Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects access or modification of cloud provider credential and configuration files by common script interpreters or code editors (python, node, vscode), which may indicate credential theft or misuse by an adversary.
Detects instances where scripting processes (Python, Node.js) accessed SSH key files or configuration files and subsequently initiated an outbound network connection within 60 seconds, which may indicate potential exfiltration of credentials or unauthorized access.
Detects rapid high-volume file and messaging operations across multiple Microsoft 365 services (SharePoint, OneDrive, Teams, Exchange) within a compressed 10-minute window from a single identity and IP address. This behavior can indicate data exfiltration or reconnaissance by an adversary.
Detects SNMP bulk walk used to collect network device configurations
Detects manipulation of data in transit via man-in-the-middle position
Detects SNMP enumeration using default community strings
Detects broad assignments of administrative roles or specific deletion permissions for cloud storage buckets in GCP, AWS, and Azure. This includes granting 'storage.admin', 'storage.objectAdmin', or 'storage.buckets.delete' in GCP, 's3:DeleteBucket' in AWS IAM policies, or 'Storage Account Contributor'/'Owner' roles in Azure. Such assignments to service accounts or non-administrative identities could enable 'Universal Bucket Hijacking' or unauthorized data deletion.
Detects indicators of the Meow RAT malware staging collected data in the /tmp/shub_ directory, compressing it into shub_log.zip using 'ditto', and subsequently exfiltrating it to a hardcoded command and control (C2) domain 'qwqerrqwr2145qw[.]com/gate'. The rule correlates process events, network events, and file events to identify the full attack chain.
Detects rapid high-volume file and messaging operations across multiple Microsoft 365 services (SharePoint, OneDrive, Teams, Exchange) within a compressed 10-minute window. This behavior can indicate data exfiltration or collection by an adversary.
Identifies the creation of an Exchange transport rule or mailbox setting that forwards all incoming emails to an external, attacker-controlled address.
Detects non-browser processes accessing sensitive browser data files (such as Login Data, Cookies, or key stores) followed by network activity to known suspicious, cryptocurrency, or potential malware-hosting domains. This behavior is indicative of credential theft and exfiltration by information-stealing malware.
Detects access, copying, or creation of files within common cryptocurrency wallet directories, as well as registry lookups related to Bitcoin data directories. This behavior is often indicative of info-stealing malware or an adversary attempting to exfiltrate digital currency assets from a compromised host.
This rule detects instances where specific processes (CefSharp.BrowsersSubprocess or SCef.WindowsAdapter) modify the clipboard content with strings matching common cryptocurrency wallet address patterns. This behavior is indicative of clipboard hijacking, where an adversary replaces a user's copied wallet address with their own to facilitate fraudulent transactions.
Detects the creation of sequentially numbered JPEG files within timestamped subdirectories of C:\Users\Public\Videos. This activity is consistent with the behavior of the SIGHTGRAB utility, a tool used by the threat actor UNC1549 for intelligence gathering through automated desktop screenshots.
Detects potential Browser-in-the-Middle (BitM) phishing activity by identifying a client browser that fetches the 'rrweb' session-recording library followed by a WebSocket connection to a different origin within 5 minutes. This sequence is indicative of an attacker-controlled browser streaming the victim's DOM and interaction events to a phishing infrastructure.
Detects MFA authentication success from one IP address followed immediately by a session access attempt from a different IP address. This pattern is characteristic of Adversary-in-the-Middle (AiTM) phishing attacks, such as those using EvilProxy, Evilginx2, or similar phishing-as-a-service (PhaaS) platforms, where an adversary proxies the authentication flow to capture session tokens.
Detects execution of sensitive administrative binaries (rm, chmod, chown) targeting critical system files or directories, or direct interaction with sensitive system files and configuration logs which may indicate unauthorized data access or evidence tampering.
Detects unauthorized access to sensitive credential and configuration files associated with AI development tools (Cursor, Claude, Gemini) and cloud providers (AWS, GCP) by the Miasma worm, which seeks to steal environment configuration and authentication data.
Detects anomalous WebSocket connections on web pages that utilize the 'rrweb' session replay library, often used by phishing infrastructure such as the Bluekit Browser-in-the-Middle (AiTM) kit to capture and relay real-time victim input (keystrokes and mouse movements) to attacker-controlled consoles.
Detects the creation of ZIP/RAR/7z archives by processes residing within the Turla STOCKSTAY installation directory (%LOCALAPPDATA%\Programs\SMN\) or by known STOCKSTAY malicious components. This behavior is associated with the STOCKSTAY 'Get' command, which gathers files and archives them in-memory for base64-encoded exfiltration.
Detects the execution of known Turla STOCKSTAY/STOCKTRADER backdoor components (ConverterDDSNet.exe or SMEditor.exe) which are used to perform unauthorized screen capture and data exfiltration from the victim's host.
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