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Daniel Jeremiah

@daniyyell
United KingdomTrusted contributorCompletionist
8 followers4,600 downloads2,430 copies68 likes128,312 views

978 detections

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='.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
3057
This rule identifies various activities associated with the Dohdoor malware campaign, combining multiple detection heuristics into a single result set. It looks for PowerShell executing curl to download batch scripts, copied Windows tools run from shared folders with unusual arguments, suspicious DLL loads from shared folders, and network connections to C2-style domains identified in the campaign.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
6055
This rule detects various stages of an attack chain, starting from an Apache ActiveMQ exploit (CVE-2023-46604) leading to LockBit-style ransomware. It identifies process creation anomalies (java.exe spawning certutil.exe for downloads), network connections to known Metasploit C2 infrastructure, the presence of specific ransomware file hashes, and attempts to clear Windows event logs, all indicative of the described attack scenario.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
1085
Detects xattr quarantine removal on a file in a writable location, often used before executing downloaded malware such as AMOS delivered via malicious skills.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
1036
Detects Linux cron persistence, log tampering, outbound IRC ports, or compiler use from temp paths, matching SSHStalker botnet tradecraft.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
0030
This rule detects activities associated with the XWorm LATAM campaign. It identifies network indicators such as specific C2 domains (jholycf100.ddns.com.br, voulerlivros.com.br, res.cloudinary.com), a specific IP address (152.249.17.145), and a destination port (7000). It also looks for the abuse of CasPol.exe making outbound connections to the identified C2 infrastructure. Furthermore, the rule detects PowerShell processes spawned by WMI (WmiPrvSE.exe) that attempt to fetch content from Cloudinary and load assemblies in memory, indicating potential in-memory execution. Finally, it includes a specific SHA256 file hash (7befeacf0b3480fb675d0cab7767b5b9697edc9d0e05982025a06ead0054afd5) associated with the campaign.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
6077
Detects Claude Code spawning suspicious child processes, consistent with abuse of project configuration hooks or MCP initialisation commands.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
1038
Detects `msedgewebview2.exe` connecting to Grok/Copilot when the parent is not a browser/Office app, matching the AI-in-the-middle C2 proxy technique.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
1029
This rule detects various stages of the CastleLoader malware activity, including C2 communication, process hollowing using AutoIt and jsc.exe, and known malware hashes. It correlates network traffic to a specific C2 server, identifies suspicious process creation patterns where AutoIt launches jsc.exe, and sweeps for known SHA256 hashes associated with CastleLoader.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
1076
This rule detects indicators associated with the RenEngine campaign, which involves the deployment of HijackLoader, Lumma Stealer, and ACR Stealer. Detection is based on specific MD5 hashes of known malicious files, filenames used in the campaign, and command and control (C2) domains identified as part of the infrastructure.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
0068
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