256 hashes, communication with a known C2 domain (tripswithengine.com), and the use of a hard-coded user-agent string (Firefox/21.0) across various telemetry sources within the last 30 days.
Detects the two Windows-networking-named DLLs the report confirms as sideloaded via the normal OS loader (WinSparkle.dll, libcurl.dll) plus vim64.dll (a filename Vim's real installer never produces at all). Path check now covers any location outside a small allowlist of known-legitimate vendor install folders, not just ProgramData, so it also catches the reported ProgramData\\USOShared, ProgramData\\VIM, and ProgramData\\TightVNC\\VIM placements. Known limitation: the one reported case where the malicious WinSparkle.dll sits at the exact canonical Program Files\\Poedit path cannot be distinguished by path alone -- that specific sideload is instead caught by the companion 'Extensionless Archive Paired with Same-Named DLL Drop' rule via the archive-pairing signal.
This rule monitors for indicators of compromise (IOCs) associated with the Lunex Malware-as-a-Service (MaaS) campaign. It aggregates telemetry from file creation, process execution, and network connections to identify the presence of known malicious hashes, C2 IP addresses, phishing-related domains, and specific payload URLs.
Detects when common web server worker processes spawn command-line tools or shell interpreters, which is a common post-exploitation technique used by web shells like Godzilla to execute arbitrary commands.
Detects a suspected exploitation attempt of CVE-2024-21412. The rule identifies a chain of execution involving an internet shortcut (.url) masquerading as a common file type (e.g., .jpg.url), which subsequently opens another shortcut to a WebDAV/IP host. This sequence is used to bypass Mark-of-the-Web (MotW) protections and execute a malicious batch script and Rundll32 process.
This rule detects installation of known malicious npm packages associated with the PhantomSub campaign, which abuse WhatsApp spam channels. It also identifies network connections to known remote C2 channel-list URLs or domains used by these packages to automate channel joining.
This rule detects a single device making a high volume of connections to known machine learning model and dataset hosting repositories (e.g., Hugging Face, Kaggle, TensorFlow) within a short timeframe. Such activity may indicate bulk exfiltration of sensitive internal research data, proprietary models, or large datasets.
Detects potential lateral movement by users who have recently been flagged for credential theft or infostealer activity. The rule correlates initial security alerts with subsequent Windows logon events (RDP, network/WinRM) or SMB share access, identifying users connecting to multiple distinct destinations within a 48-hour window.
Detects unauthorized processes attempting to read or create sensitive browser credential files ('Login Data', 'Web Data', 'Cookies', 'logins.json', 'key4.db'). This activity is commonly associated with information-stealing malware (such as Lumma, StealC, Vidar, RedLine, and Amadey) that targets browser databases to extract stored secrets, often bypassing standard browser process access.
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 unauthorized processes attempting to read or create sensitive browser credential files ('Login Data', 'Web Data', 'Cookies', 'logins.json', 'key4.db'). This activity is commonly associated with information-stealing malware (such as Lumma, StealC, Vidar, RedLine, and Amadey) that targets browser databases to extract stored secrets, often bypassing standard browser process access.
This rule detects the installation or execution of common Remote Monitoring and Management (RMM) tools (e.g., AnyDesk, ScreenConnect, Atera, Splashtop, TeamViewer) on Windows endpoints within a 4-hour window of associated cloud identity risk activity (such as risky sign-ins, MFA changes, or privilege grants). It filters out legitimate activity initiated via standard software management pipelines (e.g., SCCM, Intune) to identify potential unauthorized use of remote access software by adversaries following account compromise.
Detects impossible-travel activity where a single user account authenticates successfully from multiple distinct countries or IP addresses within a short 15-minute window. This behavior is highly indicative of potential session hijacking or the concurrent use of a stolen session token by both an attacker and a legitimate user.
Detects access to sensitive browser credential and cookie files by processes that are not recognized web browsers or their designated update components. This behavior is highly indicative of credential theft activity where an adversary is attempting to extract stored credentials or session cookies from local browser storage.
Detects instances where the Windows Terminal application (or related processes like OpenConsole) spawns suspicious command-line utilities such as PowerShell, CMD, curl, or certutil with indicators of potential download activity or command-line obfuscation. This pattern is often indicative of interactive adversary activity attempting to stage tools or execute payloads.
Detects periodic, beacon-like network activity targeting public platforms such as Steam community profiles or Telegram (api.telegram.org / t.me) originating from suspicious processes (script interpreters, unsigned binaries). This behavior is characteristic of LummaC2 and similar malware families using public web services as dead-drop resolvers for C2 fallback communication.
This rule detects potential session hijacking by correlating endpoint-based detections of known infostealer malware (e.g., Vidar, Lumma, Redline) with a subsequent cloud Identity Provider (IdP) login for the same user. The correlation specifically focuses on instances where the IdP authentication originates from an IP address different from the infected host, suggesting the use of stolen session cookies by an external actor to access corporate resources.
Detects unauthorized access by a non-browser process to Chromium-based 'Cookies' SQLite database files, which are used by browsers like Chrome, Edge, and Brave. This behavior is a strong indicator of credential theft or session hijacking, as attackers target these files to extract session cookies and bypass MFA for cloud services.
This rule detects the suspicious archival of browser credential files (e.g., Login Data, Cookies, wallet.dat) or the transmission of data to common command-and-control (C2) services such as Telegram, Discord, or raw IP addresses using common system tools like PowerShell, curl, or certutil.
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