Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

10,670 detections

KQL Query from file: Endpoint SMB Exposed on Public Internet
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
91397
This query is using the DeviceNetworkEvents table to filter by connections where there are encryption algorithms used. Then, I take a list of the encryption algorithms database from the well-known site iana.org which is an entity that monitors the global allocation of IP addresses, autonomous systems, DNS domain name root servers and other Internet Protocol resources. Finally, It list cases where there are multiple connections established using non-recommended or non-valid datagram transport layer security (DTLS), which could mean that our users are not protected against eavesdropping, tampering or message forgery.
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Sergio Albea@Sergio_Albea
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01 | 🇨🇭 Swiss Cyber Hunters
1 year ago
41117
Detects the multi-stage DLL sideloading technique used by the Nimbus Manticore APT group. This rule identifies when the legitimate Windows Defender component 'SenseSampleUploader.exe' loads 'xmllite.dll' from a non-standard directory, a behavior indicative of the group's novel DLL path hijacking method.
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Tim Peck@timpeck
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Detections.ai Community
1 year ago
1089
This rule detects various artifacts and behaviors associated with the DeedRAT malware, also known as MicRun or SBAMRES. It identifies the execution of 'MicRun.exe', suspicious file paths like 'C:\ProgramData\MicroDefaults', and registry persistence via 'Run' keys with specific data patterns. The rule also looks for the creation of malicious services using 'sc create MicRun', known malicious SHA256 hashes for both processes and files, and suspicious filenames such as 'SBAMRES.DLL' and 'MicRun.exe'. Additionally, it detects network communication to a known DeedRAT C2 domain, 'luckybear669.kozow.com'.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
40221
Detects the creation of Chrome extension files (.crx) that match known malicious extension IDs. Malicious CRX files on endpoints can indicate an attacker dropped or installed a malicious extension (e.g., credential harvesters, redirectors, miners). The rule flags CRX creation with known bad IDs and requires available file hashes for further investigation.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
190377
Detects outbound network connections to the Telegram API, a technique used by XWorm for command and control (C2) and data exfiltration. The rule specifically looks for connections to "api.telegram.org/bot" and "/sendMessage" paths, originating from suspicious processes like WmiPrvSE.exe or Soundman.exe, or from common user-writable locations.
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Kaung Khant Ko@kaungkhantko
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Detections.ai Community
1 year ago
123152
Detects multiple Event ID 4648 logon attempts using the same target account but from different source accounts within a short time window. This behavior may indicate lateral movement, credential stuffing, or misuse of shared credentials. By correlating explicit credential use across users, it helps identify possible compromise or abuse of privileged accounts.
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Michael Fajkus@MilesDyson
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Detections.ai Community
1 year ago
50174
This rule detects scheduled tasks that execute unsigned binaries. It specifically looks for processes initiated by 'svchost.exe -k netsvcs -p -s Schedule', which is indicative of a scheduled task, and then filters for binaries that are not signed and have low global prevalence. This can help identify malicious code executed via scheduled tasks that attempts to evade detection by using unsigned executables.
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Benjamin Zulliger@benscha
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Detections.ai Community
1 year ago
101262
This rule detects potential malware infections and command and control activity by correlating email, endpoint file, and network events with indicators of compromise (IOCs) sourced from an external OSINT feed. It specifically looks for SHA256 hashes in email attachments, domains and URLs in email links, MD5, SHA1, and SHA256 hashes of created files on endpoints, and IP addresses and domains in network connections (both direct and HTTP inspected connections). The rule aims to identify initial access, execution, and command and control phases of an attack, potentially involving Cloudflare Tunnels as suggested by the rule's title and the OSINT source.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
91187
This rule detects network connections to known EvilGinx phishing infrastructure, identified by specific remote URLs, IP addresses, and a suspicious login URL pattern. EvilGinx is a phishing framework used for credential harvesting and session cookie theft, often employing adversary-in-the-middle techniques.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
121241
This rule detects network traffic blocked by Microsoft Defender Exploit Guard Network Protection or SmartScreen. It categorizes these detections into several types: Indicator of Compromise (IoC) URLs, Web Content Filtering, Malicious/Command & Control, and Cloud App Security Broker (CASB) policy violations. The rule summarizes these events per device, providing counts for each detection category and listing the blocked URLs with timestamps.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
60153
This rule correlates Microsoft Defender for Endpoint (MDE) SmartScreen and Network Protection blocks with network activity logs. It specifically looks for instances where SmartScreenUrlWarning or ExploitGuardNetworkProtectionBlocked events occur due to 'CustomBlockList' or 'CustomPolicy' settings. The rule then joins these events with DeviceNetworkEvents to identify the associated URLs, remote IP addresses, and ports involved in the blocked network communication. The primary goal is to identify and provide context for network access attempts that are blocked by custom security policies, indicating potential malicious or unwanted website access.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
10137
Detects suspicious usage of MpCmdRun.exe, the Microsoft Defender command-line utility, to potentially steal NTLM credentials. This rule specifically looks for MpCmdRun.exe being executed with parameters related to scanning or exclusion checking, combined with attempts to access remote UNC paths (\\). This behavior can indicate an adversary attempting to force NTLM authentication to a controlled server to capture hashes.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
30125
Detects PowerShell commands using encoded command-line arguments to execute 'net user', 'net group', or 'net share' commands. This technique is often used by adversaries to obfuscate their actions and evade detection.
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Barsha Sketh@Barshasketh
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Detections.ai Community
1 year ago
40130
This rule detects activities associated with the SmartLoader malware, including the creation or renaming of specific files (ODE3.exe, Module.class, Lua51.dll) in suspicious user application data directories, the creation or update of scheduled tasks with a specific name ("SecurityHealthService_ODE3"), and the DLL sideloading of "lua51.dll". These activities indicate potential execution, persistence, and defense evasion by the SmartLoader malware.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
0071
This rule detects suspicious activities related to Protected Process Light (PPL) and driver loading that could indicate privilege escalation, defense evasion, or impact. Specifically, it looks for:
1. Processes running with 'System' integrity that were initiated by a process with a lower integrity level, which could suggest an attempt to elevate privileges.
2. Driver image load events where 'ntoskrnl.exe' is the initiating process, but the driver is loaded from a location outside of the standard 'System32' or 'System32\drivers' directories. This could indicate an adversary attempting to load malicious drivers to evade detection or persist.
3. DriverLoad actions initiated by 'ntoskrnl.exe' from outside the standard 'System32' or 'System32\drivers' directories, similar to the image load events, pointing to potential malicious driver activity.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
4051
This rule detects the execution of 'comp.exe' with any command-line arguments. This activity can be indicative of NTLM coercion attempts, where an attacker forces a target machine to authenticate to a malicious server to capture and potentially crack the NTLM hash.
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Luis Zavier Guzman Garcia@KillBillKill98
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Detections.ai Community
1 year ago
3065
This query helps you quickly see the number of affected devices or get a detailed list of machines still running versions that are approaching end of support:

Windows 10 & 11 version 22H2 → end of support on October 14, 2025
Windows 11 version 23H2 (Home & Pro) → end of support on November 11, 2025
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Sergio Albea@Sergio_Albea
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01 | 🇨🇭 Swiss Cyber Hunters
1 year ago
6285
New KSMBD DoS (CVE-2025-38501) can exhaust SMB connections via half-open TCP handshakes — patch to Linux 6.1.15+ or rate-limit TCP/445 to mitigate.
This KQL query helps to hunt for connection attempts to port 445 across Linux endpoints in Defender XDR:
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Sergio Albea@Sergio_Albea
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01 | 🇨🇭 Swiss Cyber Hunters
1 year ago
6054
This rule identifies unusual activity from locations not previously observed for a user within a defined lookback period. It leverages Microsoft Entra ID (Azure AD) Behavior Analytics and SigninLogs to baseline legitimate user locations and filter out trusted devices/IPs. The rule flags unusual activity where the source IP location is new for the user and exceeds a configurable threshold of 'unusual' behavior indicators, while also excluding specified trusted countries.
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Dylan Evans@decksy
Dexter's Laboratory
1 year ago
549595
Detects the creation of a mutex with a pattern matching new SmokeLoader versions (2025 alpha and 2025). The malware's main module is injected into explorer.exe, which then creates this distinct mutex to prevent multiple instances from running.
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Tim Peck@timpeck
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Detections.ai Community
1 year ago
4066
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