Detections

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

3,750 detections

https://www.kaseya.com/blog/dkim-replay-attacks-apple-paypal-invoice-abuse/
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Steven Lim@KQLWizard
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SlimKQL 2026
9 months ago
400265
This rule detects emails delivered to an inbox that contain URLs identified as malicious by OpenPhish, indicating a successful phishing attempt or delivery of a known malicious link.
Azure Sentinel@AzureSentinel
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AzureSentinel
9 months ago
541648
This rule detects instances where users click on URLs from emails that impersonate 'DocMagic'. It specifically looks for emails with 'docmagic' in the sender display name or address, extracts URLs from these emails, and then identifies if any of these URLs were subsequently clicked by users. This indicates a potential successful phishing attempt related to the DocMagic impersonation campaign.
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Information hacker@Informationhacker
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Detections.ai Community
9 months ago
9085
Detects anomalous Exchange Transport Rule activity: high volume changes, suspicious patterns, or after-hours modifications
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nomit vyas@xoxo
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Detections.ai Community
9 months ago
5075
Detects file access or download activity from SharePoint or OneDrive where the user agent is PowerShell. This TTP has been associated with UNC6671 (related to ShinyHunters) for data exfiltration from SaaS applications.
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nomit vyas@xoxo
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Detections.ai Community
9 months ago
150171
This rule detects potential phishing activity by identifying inbound emails from specific sender addresses that were not blocked by Microsoft Defender for Office (MDO), followed by network connections to a known malicious infrastructure associated with 'Tycoon2FA'. The rule first looks for unblocked emails from 'donotreply@docmagic.com' and 'noreply@frigoarrobba.com.br'. If such emails are found, it then checks for network connections to 'listener.facraivo.sa.com' within a 7-day window, indicating a potential compromise or user interaction with the phishing attempt.
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Steven Lim@KQLWizard
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SlimKQL 2026
9 months ago
251259
Detects network connections to the Microsoft Graph API (graph.microsoft.com) from processes that are not common Microsoft Office applications. Threat actors, such as those behind the FINALDRAFT malware, have been observed using the Graph API for covert command and control (C2) communications, often by manipulating email drafts to send and receive commands. This allows them to blend their traffic with legitimate enterprise activity.
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J Hunt@jhunt
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Detections.ai Community
9 months ago
2092
Detects file access or download operations from Microsoft SharePoint Online where the User-Agent string indicates the use of PowerShell. This behavior has been observed in campaigns by threat groups for bulk data exfiltration.
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g host@ghosty
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Detections.ai Community
9 months ago
242358
This query hunts for inbound emails that contain URLs embedded in QR codes and originate from senders that are not commonly observed in the environment, a common technique used in QR-based phishing campaigns.
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Andre Zeemering@Azeemering
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Detections.ai Community
9 months ago
141231
This query hunts for network activity and other events related to specific domains (freefoodaid.com, wellnessmedcare.org) potentially associated with CVE-2026-21509. It searches DNS queries, network connections, generic web proxy/firewall logs, and URL click events to identify interactions with these domains.
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J W@JW404
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Detections.ai Community
9 months ago
190123
This rule detects Microsoft Teams chat or call activity initiated by external users whose domains are not present in a pre-defined whitelist. It specifically looks for 'ChatCreated' or 'CallParticipantDetail' actions from external users and filters out activity from known, whitelisted external domains. This can help identify potentially unauthorized or suspicious external communication within Microsoft Teams.
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Rudra Verma@Rudraverma
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CyberHawk Consultancy
9 months ago
3077
This query parses the complex JSON parameters of the New-TransportRule and Set-TransportRule commands to find instances where email is being secretly copied externally or security is being lowered.
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Daniel Miller@dxmiller
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Detections.ai Community
9 months ago
170128
This query uses the Machine Learning series_decompose_anomalies function to build a baseline of "normal" transport rule modification behavior. If your organization typically changes 0 rules a week, and suddenly 5 are changed at 2 AM on a Saturday, this query will catch it regardless of what the parameters are.
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Daniel Miller@dxmiller
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Detections.ai Community
9 months ago
10083
This rule detects chat or call activity by external users in Microsoft Teams whose source tenant is not present in a pre-defined whitelist. This could indicate unauthorized external communication or potential data exfiltration attempts.
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Rudra Verma@Rudraverma
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CyberHawk Consultancy
9 months ago
171106
This KQL check for email links that were clicked/ email attachment that were opened before recall
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Udi B@Udi
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Detections.ai Community
9 months ago
352257
Detects emails containing threat-actor lure links to trojanized ScreenConnect MSI files, specifically targeting 'cld.pt' downloads with 'COMPROBANTE*.msi' patterns. The rule also looks for 'COMPROBANTE' keywords in email subjects as a fallback.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
9 months ago
284278
This rule detects instances where a SharePoint or OneDrive file/folder is shared with a guest user whose email address is identified as a threat intelligence indicator. This could indicate an attempt to exfiltrate data to a known malicious entity or an account compromise being used for data staging.
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Bartosz Turek@turekbar
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Detections.ai Community
9 months ago
190118
Detects when a suspicious process (such as a script interpreter or LOLBIN) is executed from a directory configured as a Microsoft Office Trusted Location. Attackers may place malicious executables or scripts in these locations to bypass security controls and execute them, often as a result of a user opening a malicious document.
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Paul P@ppritch
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Detections.ai Community
9 months ago
130102
This rule detects a multi-stage attack chain starting with a high-confidence phishing email, followed by a risky sign-in from the recipient, and culminating in sensitive actions within Azure, specifically targeting IAM role assignments, storage account key access, or AKS cluster modifications. The detection correlates these events within a defined time window to identify potential compromise of cloud resources originating from a successful phishing attack.
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Mehulkumar Savajani@Msavajani
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Detections.ai Community
9 months ago
8082
This rule tracks and deduplicates alert emails from a Managed Security Service Provider (MSSP). It identifies emails from a specific sender, filters by subject keywords (e.g., severity levels), and groups them into sessions to prevent duplicate alerts. It also extracts case numbers from portal URLs found within the emails.
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Nicholas Isakson@nisakson2000
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Detections.ai Community
9 months ago
5059
This rule detects suspicious activity related to mailbox access within Office 365. It has two main parts: 1) Identifies users accessing a high number of unique mailboxes belonging to other users. 2) Identifies users accessing a high number of unique folders within another user's mailbox. Both scenarios can indicate unauthorized access, data exfiltration attempts, or compromised accounts.
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Mehulkumar Savajani@Msavajani
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Detections.ai Community
9 months ago
476404
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