Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This detection identifies instances where a user grants consent to an OAuth application that has very low prevalence within the tenant and requests high-risk permissions. This pattern is a strong indicator of a targeted consent phishing attack, as malicious apps often target a small number of users to gain initial access.
Detects when a user generates an unusually high number of prompts to Copilot within a short period (e.g., 50 prompts in an hour). This could indicate automated activity, data exfiltration attempts, or misuse of the Copilot service.
This rule detects instances where a 'jailbreak' attempt is identified within a Microsoft Copilot interaction. It specifically looks for CopilotInteraction events where the 'JailbreakDetected' flag is set to true in the message data.
This rule detects instances where Microsoft Copilot accesses external resources, specifically identifying events where 'XPIADetected' is true. This indicates Copilot interacting with resources outside its immediate environment, which could be a security concern if the accessed resources are sensitive or untrusted.
Detects the creation of an unusual lock file at `/usr/share/nano/.lock`. This specific path is used by a backdoored Go module (impersonating golang.org/x/crypto) to temporarily store harvested plaintext passwords before exfiltration. The rule specifically looks for file creation events at this highly specific path.
Detects actions performed on RiskyUsers in Azure Entra ID by unauthorized
members. Specifically looks for CA or GA accounts performing IdentityProtection
actions where the admin is not from the Information Security department.
Note: String parsing (AdminLocalPart, AdminLastName, StrippedAdminName),
fallback identity matching, summarize arg_max, and project are handled
natively in KQL post-conversion.
members. Specifically looks for CA or GA accounts performing IdentityProtection
actions where the admin is not from the Information Security department.
Note: String parsing (AdminLocalPart, AdminLastName, StrippedAdminName),
fallback identity matching, summarize arg_max, and project are handled
natively in KQL post-conversion.
Detects when a user grants consent to an application that has not been seen in the environment before. This rule baselines known applications over a 30-day period and alerts on any new application consent grants or service principal additions within the last day that are not part of the baseline or an explicit allow list.
This rule detects successful sign-ins to Microsoft 365 services that occur via legacy authentication protocols. These protocols (e.g., Exchange ActiveSync, IMAP4, POP3, SMTP AUTH) do not support modern authentication methods like Multi-Factor Authentication (MFA) or Conditional Access policies, making them a potential bypass vector for adversaries who have compromised user credentials. The rule identifies the user, the specific legacy client application used, and provides details on the source IP address and country.
This rule detects phishing attempts related to a Booking.com campaign. It identifies suspicious URLs containing 'op_token' or 'tpo_token' parameters, often combined with paths like 'complaint' or 'reserv', on non-Booking.com domains. It specifically looks for punycode domains (e.g., 'xn--*'), lookalike domains (e.g., '*booklng*', '*mgmnt*', '*portal*'), and specific high-signal punycode domains identified in reports. The rule also includes a pattern for partner kit redirect URLs with 'tpo_token' on 'booklng' subdomains. Additionally, it suggests looking for specific email patterns from Gmail senders with subjects like 'Automatic reply', 'Availability', or 'Reservation' that contain embedded URLs matching 'complaint?op_token='.
This rule detects a potential quishing (QR code phishing) attack followed by a suspicious successful sign-in to Entra ID (formerly Azure AD). It correlates URL click events or device network events containing deep link indicators (like 'tg://login', 'wa.me/settings/linked_devices', 'signal://', 'line://') or '.apk' file downloads with a successful Entra ID sign-in by the same user within a 30-minute window. This behavior suggests a user may have scanned a malicious QR code, clicked a phishing link, or downloaded a malicious application, leading to a successful but potentially compromised authentication.
This rule detects various indicators associated with the Booking.com phishing campaign targeting hotels and customers. It identifies suspicious web requests to non-Booking.com domains containing 'op_token' and 'complaint' or 'reservation' keywords, especially when combined with punycode, 'booklng' typos, or management-related subdomains. It also looks for partner kit patterns involving 'sign-in/?tpo_token=' and 'booklng' in URLs. Additionally, it identifies suspicious emails from newly generated Gmail accounts with specific subjects ('Automatic reply', 'Availability', 'Reservation') containing 'op_token' in the subject or body.
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 communication with external entities.
This rule detects network connections or email URLs that match a list of known Indicators of Compromise (IOCs) associated with Signal-targeted phishing infrastructure and explicit phishing destination domains. These IOCs were identified in Unit 42's research on QR code attack vectors. The rule queries email URL information, URL click events, device network events, and common security logs (proxy/firewall/WAF) to identify activity related to these malicious domains.
This rule identifies accounts receiving the most email and highest threat exposure by analyzing inbound email events. It counts total emails, delivered emails, junked emails, blocked emails, and specifically highlights emails with detected threats (Phish, Malware, Spam) that were successfully delivered to the user's inbox. The output is sorted to prioritize accounts with the highest number of delivered threats.
Detects potential spam campaigns originating from disposable or trial Jira Cloud instances with randomized subdomain names. The rule identifies emails from '.atlassian.net' domains where the subdomain is longer than 12 characters and contains a mix of letters and numbers, indicating a potentially randomized or disposable instance. It then alerts if more than 5 emails with the same subject are sent from such a suspicious subdomain.
Detects incoming emails from Atlassian Jira domains (atlassian.net) that contain suspicious link redirectors or known Traffic Distribution Systems (TDS) like Keitaro. This activity is associated with a campaign where threat actors abuse Jira's trusted domain to send spam and phishing emails.
This rule detects emails originating from Atlassian Jira (specifically the .atlassian.net domain) that contain subject lines associated with a known spam campaign. The campaign uses various lures, including investment scams and online casinos, across multiple languages.
Detects incoming emails from Atlassian Jira Cloud subdomains where the subject line matches known spam patterns used in a campaign abusing the service's reputation.
This rule detects suspicious user-agent strings in Microsoft Graph activity logs that are commonly associated with reconnaissance and attack tools targeting Azure AD and Microsoft 365 environments. These tools include BloodHound, ROADtools, AADInternals, and various other utilities used for enumeration, credential spraying, and other malicious activities.
Domains that introduce substitutions, extra characters, or randomness (e.g., micr0soft, paypa1-secure) tend to have higher entropy than the original brand name. This increase in entropy is a useful signal for detecting typosquatting and brand impersonation attempts in phishing campaigns.
Detects the creation or modification of Exchange inbox rules that move messages to potentially risky folders (e.g., Deleted Items, Junk Email, RSS Feeds, Archive, Clutter) or are configured to delete messages. This behavior can be indicative of an attacker attempting to hide malicious emails, exfiltrate data, or disrupt email flow.
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