Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects messages sent or chats created by external/guest users in Microsoft Teams where the sender's name or user ID impersonates IT or support personnel, indicating a potential phishing attempt.
Hunts for newly installed applications in the ClickOnce directory cache signed by self-signed or explicitly untrusted certificates, specifically looking for process creation events where the initiating process is 'dfsvc.exe' and the signature is marked as 'Untrusted'.
Detects messages sent or chats created by external/guest users in Microsoft Teams where the sender's name or user ID impersonates IT or support personnel, indicating a potential phishing attempt.
Detects the Python Imaging Library (PIL) memory leak used to bypass ASLR prior to the JPEG2000 heap overflow. This KQL query specifically looks for syslog messages containing 'cannot identify image file' and 'BytesIO object at 0x', which are indicators of this specific memory leak vulnerability being triggered.
This rule detects any activity within Office 365 logs that includes a 'username' field and then projects a SHA256 hash of a 'file.exe'. While the specific detection logic is incomplete, it indicates an attempt to correlate Office 365 user activity with file execution or manipulation, potentially for forensic analysis or to identify suspicious file interactions.
Detects MFA device registration occurring during a suspicious session heavily focused on HR portal access. This rule correlates MFA registration events with access to HR applications like Workday or ADP within a 10-minute window, indicating potential account takeover or unauthorized access attempts.
Detects anomalous process execution patterns originating from SAP system processes or accounts, such as SAP work processes spawning shell commands, usage of known RCE-related scripts, and privileged accounts like WF-BATCH or TMSADM invoking administrative command-line tools.
Detects unauthorized access attempts to ServiceNow Scripted REST APIs, specifically targeting misconfigured endpoints that do not require authentication. This rule monitors for requests made by the 'guest' user, known malicious IP addresses, or requests missing authorization headers directed at potentially vulnerable APIs like 'related_list_edit'.
Detects session hijacking attempts where a session cookie is used from a different IP address or user-agent immediately following a successful MFA authentication event. This behavior is indicative of an adversary replaying a stolen session token.
This rule detects potentially malicious browser activity by monitoring for Google Chrome outbound network connections to known command-and-control (C2) domains associated with malicious browser extensions (e.g., BadBlocker). It also flags the installation or loading of specific, known-malicious browser extension IDs on endpoints.
Detects potential malicious browser extension activity by correlating internal browser process network connections to suspicious infrastructure (e.g., adblock-for-youtube.com) with subsequent network traffic from the same process PID to third-party domains within 60 seconds of visiting sensitive high-value websites (e.g., login portals, banking). The rule also alerts on any direct network connection to identified malicious exfiltration infrastructure.
This rule detects network connection events where the AutoGen Studio application (identified by its image filename) initiates connections to localhost (127.0.0.1 or ::1) on ports 8080 or 8081. This is typical behavior for the AutoGen Studio web interface or API server running locally.
Detects new app installations, expansions of OAuth scopes, or the addition of collaborators to Slack applications. These activities can indicate an adversary attempting to gain persistent access, escalate privileges, or exfiltrate data from Slack by leveraging malicious or compromised applications.
Detects anomalous, high-volume npm package publication patterns from a single user account within a 5-minute window. This behavior is indicative of automated worm propagation or supply chain attacks using compromised developer tokens, specifically identified by high-frequency 'publish' events.
This rule detects a potential data collection or exfiltration attempt in Microsoft Teams by identifying accounts that have accessed an abnormally high number of messages (more than 100 within a 5-minute window). This behavior may indicate an automated process or a compromised user account attempting to scrape internal communications.
Detects instances where a specific identity or caller triggers Azure Function or Logic App workflows at a high volume (more than 50 successful invocations within a 5-minute window). This threshold may indicate automated exploitation, potential brute-force attempts on API endpoints, or a misconfigured/malfunctioning service causing excessive resource usage.
This rule detects a potential data collection or exfiltration attempt in Microsoft Teams by identifying accounts that have accessed an abnormally high number of messages (more than 100 within a 5-minute window). This behavior may indicate an automated process or a compromised user account attempting to scrape internal communications.
Detects instances where a specific identity or caller triggers Azure Function or Logic App workflows at a high volume (more than 50 successful invocations within a 5-minute window). This threshold may indicate automated exploitation, potential brute-force attempts on API endpoints, or a misconfigured/malfunctioning service causing excessive resource usage.
Detects a single source issuing at least eight HTTP PUT requests to five or more distinct Ghost Admin post objects within a ten-minute window. This activity is indicative of the Ghost ClickFix attack chain, which involves mass modification of blog posts.
Detects successful (HTTP 200) requests to ServiceNow API endpoints (/api/now/) that lack proper authentication, such as requests by the 'guest' user or requests missing authorization headers or session tokens.
This rule detects Windows application crash events (Event IDs 1000 and 1001) specifically for 'NearShare.exe', 'NearbySharing.exe', or 'quickshare.exe' processes. The detection triggers when the crash description contains indicators of memory-related instability, such as access violations, heap corruption, or invalid virtual calls, which may suggest exploitation attempts or service instability.
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