Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The below Sentinel KQL analytics rule is able to detect potential privilege escalation to Global Admin role via compromised service principal
This rule helps you find files that may be part of the EmEditor watering hole incident by looking for a small set of very specific clues that were described in public reporting. It searches for lookalike website names and a repeated campaign marker that appeared in the attacker’s network paths. A match does not automatically prove malware, but it is a strong hint that the file should be reviewed, especially if it is a script, configuration, or installer related content. If you get a hit, confirm where the file came from and whether it is expected for that machine. If it is unexpected, save the file for analysis, check for other related downloads, and look for signs of credential theft or surveillance activity. Also search for the same marker across endpoints, because campaigns often reuse the same identifier on multiple victims. The intent is to give defenders an easy, reliable starting point for triage using human readable clues.
Detects instances where 'nslookup.exe' is initiated by 'explorer.exe'. This activity can be indicative of an adversary performing DNS queries for reconnaissance or command and control (C2) staging, especially when not part of a legitimate administrative script or user action. The rule excludes a common false positive related to conhost.exe.
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.
Detects Booking.com partner phishing kit artifacts described by Bridewell (op_token complaint lures, tpo_token sign-in flow, booklng subdomain, punycode homograph infra).
Detects the execution of osascript to display a deceptive dialog box mimicking 'System Preferences' to harvest user passwords. This technique was observed being used by the Atomic Stealer (AMOS) malware.
Detects suspicious network connections to 'outlook-one.vercel.app' or 'api.telegram.org' when initiated by common web browsers (msedge.exe, chrome.exe, firefox.exe) or Outlook (outlook.exe). This pattern can indicate phishing attempts, credential harvesting, or data exfiltration via Telegram bots.
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 a sequence of macOS system profiling and software update commands associated with the UNC1069 'ClickFix' social engineering ruse, often followed by a payload download via curl piped to a shell.
Detects TruffleHog credential validation via sts:GetCallerIdentity - initial access indicator for AWS WorkMail phishing campaigns
Detects a sequence of system reconnaissance commands followed by data exfiltration to temp.sh, a TTP used in the Notepad++ supply chain attack.
This rule detects sign-in attempts to Azure Active Directory (AAD) service principals where the User-Agent string contains "TruffleHog". TruffleHog is an open-source tool used for finding sensitive data (like credentials) in various data sources. Its presence in AAD sign-in logs, especially for service principals, could indicate an attempt to scan for or verify leaked secrets or credentials associated with service accounts.
This rule detects when known code scanning tools like Trufflehog, Gitleaks, or Gittyleaks attempt to read the AWS credentials file. This activity could indicate an adversary or an internal security tool searching for sensitive AWS access keys and tokens.
Azure Device Code OAuth Consent
Cortex XDR
This rule detects suspicious activity related to Microsoft 365 Device Code OAuth consent flows. It specifically looks for device code authentications that are single-factor or lack MFA, and then groups these by IP address and client application. The rule identifies suspicious patterns such as a high number of logins, unique users, or unique applications from a single IP address, or rapid login attempts within a short timeframe, which could indicate enumeration or phishing attempts.
This rule detects potential malicious email campaigns by identifying when multiple users submit email reports (e.g., phishing or spam) that share common entities such as sender IP, primary sender address/domain, secondary sender address/domain, or subject line. A configurable threshold determines the minimum number of distinct reports required to flag an entity as suspicious.
This rule query identifies likely post‑exploitation activity associated with React2Shell (CVE-2025-55182) in which Part 1 identifies web servers spawning unusual child processes (such as command shells or system utilities) combined with suspicious command-line patterns, which may indicate post-exploitation behavior following a compromise. and part 2 detects web servers making outbound network connections to known malicious IPs or hostnames, or to domains associated with tunneling services (e.g., trycloudflare.com), suggesting potential command-and-control activity or data exfiltration.
This alert finds sessions where a device-code flow produced multiple sign-in events (interactive + non-interactive), with mismatched user-agents or differing country/geolocation, for the same Session ID - a strong indicator of device-code phishing abuse.
Looks for:
Brute-forcing device code tokens
Token replay attempts
Malicious use of device code authentication across different devices or locations
Anomalous sign-in behaviour suggesting account compromise
Looks for:
Brute-forcing device code tokens
Token replay attempts
Malicious use of device code authentication across different devices or locations
Anomalous sign-in behaviour suggesting account compromise
Detects the installation of specific NPM packages that have been identified as compromised by the Shai-Hulud "Second Coming" worm. Installation of these packages can lead to credential theft and further propagation of the malware.
Detects network connections to dedicated IP addresses previously used to host Evilginx phishing proxies. While the threat actor has reportedly shifted to using Cloudflare, these IPs represent past infrastructure and should be monitored for potential reuse.
This rule set detects several indicators of compromise related to the Shai-Hulud threat activity. It identifies specific malicious file hashes (SHA256) for 'bundle.js' files, the execution of the 'trufflehog' tool which is often abused for secrets discovery, the presence of a malicious YAML file named 'shai-hulud-workflow.yml', and network connections to 'webhook.site' domains, optionally with a specific URI, which are used for data exfiltration or command and control.
Detects a high volume of Microsoft Teams invitation emails sent to multiple users within the organization. This could indicate a reconnaissance attempt or a widespread phishing campaign where an attacker is trying to lure users into a malicious external tenant, bypassing some internal security controls.
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