Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a sequence of events where an account performs a device code flow sign-in, registers or joins a device, and accesses a high volume of files in SharePoint or OneDrive within a 24-hour window. This pattern is commonly associated with adversary techniques abusing device code flows for initial access and registering managed/compromised devices to access sensitive corporate data.
Detects a high volume of Azure Key Vault secret reads or key decryption operations performed by a single caller identity from multiple source IP addresses within a one-hour window, which may indicate credential harvesting or unauthorized access.
Correlates a device code flow sign-in event with bulk file downloads from SharePoint or OneDrive by the same user account within a 1-hour window. This behavior can indicate potential account compromise or misuse where an adversary uses device code phishing to authenticate and subsequently exfiltrate sensitive files.
This rule queries the ExposureGraphNodes table to identify and summarize assets that are configured as internet-facing or exposed to the internet.
Detects outbound network connections to domains associated with the AdFection / Discover-Tech / Controlium threat infrastructure using a Sentinel watchlist, filtering out known browser activity or allowing custom domain lists.
Detects the removal of user accounts from a specific sensitive Microsoft Entra ID group, which may indicate unauthorized group membership changes or potential privilege escalation activities.
Detects a user account that performs a device code sign-in flow followed by the registration of five or more devices with deceptive names (matching patterns like microsoft- or windows-) within a one day timeframe. This behavior can indicate an adversary establishing persistence or attempting tenant resource exhaustion using compromised accounts.
Detects password spraying activity against Azure Active Directory / Microsoft 365 services where a single source IP attempts to authenticate against numerous distinct user accounts with low attempt counts per account and sustained over time, while excluding successful authentication IPs.
Detects potential cloud storage object discovery activity in Azure Blob Storage by identifying anomalous listing or enumeration operations from callers, including high request counts, extensive container access, high failure rates, or anonymous authentication.
Correlates a high-risk or compromised Microsoft Entra sign-in event with a subsequent device registration (Add device or Register device) performed by the same user account within a 3-hour window.
Users who received a delivered phishing email and then signed in from an IP not seen for them in the prior 30 days within 24 hours. Hunting query, not an alert.
Detects endpoint, network, and security log activity matching known indicators of compromise (IOCs) associated with PEERSTITCH / CL-STA-0954, including specific file hashes, IP addresses, and URLs.
Detects an Entra 'Add device' event within 2 minutes after a successful sign-in from an IP never seen for that user in the lookback window, and where the registration originates from that same new IP (rogue device persistence after token replay).
Detects endpoint, network, and security log activity matching known indicators of compromise (IOCs) associated with PEERSTITCH / CL-STA-0954, including specific file hashes, IP addresses, and URLs.
Detects endpoint, network, and security log activity matching known indicators of compromise (IOCs) associated with PEERSTITCH / CL-STA-0954, including specific file hashes, IP addresses, and URLs.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects endpoint, network, and security log activity matching known indicators of compromise (IOCs) associated with PEERSTITCH / CL-STA-0954, including specific file hashes, IP addresses, and URLs.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Detects non-browser Python-based HTTP clients (such as python-requests, python-urllib, aiohttp, or httpx) targeting specific API endpoints (/user, /profile, /order, /upload) while exhibiting indicators of SQL injection or high-volume object ID enumeration.
Identifies devices that have been enrolled within the last 30 days, displaying details such as device name, model, enrollment profile name, and enrollment date.
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