Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule set looks for signs linked to the Shadow Campaigns espionage group. It flags the use of their loader, checks for connections to known servers they have used, spots fake security software used as bait, and highlights suspicious activity coming from web server processes that may indicate a hidden backdoor.
This rule detects potential RDP lateral movement by identifying accounts that log on to multiple distinct workstations via RDP (LogonType 10) within a one-hour window, where the workstation name is different from the computer name. A logon chain of more than two distinct computers for the same account and IP address within an hour is flagged as suspicious.
This rule detects HTTP network connections to the Telegram bot API (api.telegram.org/bot). This pattern is often associated with infostealers exfiltrating data to attacker-controlled Telegram bots. The rule specifically looks for the 'NETWORK_HTTP' event type and a URL containing '/api.telegram.org/bot' (case-insensitive).
Detects PowerShell downloading XWorm V6 binary from github.com, spawned by wscript.exe
Detects processes masquerading as legitimate software making HTTP requests to specific API endpoints associated with the TrustConnect/DocConnect RAT C2.
This rule detects suspicious enumeration of Azure Blob, File, Table, Queue, or DFS storage accounts by internal users. It identifies devices making network connections to public Azure storage URLs using potentially suspicious processes (e.g., PowerShell, Python, AzCopy, curl, wget, WinSCP, FileZilla, Storage Explorer). The rule then analyzes the distinct storage accounts accessed and uses a Jaccard index to identify unusual naming conventions among the accessed storage accounts, potentially indicating an insider attempting to discover or exfiltrate data from unfamiliar storage resources.
Detects network connections or DNS queries to domains and IP addresses identified as payload delivery and C2 infrastructure for a JWrapper/SimpleHelp RAT campaign. Monitoring these indicators can help detect initial compromise or ongoing C2 communication.
Detects suspicious network connections to 'outlook-one.vercel.app' or 'api.telegram.org' when initiated by common web browsers (msedge.exe, chrome.exe, firefox.exe) or Outlook (outlook.exe). This pattern can indicate phishing attempts, credential harvesting, or data exfiltration via Telegram bots.
Detects suspicious HTTP command-line connections initiated by sqlservr.exe, which may indicate misuse or post-exploitation activity.
Detects outgoing network connections using the User-Agent 'ArkanixStealer/1.0', which is hardcoded in the C++ variant of the Arkanix Stealer.
This rule detects network connections to domains identified as malicious redirectors or landing pages used in a spam campaign that exploited Atlassian Jira. The domains are associated with phishing or malware distribution efforts.
Detects the execution of 'cmd.exe' initiated by common Microsoft Office applications, scripting engines, or msiexec.exe, where the command line includes 'curl' for downloading a '.pdf' file and also attempts to delete files using 'del /s /q'. This behavior is often associated with initial access, download of malicious payloads, and cleanup activities by adversaries. The rule specifically looks for command lines that interact with 'Users\Public', 'conhost.exe', or use the '--headless' flag, which can indicate automated or background execution.
This rule detects network communication with known command and control (C2) infrastructure associated with the OysterLoader malware. It identifies C2 activity by looking for connections to specific domains and IP addresses, as well as requests to particular API paths within the RemoteUrl field.
This detection identifies the execution of iptables commands used to implement Single Packet Authorization (SPA). This technique was observed being used by UNC6201 on compromised VMware appliances to create stealthy, conditional network proxies for C2 traffic. The rule looks for specific command-line arguments indicative of SPA setup, including rules for 'magic packet' detection, dynamic IP list management using the 'recent' module, and traffic redirection.
Detects potential exploitation attempts against a buffer overflow vulnerability (CVE-2026-2329) in Grandstream VoIP phones. This rule identifies web requests targeting the vulnerable API endpoint '/cgi-bin/api.values.get' with an overly long query string (>64 bytes) or the use of multiple colons (>=3) which could indicate a ROP chain attempt. The detection is based on DeviceNetworkEvents from Microsoft Defender for Endpoint.
Detects non-browser processes that spawn the WebView2 process (msedgewebview2.exe) which subsequently makes network connections to known AI platforms like copilot.microsoft.com or grok.com. This behavior is indicative of malware using an embedded browser for covert Command and Control (C2) communications, as described by Check Point Research.
This rule detects various activities associated with the 'CrashFix' variant of the 'Clickfix' malware, which deploys a Python-based Remote Access Trojan (RAT). The detection logic covers several stages of the attack:
1. **Browser Extension Installation**: Identifies the creation of a specific malicious Chrome extension file (.crx) with a unique identifier.
2. **Command and Control (C2) Traffic**: Monitors network connections to known malicious URLs and IP addresses associated with the malware's C2 infrastructure.
3. **Malicious Hashes**: Detects the execution of processes with specific SHA256 hashes known to belong to the CrashFix malware.
4. **LOLBIN Abuse**: Identifies the use of living-off-the-land binaries (LOLBINs) like 'finger.exe' and 'ct.exe' in suspicious command-line combinations, potentially for discovery or execution.
5. **Malicious IP Communication**: Looks for network connections initiated by 'ct.exe' with the 'confirm' argument, indicating communication with potentially malicious remote IPs.
6. **Python TTPs**: Detects Python execution patterns, specifically 'pythonw.exe' running 'modes.py' and making outbound network connections to non-local IPs, indicative of the Python RAT.
7. **Persistence via Registry Run Key**: Monitors for registry modifications related to 'pythonw.exe modes.py', suggesting persistence mechanisms.
8. **Persistence via Scheduled Task**: Identifies the creation of scheduled tasks that execute 'run.exe' and 'udp.pyw', another persistence method.
1. **Browser Extension Installation**: Identifies the creation of a specific malicious Chrome extension file (.crx) with a unique identifier.
2. **Command and Control (C2) Traffic**: Monitors network connections to known malicious URLs and IP addresses associated with the malware's C2 infrastructure.
3. **Malicious Hashes**: Detects the execution of processes with specific SHA256 hashes known to belong to the CrashFix malware.
4. **LOLBIN Abuse**: Identifies the use of living-off-the-land binaries (LOLBINs) like 'finger.exe' and 'ct.exe' in suspicious command-line combinations, potentially for discovery or execution.
5. **Malicious IP Communication**: Looks for network connections initiated by 'ct.exe' with the 'confirm' argument, indicating communication with potentially malicious remote IPs.
6. **Python TTPs**: Detects Python execution patterns, specifically 'pythonw.exe' running 'modes.py' and making outbound network connections to non-local IPs, indicative of the Python RAT.
7. **Persistence via Registry Run Key**: Monitors for registry modifications related to 'pythonw.exe modes.py', suggesting persistence mechanisms.
8. **Persistence via Scheduled Task**: Identifies the creation of scheduled tasks that execute 'run.exe' and 'udp.pyw', another persistence method.
Identifies processes that first communicate with AI services and then perform a low-volume burst of file creation or deletion events. This behavioral pattern may indicate an AI-driven ransomware or wiper attack that is surgically targeting key data to evade traditional volume-based detection methods, as theorized by Check Point Research.
This rule set detects the OysterLoader malware. The first rule, 'OysterLoader_Mutex_and_TaskNames', identifies the malware based on specific mutex names, scheduled task names, and user-agent strings ('WordPressAgent' and 'FingerPrint') used by OysterLoader. The second rule, 'OysterLoader_C2_Endpoint_Strings', focuses on identifying OysterLoader by detecting specific C2 API paths used for communication with its command and control server. Both rules require the presence of a valid PE file header (MZ magic bytes).
Detects network connections or DNS queries to domains and IP addresses identified as payload delivery and C2 infrastructure for a JWrapper/SimpleHelp RAT campaign. Monitoring these indicators can help detect initial compromise or ongoing C2 communication.
This YARA rule set detects various artifacts associated with the Remcos RAT 'ClickFix' campaign. The rules identify persistence mechanisms (registry run keys or scripts involving 'Shotcut video editor', '2120206', and 'shotcut.exe' for DLL sideloading), archive or path indicators ('2120206' and 'shotcut.exe'), clipboard scripts used for dropping malware related to the Shotcut DLL sideloading technique.
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