Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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The following analytic detects suspicious usage of BitLockerToGo.exe, which has been observed being abused by Lumma stealer malware. The malware leverages this legitimate Windows utility to manipulate registry keys, search for cryptocurrency wallets and credentials, and exfiltrate sensitive data. This activity is significant because BitLockerToGo.exe provides functionality for viewing, copying, and writing files as well as modifying registry branches - capabilities that the Lumma stealer exploits for malicious purposes. If confirmed malicious, this could indicate an active data theft campaign targeting cryptocurrency wallets, browser credentials, and password manager archives. The detection focuses on identifying BitLockerToGo.exe execution patterns that deviate from normal system behavior.
Detects DNS queries containing patterns associated with Kerberos coercion attacks via DNS object spoofing.
The pattern "1UWhRCAAAAA..BAAAA" is a base64-encoded signature that corresponds to a marshaled CREDENTIAL_TARGET_INFORMATION structure.
Attackers can use this technique to coerce authentication from victim systems to attacker-controlled hosts.
It is one of the strong indicators of a Kerberos coercion attack, where adversaries manipulate DNS records
to spoof Service Principal Names (SPNs) and redirect authentication requests like CVE-2025-33073.
The pattern "1UWhRCAAAAA..BAAAA" is a base64-encoded signature that corresponds to a marshaled CREDENTIAL_TARGET_INFORMATION structure.
Attackers can use this technique to coerce authentication from victim systems to attacker-controlled hosts.
It is one of the strong indicators of a Kerberos coercion attack, where adversaries manipulate DNS records
to spoof Service Principal Names (SPNs) and redirect authentication requests like CVE-2025-33073.
Detects DNS queries containing patterns associated with Kerberos coercion attacks via DNS object spoofing.
The pattern "1UWhRCAAAAA..BAAAA" is a base64-encoded signature that corresponds to a marshaled CREDENTIAL_TARGET_INFORMATION structure.
Attackers can use this technique to coerce authentication from victim systems to attacker-controlled hosts.
It is one of the strong indicators of a Kerberos coercion attack, where adversaries manipulate DNS records
to spoof Service Principal Names (SPNs) and redirect authentication requests like CVE-2025-33073.
The pattern "1UWhRCAAAAA..BAAAA" is a base64-encoded signature that corresponds to a marshaled CREDENTIAL_TARGET_INFORMATION structure.
Attackers can use this technique to coerce authentication from victim systems to attacker-controlled hosts.
It is one of the strong indicators of a Kerberos coercion attack, where adversaries manipulate DNS records
to spoof Service Principal Names (SPNs) and redirect authentication requests like CVE-2025-33073.
Detects abnormal network activity and connectivity issues in Ollama including non-localhost API access attempts and warning-level network errors such as DNS lookup failures, TCP connection issues, or host resolution problems that may indicate network-based attacks, unauthorized access attempts, or infrastructure reconnaissance activity.
Detects DNS query requests to "update.onelaunch.com". This domain is associated with the OneLaunch adware application.
When the OneLaunch application is installed it will attempt to get updates from this domain.
When the OneLaunch application is installed it will attempt to get updates from this domain.
This rule detects potential Domain Generation Algorithm (DGA) activity by analyzing network connection logs. It identifies suspicious domains based on their structure (length, character set) and then filters them using a trigram analysis. Domains with non-repeating trigrams and rare trigrams (not found in a baseline of Alexa Top 1M domains) are flagged as DGA candidates. The rule then joins these candidates back to the original network logs to identify actual connections to these suspicious domains.
The analytic detects instances where `vbc.exe`, the Visual Basic Command Line Compiler, initiates DNS queries. Normally, `vbc.exe` operates locally to compile Visual Basic code and does not require internet access or to perform DNS lookups. Therefore, any observed DNS activity originating from `vbc.exe` is highly suspicious and indicative of potential malicious activity. This behavior often suggests that a malicious payload is masquerading as the legitimate `vbc.exe` process to establish command-and-control (C2) communication, resolve domains for data exfiltration, or download additional stages of malware. Security teams should investigate the process's parent, command-line arguments, and the resolved domains for further indicators of compromise.
This rule identifies DNS lookups associated with common Tor proxies and services. It detects queries for domains ending in '.onion' and various Tor gateway domains (e.g., '.hiddenservice.net', '.tor2web.com', '.tor-gateways.de'). This activity can indicate the use of the Tor network for anonymization, which adversaries may leverage for command and control, data exfiltration, or to obscure their malicious activities.
This rule detects DNS resolution attempts for domains associated with Tor onion services and Tor2web gateways. It specifically looks for DNS queries ending with various Tor-related top-level domains and subdomains, indicating potential use of the Tor network for anonymization or accessing hidden services.
Detects DNS queries to an ".onion" address or other domains associated with Tor routing networks and Tor2web proxies. This indicates potential use of Tor for anonymous communication or access to dark web services.
Zloader Custom DNS C2
YARA-L
Detects Zloader's custom DNS tunneling protocol which uses multiple Base32 encoded subdomains for C2 communication.
This rule detects a high volume of DNS queries (over 50) from a single source IP to a limited number of destination IPs (2 or less) for non-standard domains. It excludes common legitimate domains like microsoft.com, google.com, apple.com, cloudflare.com, akamai.com, and amazonaws.com, as well as queries to private IP ranges. This pattern can indicate DNS tunneling, data exfiltration, or command and control activity.
Detects DNS queries to domains within known low reputation Effective Top-Level Domains (eTLDs). These eTLDs are often associated with malicious activities such as command and control, phishing, or malware distribution. The rule leverages a curated list of suspicious eTLDs, which is updated periodically.
Detects network connections to the 'webhook.site' domain, which is used as an exfiltration endpoint by the 'Shai-Halud' supply chain attack campaign. The risk score is elevated if the specific malicious URL path is observed.
Detects processes potentially related to XillenStealer making outbound network connections or DNS queries for telegram.org. This is indicative of command and control or data exfiltration activity.
Detects DNS resolution of an .onion address related to Tor routing networks
Detects DNS queries to an ".onion" address related to Tor routing networks
This power query is to detect NPM package is downloaded by the user, using the SentinelOne Singularity Power query.
This rule detects network connections to known dynamic DNS (DDNS) subdomains. Adversaries often use dynamic DNS services to maintain persistent command and control (C2) communication channels, as these services allow them to frequently change the IP address associated with a static hostname, making it harder for defenders to block or track their infrastructure. These providers also have established domain reputation, and provide legitimate services making blanket IOC rules impossible. The rule identifies connections to specific DDNS providers such as DuckDNS, No-IP, PublicVM, and others.
Base64 Website Access
YARA-L
Detects a user accessing multiple websites commonly used for Base64 encoding and decoding within a short time frame. This activity could be a precursor to data exfiltration or an attempt to obfuscate malicious commands.
The following analytic detects DNS queries initiated by the Windows AI Platform to domains associated with Hugging Face, a popular provider of machine learning models and services. Monitoring for such DNS requests is important because it can reveal when systems are reaching out to external AI platforms, which may indicate the use of third-party AI resources or the transfer of sensitive data outside the organization’s environment. Detecting these queries helps organizations enforce data governance policies, prevent unapproved use of external AI services, and maintain visibility into potential data exfiltration risks. Proactive monitoring ensures better control over AI model usage and organizational data flows.
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