Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential insider threats or departing employees by correlating abnormal bulk data downloads from cloud repositories (SharePoint/OneDrive/Box/etc.) with subsequent sensitive data access and exfiltration signals. It uses baseline behavioral profiling, requires a threshold of sensitive file interactions, and mandates high-confidence exfiltration indicators (removable media usage, suspicious external domains, or multiple combined destination events) to reduce noise. Archive/staging activity is used as an optional confidence booster.
This rule detects scenarios where a user completes a device-code authentication flow, followed immediately (within 10 minutes) by the registration of an unmanaged, non-compliant device to their account. This behavior is indicative of potential token theft (e.g., EvilTokens) where an adversary uses a stolen token to register their own device as a persistent, unmanaged entity, bypassing standard corporate device enrollment controls.
Detects the 'auto-exfil' pattern associated with the TeamFiltration tool. The rule identifies a sequence of SharePoint Online file access immediately followed by a Microsoft Graph token request from the SharePoint Online Web Client Extensibility app. To reduce noise, it mandates a very short time delta between events (<= 60 seconds) combined with either the use of an IP address/ASN not previously seen for the account in the last 14 days, or a preceding failed sign-in attempt for the account.
Detects a suspected account compromise sequence where an account first authenticates to a Microsoft Teams application from infrastructure associated with TeamFiltration (e.g., specific AWS ranges), followed by a rapid (within 2 minutes) authentication to a VPN or SAML service provider from a different IP address, indicative of an account pivot.
Detects the TeamFiltration/UNK_CondorFiltration spray signature: a large
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
Detects a sequence of activity where a user receives a high volume of inbound emails (potential vishing or social engineering lures) within a short window, followed by the user executing Windows Remote Assistance or Quick Assist tools within the next 6 hours, which is highly indicative of remote access social engineering pre-cursors.
The following analytic identifies when an O365 email account sends and then hard deletes an email to an external recipient within a short period (within 1 hour).
This behavior may indicate a compromised account where the threat actor is attempting to remove forensic artifacts or evidence of exfiltration activity.
This behavior is often seen when threat actors want to reduce the probability of detection by the compromised account owner.
This behavior may indicate a compromised account where the threat actor is attempting to remove forensic artifacts or evidence of exfiltration activity.
This behavior is often seen when threat actors want to reduce the probability of detection by the compromised account owner.
Detects anomalous, high-volume reconnaissance activity against multiple Microsoft Graph API endpoints (users, groups, roles, authentication methods, service principals, sites, and drives) by a single identity within a one-hour window. This behavior is indicative of post-compromise enumeration, often associated with threats like UNC6671/Storm-3121.
This rule detects a multi-stage Business Email Compromise (BEC) attack involving executive impersonation via look-alike domains, followed by the creation of suspicious inbox rules (forwarding/deletion) by the victim, and concurrent external communication (Teams/Zoom meeting invites) from a newly created account. It correlates these activities to identify sophisticated payment fraud campaigns.
Detects the reuse of a session or refresh token within a short timeframe (<= 900 seconds) where the source IP location, device identifier, or User-Agent string has materially changed. This behavior is indicative of Adversary-in-the-Middle (AiTM) attacks, where a session cookie has been stolen and replayed from an attacker's infrastructure to hijack a legitimate user's session.
Detects malicious AI assistant links delivered via spearphishing emails that contain pre-populated prompt injection query parameters. The rule correlates the clicking of a high-signal URL (containing parameters like prompt, system, or lengthy search queries with malicious keywords) originating from an email with a subsequent active session to the same AI service within 5 minutes, confirming potential weaponized AI assistant session manipulation. Covers T1566.002, T1204.001
Detects anomalous, high-frequency, multi-channel probing of AI agent input surfaces. The rule identifies external actors sending instruction-injection style keywords across different communication channels (e.g., email, Teams, calendar) within a short window, which may indicate an attempt to identify and manipulate an organization's autonomous agents. Covers T1595.002
A documented FileFix variant arrives as an HTML/MHTML email attachment styled to look like a Word document or PDF, displaying a fake 'file could not be rendered' prompt that leads into the address-bar paste.
This rule detects potentially malicious search activity in Microsoft SharePoint by monitoring for high-frequency queries that include specific site class patterns ('STS_Site' or 'STS_Web') and a document ID range search pattern ('indexdocid'). This behavior is characteristic of an adversary attempting to enumerate or scrape documents within a SharePoint environment.
Detects automated mailbox monitoring (mailbox access cadence) followed by searches for sensitive finance-related keywords (e.g., invoice, payment, wire, ACH). This pattern is characteristic of a 'Box Monitor' or 'Inbox Monitor' actor, which maintains persistence via API polling to exfiltrate financial information from a compromised account.
Detects potential Adversary-in-the-Middle (AiTM) activity by identifying a successful interactive MFA-protected sign-in followed within 15 minutes by a non-interactive (refresh token) sign-in for the same user from a different IP address, ASN, or User-Agent. This pattern is indicative of session hijacking where an attacker reuses a stolen session token.
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
This rule monitors for high-frequency download or access events of files associated with AI development, such as model weights (.pt, .ckpt, .safetensors, .h5, .onnx, .pkl, .pb), checkpoints, and research datasets from cloud storage. It triggers when an account accesses or downloads 20 or more unique AI-related files within a 60-minute window, which is indicative of unauthorized data exfiltration of intellectual property.
Detects potential Business Email Compromise (BEC) by monitoring inbound email threads for unexpected changes in the sender domain during ongoing conversations. This rule flags replies that contain payment-related keywords (e.g., IBAN, SWIFT, bank details) where the sender domain has not been observed in the previous 30 days of the thread's history.
Detects known file hashes associated with SideCopy/ReverseRAT.
This rule monitors for indicators of compromise (IOCs) associated with the threat actor SideCopy and their associated malware, such as ReverseRAT. It hunts for specific malicious SHA256 file/process hashes, connections to known malicious C2 infrastructure (IPs and domains), requests to known malicious URLs, and user interaction with these URLs via email clicks.
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