Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects potential unauthorized access to Azure Storage Blobs following the retrieval of storage account access keys. It correlates 'ListKeys' API events with subsequent blob access activities from either unrecognized IP addresses or via Shared Access Signature (SAS) tokens, indicating potential credential misuse.
Detects network connections to Bunny CDN infrastructure that contain common URL path indicators associated with phishing, a technique observed in activity attributed to UNC1151 (Ghostwriter).
Detects instances of npm package publication events initiated by known-compromised maintainer accounts (czirker, llxlr). These accounts have been identified as being used to distribute malicious packages, such as leo-aws versions, representing a software supply chain compromise.
Detects phishing attempts leveraging legitimate service redirectors such as Calendly and Google share URLs to deliver malicious photo-themed ZIP archives. The rule identifies suspicious redirect chains to Cloudflare-hosted (.cfd) domains and monitors for specific ZIP filename patterns commonly used in these campaigns to target the hospitality sector.
Detects malicious npm package propagation indicative of the Miasma/Mini Shai-Hulud worm. The rule identifies suspicious patterns in AuditLogs, specifically burst npm publishes by known malicious actors or involving known malicious package names, as well as the use of weaponized GitHub Actions workflows or unauthorized snapshot branches.
This rule detects potentially malicious emails that leverage Calendly as a lure. It looks for emails that pass standard authentication (SPF/DKIM/DMARC) but contain suspicious elements such as URLs redirecting to Calendly or Google, subject lines related to common social engineering themes (complaints, health inspections, etc.), or the presence of ZIP attachments that match common photo/image naming patterns.
This rule detects suspicious emails exhibiting patterns associated with 'authentication laundering' by identifying the combination of legitimate scheduling or redirection links (e.g., Calendly, Google Redirect) with potentially malicious indicators such as zip file links, suspicious .cfd domains, or impersonation of booking management services. It calculates a laundering score based on these features and the health of email authentication signals (SPF/DKIM).
Detects spear-phishing emails associated with Operation DragonReturn, which impersonates the Indian Income Tax Department. The rule identifies specific malicious attachment filenames, suspicious URLs, subject lines, and sender domains commonly used in these campaigns to deliver malicious content.
This rule monitors web request URLs and associated messages for common SQL injection characters and sequences, such as quotes and semicolons. It specifically targets requests involving the 'apiuser' account to identify potential attempts to manipulate or exploit backend database queries.
This rule detects the execution of potential trojanized ManageEngine OpManager MSI installer files (ManageEngine-OpManager.msi or opmanager.msi) by msiexec.exe when initiated by processes other than standard system binaries like explorer.exe, svchost.exe, or msiexec.exe itself. This behavior is indicative of an attacker attempting to execute a malicious installer package, which may be part of a supply chain compromise or an attempt to install a malicious payload masquerading as legitimate software.
Detects malicious npm package behavior where a package uses 'npm pack' and associated script files (e.g., sync-peer.cjs) to download and overwrite its own installed files. This technique is often used in software supply chain attacks to bypass static analysis of the original package tarball by fetching a second, malicious version at runtime.
Detects node.js executing known malicious npm lifecycle scripts (such as install-check.cjs, verify-peer.cjs, sync-peer.cjs, postinstall-run.js, and preinstall.js) often found in node_modules folders. These scripts are associated with the Polymarket Trap supply chain campaign, which leverages malicious npm hooks for initial access or malicious activity within a development environment.
Detects the execution of Node.js or npm processes that reference known malicious transitive npm dependencies or typosquatted packages identified in the Polymarket Trap supply chain campaign, such as 'log-taker' and various 'thirdweb' typosquats.
Detects the execution of Node.js scripts associated with the Polymarket Trap / Trum3it npm supply chain campaign. This rule monitors process launch events for Node.js command lines that include suspicious lifecycle hook scripts (e.g., install-check.cjs, postinstall-run.js) often used by malicious packages to achieve initial code execution on developer machines.
Detects the execution of a malicious npm package ('@withgoogle/stitch-sdk') which uses scope-squatting to impersonate a legitimate library. The rule flags the execution of preinstall scripts that involve references to the malicious exfiltration domain 'stitch-production.org' or the identified maintainer 'maximus-mcmillan', indicating unauthorized credential harvesting.
This rule detects when Microsoft Office applications (Word, Excel, Equation Editor, PowerPoint) spawn common LOLBAS processes such as mshta, wscript, cscript, powershell, or cmd. It includes additional filtering for command-line arguments containing indicators of HTA or RTF exploitation patterns, which are typical of malicious Office documents attempting to execute secondary payloads.
This rule detects potential XML External Entity (XXE) injection attempts by looking for specific XML-related keywords ('<?xml' or 'DOCTYPE') within the URI query string of IIS web server logs. It triggers an alert if three or more such attempts are observed from the same IP address within a one-hour window, indicating a possible automated scanning or attack.
This rule detects an unusually high number of command-line executions containing keywords related to 'dependency' or 'library' and 'update' or 'upgrade' within a one-hour window on a single computer. This behavior could indicate an adversary attempting to modify system components, install malicious libraries, or compromise the software supply chain by frequently updating or upgrading software dependencies.
This rule detects a high volume of file creation events (100 or more within an hour) occurring in common development-related directories such as 'node_modules', 'packages', or 'vendor'. This activity can be indicative of legitimate software development processes like dependency installation or project builds. However, it can also signal malicious activity, particularly if observed on systems not typically used for development, or as part of a supply chain compromise where malicious dependencies are being introduced or built.
This rule detects a high frequency of process creations (Event ID 4688) with command-line arguments containing keywords indicative of software publishing or deployment, such as 'publish', 'deploy', 'artifact', or 'release'. A count of 3 or more such events within a one-hour window from the same computer and account is considered suspicious. This pattern could indicate legitimate CI/CD activities, but also potential abuse of software deployment tools or a software supply chain compromise by an adversary.
This rule detects the creation of 'requirements.txt' or 'pom.xml' files on a system. These files are commonly used in software development projects (Python and Java/Maven, respectively) to manage dependencies and project configurations. Monitoring their creation can help identify legitimate development activities, but also potential malicious actions such as supply chain compromise where an adversary might introduce or modify project dependencies.
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