Detections

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

3,750 detections

This rule detects a correlation between an email phishing burst (high volume of emails with a specific failed payment subject) and the subsequent creation of suspicious 'x_trace_' files in 'var/report/' directories. This pattern is indicative of a phishing campaign where a malicious attachment or link might be attempting to write local tracking or diagnostic files on a victim's host.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
2 months ago
001
Detects high-volume phishing emails that utilize subjects claiming extreme discounts (e.g., 65% off) and contain links to domains ending in the .shop top-level domain (TLD). The rule correlates email subjects with URL domains and alerts when multiple recipients are targeted by the same sender/domain combination.
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Arnold Chan@slaz
Defender - KQL
2 months ago
000
Detects inbound emails masquerading as reputable advisory firms (PwC or KPMG) using lookalike sender domains, combined with wire-transfer fraud phrases in the subject line. Correlates with identity logon telemetry for the same fraudulent WhatsApp Business phone number, enabling detection across both email and authentication channels. Note: message body content is not available in the EmailEvents schema, so fraud-phrase matching is subject-only.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
000
Detects inbound emails masquerading as reputable advisory firms (PwC or KPMG) using lookalike sender domains, combined with wire-transfer fraud phrases in the subject line. Correlates with identity logon telemetry for the same fraudulent WhatsApp Business phone number, enabling detection across both email and authentication channels. Note: message body content is not available in the EmailEvents schema, so fraud-phrase matching is subject-only.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
000
Detects forged NDA documents used in Phantom Deal M&A fraud campaign, requiring co-occurrence of impersonated advisory firm branding, secrecy-clause language restricting communication to personal channels, and M&A-fraud-specific wire/payment indicators rather than secrecy-clause phrasing alone
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
000
This rule monitors for inbound external emails where the sender requests private communication (e.g., 'private email' or 'personal address') in combination with keywords related to sensitive business topics like M&A, legal, or urgent financial transactions. This pattern is characteristic of Business Email Compromise (BEC) or social engineering attempts designed to move sensitive conversations outside of monitored corporate channels.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
000
Detects potential Business Email Compromise (BEC) related to 'Phantom Deal' fraud. The rule identifies email threads where a user receives an urgent request for proof of payment (MT103/UETR) within 72 hours of an email discussion involving both wire transfer/payment keywords and M&A/deal context.
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Arnold Chan@slaz
Defender - KQL
2 months ago
000
Detects potential Business Email Compromise (BEC) related to 'Phantom Deal' fraud. The rule identifies email threads where a user receives an urgent request for proof of payment (MT103/UETR) within 72 hours of an email discussion involving both wire transfer/payment keywords and M&A/deal context.
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Arnold Chan@slaz
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Detections.ai Community
2 months ago
000
Detects inbound emails containing keywords associated with known ransomware extortion tactics (e.g., mention of specific ransomware names, data leaks, and payment demands). The rule filters for inbound traffic to identify external threats while excluding potential internal-generated traffic.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
001
Detects anomalous email access patterns across multiple mailboxes using specific application identifiers or access contexts often associated with automated collection tools. This rule flags when an application accesses more than 20 items across distinct mailboxes in a 15-minute window, which is indicative of potential unauthorized bulk email collection or data exfiltration.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
101
Detects anomalous access to Microsoft 365 services (OneDrive, SharePoint, Mail) where the user activity is characterized by a high volume of operations (more than 30) across a diverse set of objects (more than 15) within a one-hour window. The detection focuses on activity originating from specific common automation/scripting User-Agents (Microsoft Graph, Python httpx/requests) that deviate from typical, focused service account behavior.
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Arnold Chan@slaz
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Midnight Slayer
2 months ago
101
Detects successful Azure AD sign-ins where the user agent identifies as a Python requests library version (2.33.1 or 2.34.2) that has not been observed for that specific user account in the preceding 14 days. This behavior is indicative of anomalous automated or scripted access.
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Arnold Chan@slaz
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Detection & Hunting Community
2 months ago
001
This rule detects suspicious, high-volume file access or download operations in SharePoint and OneDrive. It filters for activities performed by specific user agents commonly associated with automated scripting tools (e.g., python-requests, Microsoft.Graph.Client), which indicates potential automated exfiltration or unauthorized bulk data collection.
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Arnold Chan@slaz
Defender - KQL
2 months ago
001
This rule monitors Office 365 SharePoint file operations and search queries for patterns indicative of automated discovery and exfiltration of sensitive content. It specifically identifies high-frequency search queries involving wildcard parameters used in SharePoint content indexing, which may suggest an adversary is systematically crawling or enumerating organizational documents.
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Ankit Mehta@Secvyn
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Detection & Hunting Community
2 months ago
000
Detects cloud application events originating from suspicious or specific User-Agent strings, including 'python-requests' and identified outdated or potentially spoofed Chrome versions (146, 150, 151.0.0). This behavior often correlates with automated scripts or bot activity interacting with cloud services.
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Ankit Mehta@Secvyn
Defender - KQL
2 months ago
000
Detects cloud application events originating from suspicious or specific User-Agent strings, including 'python-requests' and identified outdated or potentially spoofed Chrome versions (146, 150, 151.0.0). This behavior often correlates with automated scripts or bot activity interacting with cloud services.
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Ankit Mehta@Secvyn
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Hunters
2 months ago
000
Detects a user performing a high volume of SharePoint site discovery queries within a one-hour window. This behavior often indicates an adversary attempting to map site structures and discover content across an organization's SharePoint environment.
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Ankit Mehta@Secvyn
Defender - KQL
2 months ago
000
Detects a user performing a high volume of SharePoint site discovery queries within a one-hour window. This behavior often indicates an adversary attempting to map site structures and discover content across an organization's SharePoint environment.
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Ankit Mehta@Secvyn
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Detection & Hunting Community
2 months ago
000
Detects a user performing a high volume of SharePoint site discovery queries within a one-hour window. This behavior often indicates an adversary attempting to map site structures and discover content across an organization's SharePoint environment.
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Ankit Mehta@Secvyn
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Hunters
2 months ago
000
This rule monitors Office 365 SharePoint file operations and search queries for patterns indicative of automated discovery and exfiltration of sensitive content. It specifically identifies high-frequency search queries involving wildcard parameters used in SharePoint content indexing, which may suggest an adversary is systematically crawling or enumerating organizational documents.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
000
Detects high-frequency access to mail items or attachments using specific One Outlook Web Client AppIDs. This behavior may indicate automated mailbox harvesting or unauthorized bulk data access via an atypical API path.
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Ankit Mehta@Secvyn
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Detections.ai Community
2 months ago
000
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