Detections

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

1,598 detections

Detects scenarios where an attacker attempt to hide emails in order to perform phishing attacks by replacing, for example, financial information from the original email with another email containing attacker's financial information. This technique may also be used to avoid specific email notification to be received by end users in case, for example, of an ongoing breach.
SIGMA Detection Rules@SIGMADetectionRules
SIGMA Detection Rules
1 year ago
009
Detects suspicious OAuth app consents, role assignments, and group changes involving Workday and Salesforce, indicating potential account compromise or privilege escalation.
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Tun Tun Naing@tuntun
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Detections.ai Community
1 year ago
80180
This detection identifies network connections to domains that may be impersonating ConnectWise or ScreenConnect for credential harvesting purposes. The logic is based on tactics observed in the MCTO3030 campaign which used domains with specific country-code TLDs or generic "connectwise" and "screenconnect" themes.
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test User@testuser007
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Detections.ai Community
1 year ago
60105
This detection identifies suspicious use of wreply or redirect_uri parameters in ADFS or Microsoft login URLs. Attackers can abuse these parameters to redirect users to non-Microsoft domains after authentication, a technique commonly referred to as ADFSjacking.
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Awais Munir@iawais
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Detections.ai Community
1 year ago
55142
In May 2025, a campaign started using the Microsoft Exchange Direct Send feature to send phishing mails to organizations. This feature is designed for use by printers, scanners, cloud services and other devices that need to send messages on behalf of the company. This detection rule tries to detect the malicious mails being send via Direct Send using a couple of indicators:

- Sender email is the same as Recipient email
- SPF and DMARC both failed
- Mail is not comming in via an Exchange connector
- The sender IP address country is not a country that the user is known to login from

FYI, if you remove the country check (last line of the query), you can use the query to identify if there are legitimate mails as well. If not, you can disable the Direct Send feature in Exchange Online.
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Robbe Van den Daele@RobbeVdDaele
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Detections.ai Community
1 year ago
213295
This rule identifies users who have clicked on specific URLs that are known to be associated with phishing attempts. It correlates email URL information with URL click events to pinpoint users who interacted with malicious links shared via email. This is particularly useful for identifying victims of targeted phishing campaigns.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
8086
This rule identifies logon attempts on any device within 30 minutes of a user receiving an email categorized as malware, phishing, or spam. It correlates email event data with identity logon events to detect potential compromise scenarios where a user might interact with a malicious email and subsequently log on, possibly indicating a successful initial access or credential compromise.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
2085
This rule identifies users who clicked on URLs within emails from a specific sender. It correlates email events, URL information, and URL click events to pinpoint which users interacted with links in emails, particularly useful for tracking responses to potential phishing attempts from a compromised account.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
3080
This rule identifies inbound emails that have been delivered to the organization's email domain and are categorized as 'Phishing' by the email security system. It specifically looks for phishing indicators within the email's attachment or body. The query then summarizes the count of such emails by their URL domain, sorting them to highlight the most frequent phishing domains. The accompanying Python script demonstrates how to cross-reference these identified URL domains with VirusTotal for further analysis.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
1078
This rule detects inbound emails where the sender's domain contains "microsoft" but does not end with "microsoft.com". This is a common tactic used in phishing attacks to spoof legitimate Microsoft domains, tricking recipients into believing the email is from a trusted source.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
3076
This rule identifies and analyzes user interactions with URLs embedded in emails, specifically focusing on emails that are either inbound or intra-organizational. It determines which users clicked on URLs within these emails and provides a summary of this activity. This analysis is particularly useful in security contexts, where understanding user behavior regarding potentially risky links can help in identifying phishing attacks or other malicious activities.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
5167
This rule identifies emails originating from sender addresses listed in a GitHub-hosted CSV file, which is explicitly named 'North-Korean-Emails'. The rule's purpose is to flag incoming emails that appear to be sent from individuals or entities associated with North Korea, based on the provided list of email addresses. This could indicate potential phishing, espionage, or other malicious activities originating from North Korean threat actors.
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Stiaan van der Watt@st1aan
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Detections.ai Community
1 year ago
6265
This rule detects Tycoon and ODx AiTM phishing activity that bypasses MFA. It matches:

🔹 Network connections to known malicious domains, IP addresses, and URLs.
🔹 Email-URL clicks and Azure AD sign-in events involving those domains or specific malicious application IDs.
🔹 Sign-ins originating from suspect IP addresses or user-agent strings.
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Aamir Muhammad@Aamir
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Detections.ai Community
1 year ago
202209
This query hunts for files shared by a specified malicious sender on user devices. It identifies if attachments from emails sent by the malicious sender have been downloaded, saved, or are present on the user's devices by joining email attachment information with device file events based on the SHA256 hash of the attachment.
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Subash Ghimire@iamsubashg
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Detections.ai Community
1 year ago
1041
Detects indicators of compromise (IOCs) and suspicious OAuth consent activity
linked to the Tycoon/ODx phishing kits. These campaigns impersonate Microsoft
OAuth apps to bypass MFA and harvest Microsoft 365 credentials.
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Aryan Aryan@felon1337
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Detections.ai Community
1 year ago
112126
Hunts for Office 365 emails that contain URLs of popular Monero exchanges or keywords related to Monero wallet addresses. This could indicate phishing attempts, scams, or other illicit activities.
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Venona Front@venonafront
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Detections.ai Community
1 year ago
3133
Detects unusual domain resolutions originating from CScript/WScript that can identify malicious javascript files executing in an environment, often as a result from a phishing or watering hole attack.
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SigmaHQ Detections@sigmaHQ
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SigmaHQ
1 year ago
2029
Detects .lnk (shortcut) files launched by scripting engines (e.g., PowerShell, CMD, WScript) exhibiting suspicious traits like hidden execution, embedded commands, or admin privilege requests. Common in phishing, LOLBin abuse, and initial access.
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Awais Munir@iawais
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Detections.ai Community
1 year ago
50101
This rule detects when an email with a detected threat (e.g., malware, phishing) has an attachment that is subsequently observed on an endpoint device. This indicates that a malicious attachment from an email was downloaded and executed or saved on a device.
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Ahamed Rizvan@ahamedrizvan
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Detections.ai Community
1 year ago
7093
This rule detects instances where an email with identified threats (e.g., malware, phishing) is received and a URL within that email is subsequently clicked by a user. It correlates email threat information with URL click events to identify successful user interaction with malicious links.
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Ahamed Rizvan@ahamedrizvan
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Detections.ai Community
1 year ago
6167
This rule detects instances where a user clicks on a URL within an email, and subsequently, the email is moved to quarantine. This sequence of events suggests that the email was initially delivered, a user interacted with a potentially malicious link, and then a post-delivery security action (quarantine) was taken, indicating a delayed detection of a threat, likely phishing or malware.
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Ahamed Rizvan@ahamedrizvan
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Detections.ai Community
1 year ago
9058
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