Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule identifies risky sign-in attempts in Azure Active Directory where the sign-in originates from an IP address that has not been seen before or has been seen fewer than 3 times in the last 29 days for that specific user. It filters out guest users, non-compliant devices, and unmanaged devices, focusing on sign-ins with an aggregated risk level greater than 1 and a sign-in risk level of 50 or higher. Excluded applications are specified to reduce false positives.
Detects attempts to exploit multiple vulnerabilities (CVE-2025-52905, CVE-2025-52906, CVE-2025-52907) in TOTOLINK X6000R routers. Attackers can leverage argument injection, unauthenticated command injection, and security bypasses through the '/cgi-bin/cstecgi.cgi' endpoint to achieve remote code execution or denial of service.
Detects a suspicious sequence where a JavaScript file is executed, followed shortly by the execution of a Windows Installer (MSI) package on the same host. This pattern is consistent with the initial access technique used by threat actors like Lunar Spider, where a malicious script downloads and runs a subsequent payload.
This KQL query analyzes Microsoft Entra ID (formerly Azure AD) sign-in and audit logs to identify potentially risky multi-factor authentication (MFA) registration events. It works by checking for MFA registrations initiated from a new, previously unseen IP address.
The query joins historical sign-in data with recent MFA-related events. It calculates how many unique days an IP address has been used by a specific user over the last 30 days. It then flags any MFA registration event from the last 24 hours where the IP address is a new IP (seen zero days before). The final results are filtered to exclude events from new user accounts (created in the last 60 days) to focus on more established accounts.
The query joins historical sign-in data with recent MFA-related events. It calculates how many unique days an IP address has been used by a specific user over the last 30 days. It then flags any MFA registration event from the last 24 hours where the IP address is a new IP (seen zero days before). The final results are filtered to exclude events from new user accounts (created in the last 60 days) to focus on more established accounts.
Detects the creation or modification of a GitHub Actions workflow file that attempts to exfiltrate secrets. This pattern is associated with the Shai-Hulud worm, which injects malicious workflows to steal credentials using `toJSON(secrets)` and exfiltrate them using tools like `curl` and `base64`.
Detects exploitation attempts against common network edge devices (Cisco, Ivanti, Palo Alto) associated with Salt Typhoon's TTPs for initial access.
Detects attempts to bypass authentication in Fortra GoAnywhere MFT by exploiting a vulnerability (CVE-2025-10035). This is achieved by sending a crafted GET request to the Unlicensed.xhtml endpoint to trigger an exception and obtain a valid license request token, which is a prerequisite for further exploitation.
This detection rule identifies potential SEO poisoning activity associated with the Operation Rewrite campaign. It looks for a high volume of web requests from a single source IP where the HTTP referrer indicates the traffic originated from a search engine. This pattern can indicate a compromised host being used for malicious purposes or a user interacting with multiple poisoned search results.
This rule detects phishing attempts by identifying emails containing URLs and endpoint network connections to domains known to be associated with phishing campaigns. It leverages an external Indicator of Compromise (IOC) list of phishing domains. The rule scans email events for inbound messages with URLs matching these domains and also monitors endpoint network events for successful connections or HTTP inspections to these malicious domains. The results from both email and endpoint sources are then combined to provide a correlated view of potential phishing activity.
Detects LESLIELOADER, a Go-based malware loader used by the Chinese state-sponsored group RedNovember (TAG-100, Storm-2077) to deliver payloads such as SparkRAT and Cobalt Strike.
Detects a PowerShell process launch shortly after a .LNK file was created by Discord. This pattern is indicative of malicious LNK files distributed via Discord to gain initial execution.
KQL Query from file: Endpoint SMB Exposed on Public Internet
Detects BadIIS malware variants associated with the 'Operation Rewrite' campaign (CL-UNK-1037). This rule identifies the native IIS module, PHP backdoors, and other related components used for SEO poisoning.
Detects the creation of Chrome extension files (.crx) that match known malicious extension IDs. Malicious CRX files on endpoints can indicate an attacker dropped or installed a malicious extension (e.g., credential harvesters, redirectors, miners). The rule flags CRX creation with known bad IDs and requires available file hashes for further investigation.
Malicious NPM Package Version Download
Cortex XDR
This rule detects the download or installation of known malicious NPM package versions by monitoring process command-line arguments for specific package names and versions. It targets common package managers like npm, yarn, and pnpm, as well as node.exe, to identify instances where a compromised or intentionally malicious package is being introduced into a development or production environment.
Detects a user authorizing a Salesforce application via the '/setup/connect' page. This specific TTP is associated with ShinyHunters vishing campaigns where attackers impersonate IT staff and trick employees into entering a connection code, thereby granting a malicious application access to the organization's Salesforce environment.
This rule detects network connections initiated by a process with a command line containing "filesystem", "--json", and "--results=verified", which is used to scan the entire filesystem.
This specific combination of command-line arguments is associated with the Shai-Hulud malware.
This specific combination of command-line arguments is associated with the Shai-Hulud malware.
This rule detects potential malware infections and command and control activity by correlating email, endpoint file, and network events with indicators of compromise (IOCs) sourced from an external OSINT feed. It specifically looks for SHA256 hashes in email attachments, domains and URLs in email links, MD5, SHA1, and SHA256 hashes of created files on endpoints, and IP addresses and domains in network connections (both direct and HTTP inspected connections). The rule aims to identify initial access, execution, and command and control phases of an attack, potentially involving Cloudflare Tunnels as suggested by the rule's title and the OSINT source.
here we go with another quick and dirty one to detect Phishing Urls in Emails listed on phishunt.io Feed.
Recommended Action move to Junk Mail Folder or Delete the Message
Recommended Action move to Junk Mail Folder or Delete the Message
This rule detects network connections to known EvilGinx phishing infrastructure, identified by specific remote URLs, IP addresses, and a suspicious login URL pattern. EvilGinx is a phishing framework used for credential harvesting and session cookie theft, often employing adversary-in-the-middle techniques.
This rule detects the creation of an executable file (.exe) that is being extracted by an archive where the command line includes 'tar -xzf' and a '.tar.gz' archive.
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