Detections

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

1,735 detections

Detects incoming emails processed by Rspamd that exhibit suspicious authentication header signatures. The rule identifies emails lacking DKIM, ARC, or user agent information while simultaneously showing a zero receive count, potentially indicating spoofed, unauthenticated, or malformed phishing attempts.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
This rule monitors network traffic, DNS queries, and user web clicks to detect interactions with known malicious domains associated with credential harvesting and phishing campaigns, specifically those impersonating security or SSO portals.
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Arnold Chan@slaz
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Hunters
2 months ago
17031
This rule detects potential OAuth token theft resulting from device code phishing (e.g., N0va phishkit). It monitors for a successful OAuth device-code authentication followed within 5 minutes by a secondary successful sign-in for the same user from a different IP address, different browser client, or different user agent, which is a common indicator of an adversary-in-the-middle (AiTM) session hijacking attempt.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
009
This rule detects phishing emails where the sender's display name impersonates well-known brands (e.g., Microsoft, DocuSign, Zoom) while using a non-official domain. It further correlates these suspicious senders with embedded URLs that either match the targeted brands' domains or contain patterns commonly associated with device code phishing or API verification workflows.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
209
Detects phishing emails containing lures that direct users to the Microsoft device login portal to enter an attacker-supplied code. The rule correlates the delivery of these emails with subsequent successful device-code based authentication events, identifying potential token theft via the OAuth device code flow.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
004
Detects inbound emails containing an '.r01' attachment (often associated with multi-part RAR archives) where both SPF and DMARC authentication checks have failed, and the email subject implies business-related themes like purchase orders or supply chain communication. This pattern is indicative of a spearphishing attempt.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
104
Detects downstream delivery of likely AI-paraphrased mass-produced lure content by identifying bursts of near-duplicate subject lines from newly-seen domains with auth failures.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
001
Detects downstream delivery of likely AI-paraphrased mass-produced lure content by identifying bursts of near-duplicate subject lines from newly-seen domains with auth failures.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
101
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
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Arnold Chan@slaz
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Midnight Slayer
1 month ago
001
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
001
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
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Arnold Chan@slaz
Defender - KQL
1 month ago
001
Detects bursts of AI-paraphrased, brand/executive-impersonating email lures delivered to the inbox: clusters near-duplicate subject-line variants from the same sending domain within a 6-hour window, and requires a corroborating signal (authentication failure or a sender domain first seen within the last 14 days) plus an ESP allow-list exclusion to avoid flagging legitimate bulk/newsletter mail. Maps to T1683 (Generate Content) as the downstream-delivery proxy for AI-generated lure content.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
001
Detects phishing attempts leveraging SendGrid infrastructure to send emails that impersonate well-known financial brands. The detection looks for emails with authentication checks passing (SPF/DKIM/DMARC) where the sender domain is suspicious (e.g., .asia or .com not matching the brand) and the volume of such messages suggests an automated campaign.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
This rule identifies potential Apple iCloud phishing attempts by monitoring web proxy logs for requests containing specific indicators of a spoofed 'Find My' page. It specifically looks for URLs that include '/help?' combined with keywords like 'Find Devices', 'Geräte finden', 'icloud', or 'findmy', which are common markers for malicious phishing landing pages attempting to harvest user credentials.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
This rule detects anomalous network traffic patterns characteristic of the JWR phishing framework. It identifies live, operator-driven exfiltration where an attacker issues specific instruction sequences (e.g., to_card, to_sms, to_2fa) via HTTP polling or WebSockets to facilitate the character-by-character capture of sensitive information like payment card details and OTPs from a victim.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
This rule monitors DeviceNetworkEvents and DnsEvents for connections to known malicious domains and IP addresses associated with phishing campaigns. It alerts on any network communication or DNS resolution attempt targeting these indicators, providing visibility into potential user interaction with phishing infrastructure.
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Ankit Mehta@Secvyn
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Detection & Hunting Community
1 month ago
002
This rule monitors DeviceNetworkEvents and DnsEvents for connections to known malicious domains and IP addresses associated with phishing campaigns. It alerts on any network communication or DNS resolution attempt targeting these indicators, providing visibility into potential user interaction with phishing infrastructure.
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Ankit Mehta@Secvyn
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SlimKQL
1 month ago
002
This rule monitors DeviceNetworkEvents and DnsEvents for connections to known malicious domains and IP addresses associated with phishing campaigns. It alerts on any network communication or DNS resolution attempt targeting these indicators, providing visibility into potential user interaction with phishing infrastructure.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects phishing emails masquerading as legitimate DocuSign remittance advice notifications. The rule identifies emails containing specific keywords related to PDF sharing or remittance advice originating from 'docusign' and featuring suspicious, alternating-case hyperlinks often used in credential phishing campaigns.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
This rule detects phishing emails associated with the 'AnonyMousKIT' campaign that spoof Apple-related services ('Find My', 'Apple Support') using common adversary-controlled Gmail/iCloud addresses. The rule specifically targets institutional recipients in .gov, .edu, and .ac domains, identifying potential credential harvesting attempts despite the campaign's original consumer-focused pretext.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
This rule monitors email traffic for attachments with suspicious file types (.htm, .xhtml, .svg, .zip) or specific filenames commonly used in phishing campaigns. It focuses on emails associated with Amazon SES infrastructure, often indicative of phishing attempts leveraging reputable infrastructure to deliver malicious content or stager files.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
001
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