Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule set detects components of the ClipXDaemon, a Linux clipboard hijacker. The first rule, 'ClipXDaemon_Bincrypter_Loader', identifies a loader component characterized by specific strings related to process information, OpenSSL, gzip, and a pattern of variables (P, S, C, R) often used in shell scripts for unpacking, all within a small file size. The second rule, 'ClipXDaemon_ELF_Clipboard', targets the main ELF executable of ClipXDaemon. It looks for an ELF file that interacts with X11 clipboard functions (XConvertSelection, XSetSelectionOwner), attempts to masquerade its process name as 'kworker/0:2-events', and contains hardcoded cryptocurrency wallet addresses used by the attacker. Together, these rules aim to identify both the unpacking mechanism and the core functionality of the ClipXDaemon malware, which is designed to swap cryptocurrency wallet addresses from the clipboard.
Detects successful Entra ID sign-ins that exhibit characteristics of an Adversary-in-the-Middle (AiTM) session cookie hijack.
This activity is often associated with AiTM phishing kits like Tycoon2FA, where attackers replay stolen session cookies from unmanaged devices to bypass MFA.
This activity is often associated with AiTM phishing kits like Tycoon2FA, where attackers replay stolen session cookies from unmanaged devices to bypass MFA.
This rule detects potentially risky browser sign-ins from unmanaged devices, which aligns with account access patterns observed in AiTM (Adversary-in-the-Middle) phishing campaigns like those discussed in the Tycoon2FA report. It identifies sign-ins where the risk level is elevated (50 or 100), the client application used is a browser, and device trust type and device name information are empty, suggesting an unknown or untrusted device. This serves as a lead to investigate suspicious browser-based sign-ins that might indicate an AiTM compromise.
Detects browser processes (Chrome or Edge) launched with command lines containing known malicious extension IDs associated with AI chat harvesting.
Detects a web server process spawning tools commonly used for data staging and exfiltration, such as rar.exe, certutil.exe, and type.exe. This behavior is characteristic of the CL-UNK-1068 actor's exfiltration TTP, often performed via a web shell.
Detects the execution of PowerShell with a command line containing a specific sequence of strings associated with extracting and executing malware from a ZIP file, as observed in the Steam_Monitor campaign. This typically involves using PowerShell commands like 'Get-ChildItem', '::OpenRead', and 'TaR' in conjunction with a '.zip' file.
Detects the execution of shell or system utilities (e.g., powershell, cmd, curl) where the parent process is a known AI agent binary like OpenClaw. This activity can indicate that an attacker has compromised the AI agent (e.g., via the ClawJacked vulnerability) and is using its capabilities to execute arbitrary commands, collect data, or exfiltrate information from the host system.
This rule is meant to help analysts quickly spot a high-confidence indicator related to Google AuraInspector Salesforce Aura Audit. It is written to be easy to understand and to keep false alarms low by focusing on a very specific match: an HTTP POST to a Salesforce /aura endpoint that includes specific Aura method strings. A match does not automatically prove an attacker is currently active, and it does not prove a file was executed, but it does mean the event is important because it lines up with a public threat intelligence source. When this triggers, start by identifying the host, user, and timeframe involved, then decide whether the activity is expected for that system. If it is unexpected, preserve the related logs and any files, and look for nearby events that could explain how the indicator appeared, such as a download, a new process, or a new connection. If the same indicator appears on multiple systems, treat it as a scoping signal and expand the investigation window. Use the reference link (https://cloud.google.com/blog/topics/threat- intelligence/auditing-salesforce-aura-data-exposure) to document where the indicator came from and to support incident notes and reporting.
Detects the enumeration of camera or microphone hardware using the 'Get-PnpDevice' PowerShell cmdlet. This behavior is a precursor to surveillance activities such as webcam capture or audio recording and has been associated with the Moonrise RAT.
This rule detects instances where Microsoft Copilot accesses external resources, specifically identifying events where 'XPIADetected' is true. This indicates Copilot interacting with resources outside its immediate environment, which could be a security concern if the accessed resources are sensitive or untrusted.
Detects the creation of an unusual lock file at `/usr/share/nano/.lock`. This specific path is used by a backdoored Go module (impersonating golang.org/x/crypto) to temporarily store harvested plaintext passwords before exfiltration. The rule specifically looks for file creation events at this highly specific path.
Detects the use of the GNU Debugger (GDB) to dump memory from a live process. This technique is used by frameworks like ShadowHS to extract credentials and other secrets directly from memory, bypassing file-based security controls.
Detects common shell tools accessing OpenClaw plaintext workspace secrets such as the .env file under ~/.openclaw/workspace/.
Detects archiving of OpenClaw workspace data which may contain plaintext conversations and secrets, consistent with collection and staging for exfiltration.
Detects the deletion of the RunMRU registry key and the clearing of the clipboard within a short time window on the same host. This sequence of anti-forensic actions is used by the batch script component of the Dohdoor malware campaign to hide its tracks.
This rule detects phishing attempts related to a Booking.com campaign. It identifies suspicious URLs containing 'op_token' or 'tpo_token' parameters, often combined with paths like 'complaint' or 'reserv', on non-Booking.com domains. It specifically looks for punycode domains (e.g., 'xn--*'), lookalike domains (e.g., '*booklng*', '*mgmnt*', '*portal*'), and specific high-signal punycode domains identified in reports. The rule also includes a pattern for partner kit redirect URLs with 'tpo_token' on 'booklng' subdomains. Additionally, it suggests looking for specific email patterns from Gmail senders with subjects like 'Automatic reply', 'Availability', or 'Reservation' that contain embedded URLs matching 'complaint?op_token='.
Detects the execution of 'osascript' to display a deceptive system dialog box mimicking a 'System Preferences' password prompt. This technique is used by malware like the Atomic macOS Stealer (AMOS) to trick users into entering their administrative password for credential theft.
This rule detects activity related to the DKnife gateway AitM (Adversary-in-the-Middle) threat, as detailed in Talos Intelligence reporting. It identifies specific binary names (dknife.bin, sslmm.bin, postapi.bin, rules.bin, sshapi.bin, inotify.bin, curlapi.bin) associated with the threat, either as process names or file names. Additionally, it looks for configuration artifacts (rules.conf, sslmm.cfg, url.cfg) used by the proxy/redirect logic, either as file names or within process command lines. Finally, the rule identifies exfiltration or tagging markers (dkimsi=, 460110672021628, PASSWORD) observed in logs or artifacts, which are indicative of DKnife's reporting mechanisms.
Detects suspected DKnife gateway AitM activity by matching Linux process/file artifacts (component names and config files) described in the Talos DKnife disclosure.
Detects data exfiltration patterns used by HoneyMyte scripts. The rule monitors for rar.exe compressing files with a specific password or curl.exe uploading data to the Pixeldrain file-sharing service.
Detects DKnife text markers and config file names referenced by Cisco Talos (dkimsi tag, default IMSI, credential tag, and common DKnife config artefact names).
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