Detections

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

40,063 detections

Detects potential pass-the-hash activity through NTLM network logons (Type 3). The rule identifies anomalies such as mismatched workstation names relative to the source computer or NTLM authentication using zero key length material, which is often indicative of automated lateral movement attempts bypassing standard authentication processes.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
001
Detects the execution of potentially malicious processes originating from common mail client attachment cache directories, the use of suspicious double extensions in file names, or common command-line interpreters being spawned by Microsoft Office applications, which are high-confidence indicators of phishing or malicious document exploitation.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
001
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
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Arnold Chan@slaz
Defender - KQL
1 month ago
000
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
000
Detects ScreenConnect client processes initiating outbound network connections to external cloud relay addresses (typically *-relay.screenconnect.com) from locations outside of standard Program Files directories. This behavior is indicative of unauthorized, standalone, or adversary-deployed ScreenConnect instances attempting to establish a Command and Control (C2) channel, bypassing standard IT-managed deployment pathways.
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Arnold Chan@slaz
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Hunters
1 month ago
000
Detects the creation of ransom or extortion note files within known web server directories immediately following suspicious HTTP activity targeting an internet-facing host. This pattern aligns with known ShinyHunters extortion tactics where applications are exploited to deploy extortion notes.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
Detects the deployment and activity of the MeshCentral remote management agent (meshagent), including process execution, service creation, and network communication to MeshCentral infrastructure. This behavior is indicative of unauthorized persistence and remote command-and-control, often associated with post-compromise activity such as that observed by ShinyHunters.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
Detects the execution of TruffleHog, an automated secret-scanning CLI tool, often utilized by threat actors to harvest sensitive credentials from local filesystems, repositories, environment variables, or CI/CD configuration files following unauthorized access.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
Detects the execution of the GigaWiper malware or the use of common system commands associated with destructive data activities, such as recursive file removal, disk formatting, or secure data overwriting, often used by threat actors for extortion.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
Detects the installation or first execution of common remote monitoring and management (RMM) software, specifically AnyDesk, TeamViewer, or ScreenConnect, shortly after an identity change or MFA reset event, indicative of social engineering vishing-to-remote-access techniques often employed by threat actors such as Scattered Spider (UNC3944).
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
Detects anomalous network traffic patterns characteristic of the PetitPotam exploit, specifically targeting the MS-EFSRPC interface on Windows SMB pipes. This behavior is used to force a remote system to initiate authentication to a specified target, facilitating NTLM relay attacks.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
001
Detects NTLM authentication attempts targeting administrative network shares (ADMIN$ or C$) over the SMB protocol. This behavior is a common indicator of lateral movement techniques such as Pass-the-Hash, where an adversary uses captured NTLM hashes to authenticate to remote systems.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
001
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
101
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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Arnold Chan@slaz
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Hunters
1 month ago
001
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
001
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
001
This rule detects various malicious indicators including known file hashes, IP addresses, domains, and specific URLs associated with threat activity. It consolidates hits from process, file, and network telemetry to alert on potential compromise or communication with identified command-and-control (C2) infrastructure.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
001
Detects network connections to known ChatGPT Custom GPT ClickFix campaign infrastructure (IPs and URLs) as reported by Huntress. This rule covers the network_connection logsource only. Domain/DNS matching is covered by a separate dns_query rule, and file-hash matching is covered by a separate process_creation rule, as Sigma only supports one logsource per rule.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
001
Detects the use of the sc.exe command-line utility to stop or disable the Microsoft Defender Antivirus service (WinDefend). This activity is often associated with ransomware, such as Nova ransomware, to bypass security controls prior to malicious encryption or data destruction.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
105
Detects attempts by malicious software to inhibit system recovery by deleting Volume Shadow Copies. The rule monitors for the execution of vssadmin.exe with deletion flags or wmic.exe with shadowcopy deletion commands combined with non-interactive flags, which are common indicators of ransomware preparation.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
205
Detects the use of PowerShell to modify Microsoft Defender exclusion paths by adding root drive letters or temporary directory paths. This behavior is indicative of defense evasion techniques often employed by ransomware families, such as Nova or Gentlemen, to prevent the scanning of files immediately prior to encryption.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
305
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