Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
135 detections
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Detects the installation of a DNS plugin DLL via ServerLevelPluginDll parameter in registry, which can be used to execute code in context of the DNS server (restart required)
Detects DNS queries to known OAST (Out-of-Band Application Security Testing) domains like oastify.com, oast.pro, and oast.fun where the subdomain is unusually long (over 50 characters). Long subdomains may indicate encoded data exfiltration, a technique observed in the exploitation of vulnerabilities like CVE-2026-1731 to bypass egress filtering.
Detects DNS queries for subdomains that match a specific pattern used by the threat actor GS7. The actor uses a semi-automated infrastructure with highly specific subdomain naming conventions, such as 'rss.[random]-auth.com' or 'cpcalendars.[random]-verify.online', to host phishing pages and payloads.
NKN is a networking service using blockchain technology to support a decentralized network of peers. While there are legitimate uses for it, it can also be used as a C2 channel. This rule looks for a DNS request to the ma>
Identifies clients that may be performing DNS lookups associated with common currency mining pools.
DNS TOR Proxies
Sigma
Identifies IPs performing DNS lookups associated with common Tor proxies.
Detects unexpected file modifications by 'dns.exe', which could indicate remote code execution or other exploitation, specifically referencing CVE-2020-1350 (SigRed). The rule filters out modifications to 'dns.log' to reduce false positives.
The following analytic detects the use of default or publicly known named pipes associated with Cobalt Strike. It leverages Sysmon EventID 17 and 18 to identify specific named pipes commonly used by Cobalt Strike's Artifact Kit and Malleable C2 Profiles. This activity is significant because Cobalt Strike is a popular tool for adversaries to conduct post-exploitation tasks, and identifying its named pipes can reveal potential malicious activity. If confirmed malicious, this could indicate an active Cobalt Strike beacon, leading to unauthorized access, data exfiltration, or further lateral movement within the network.
Detects DNS queries containing specific base64-encoded patterns ("UWhRCA" and "BAAAA") that are indicative of Kerberos coercion attacks via DNS object spoofing. This technique involves manipulating DNS records to spoof Service Principal Names (SPNs) and redirect authentication requests, forcing victim systems to authenticate to attacker-controlled hosts. This is a strong indicator of a Kerberos coercion attack, potentially related to vulnerabilities like CVE-2025-33073, where a marshaled CREDENTIAL_TARGET_INFORMATION structure is used.
Detects an unexpected file deletion by the dns.exe process. This activity could indicate remote code execution or other forms of exploitation, potentially related to vulnerabilities like CVE-2020-1350 (SigRed), where an attacker might manipulate DNS server files.
Detects a DNS server error indicating that a specified plugin DLL, configured in the registry, could not be loaded. This event can be triggered by an attacker attempting to load a malicious DLL for privilege escalation or persistence on a DNS server, often associated with techniques like DNSAdmin to DC compromise.
Detects an unexpected process spawning from dns.exe, which may indicate activity related to remote code execution or other forms of exploitation, specifically referencing CVE-2020-1350 (SigRed). The rule filters out legitimate child processes like conhost.exe.
This rule detects a DHCP server error where a specified Callout DLL, configured in the registry, could not be loaded. This event can indicate an attempt to inject a malicious DLL into the DHCP server process for persistence, privilege escalation, or defense evasion.
Detects the installation of a DNS plugin DLL via ServerLevelPluginDll parameter in the registry using dnscmd.exe, which can be used to execute code in the context of the DNS server (restart required). This technique can be used for privilege escalation or persistence.
This analytic detects suspicious data transfer activities involving the use of the `split` syscall with the `-b` option, which specifies the size of each output file. This technique can be used by attackers to evade detection by breaking large files into smaller parts, bypassing size-based security controls, and facilitating covert exfiltration of sensitive data. By monitoring for unusual or unauthorized use of the `split` syscall with a specified block size, this analytic helps identify potential data exfiltration attempts.
This analytic identifies the bulk creation of ransomware notes (e.g., .txt, .html, .hta files) on an infected machine. It leverages Sysmon EventCode 11 to detect multiple instances of these file types being created within a short time frame (10 seconds). A detection is triggered if 15 or more unique readme paths are observed. This activity is a strong indicator of an active ransomware attack, where the attacker is notifying the victim of the encryption. If confirmed malicious, this behavior could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
The following analytic detects suspicious attempts to find credentials stored in password stores, indicating a potential attacker's effort to access sensitive login information. Password stores are critical repositories that contain valuable credentials, and unauthorized access to them can lead to significant security breaches. By monitoring for unusual or unauthorized activities related to password store access, this analytic helps identify potential credential theft attempts, allowing security teams to respond promptly and prevent unauthorized access to critical systems and data.
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.
The following analytic detects the creation of files in the Windows %startup% folder, a common persistence technique. It leverages the Endpoint.Filesystem data model to identify file creation events in this specific directory. This activity is significant because adversaries often use the startup folder to ensure their malicious code executes automatically upon system boot or user logon. If confirmed malicious, this could allow attackers to maintain persistence on the host, potentially leading to further system compromise and unauthorized access to sensitive information.
The following analytic identifies the creation of executables or scripts in suspicious file paths on Windows systems. It leverages the Endpoint.Filesystem data model to detect files with specific extensions (e.g., .exe, .dll, .ps1) created in uncommon directories (e.g., \windows\fonts\, \users\public\). This activity is significant as adversaries often use these paths to evade detection and maintain persistence. If confirmed malicious, this behavior could allow attackers to execute unauthorized code, escalate privileges, or persist within the environment, posing a significant security threat.
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