Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,605 detections
Filters
Last updated
All Time
Detection languages
495
433
214
119
105
Contributors
403
350
248
92
65
Categories
20,440
11,814
5,871
5,145
4,864
1,605
Platforms
860
775
236
213
66
Products / Services
469
348
348
319
208
MITRE Techniques
726
541
453
167
163
CVEs
6
5
2
2
2
IDS Classtypes
235
83
34
19
18
IDS Protocols
283
56
51
16
12
This rule detects indicators of compromise (IOCs) associated with the 'ManualFinder/PDF Editor' malware campaign. It identifies malicious activity across multiple data sources, including file hashes, process hashes, suspicious certificate signers, suspicious company names in version info, suspicious file descriptions, malicious command execution, and network connections to known command and control (C2) or malicious PDF-related domains. The rule leverages external data sources for IOCs such as file hashes, C2 domains, PDF-related domains, suspicious signers, and malicious commands. It also includes static IOCs like specific file descriptions and company names. The detection logic is designed to identify various stages of the malware's activity, from initial execution to network communication.
Detects DNS queries to landing pages associated with the PDF Editor.exe & OneStart.
The following analytic detects processes attempting to connect to known IP check web services. This behavior is identified using Sysmon EventCode 22 logs, specifically monitoring DNS queries to services like "wtfismyip.com" and "ipinfo.io". This activity is significant as it is commonly used by malware, such as Trickbot, for reconnaissance to determine the infected machine's IP address. If confirmed malicious, this could allow attackers to gather network information, aiding in further attacks or lateral movement within the network.
The following analytic detects the execution of a DNS query by a process to the associated Telegram API domain, which could indicate access via a Telegram bot commonly used by malware for command and control (C2) communications. By monitoring DNS queries related to Telegram's infrastructure, the detection identifies potential attempts to establish covert communication channels between a compromised system and external malicious actors. This behavior is often observed in cyberattacks where Telegram bots are used to receive commands or exfiltrate data, making it a key indicator of suspicious or malicious activity within a network.
This rule detects an unusually high volume of DNS queries originating from a single device within a one-hour window. This behavior can be indicative of various malicious activities such as DNS tunneling for command and control, data exfiltration, or extensive reconnaissance.
This rule detects DNS queries to known malicious domains by joining IdentityQueryEvents with ThreatIntelligenceIndicator data. It specifically looks for matches between the queried domain (QueryTarget) and known malicious domains (DomainName) from threat intelligence feeds.
This hunting query detects potential abuse of the MS-RPC protocol for DoS/DDoS attacks by monitoring outbound LDAP-related DNS queries originating from Domain Controllers.
It is inspired by the SafeBreach “Win-DOS Epidemic” research, which revealed a technique where attackers abuse RPC calls to trigger massive LDAP query floods. The query flags high-volume _ldap queries to external (non-private) IPs, with extra scrutiny on processes like lsass.exe and svchost.exe that, if abused, may indicate system-level compromise or protocol exploitation.
The detection is filtered to DC naming conventions (DC*) to reduce false positives and maintain high fidelity.
Stage 1 logic integrated from SlimKQL.
It is inspired by the SafeBreach “Win-DOS Epidemic” research, which revealed a technique where attackers abuse RPC calls to trigger massive LDAP query floods. The query flags high-volume _ldap queries to external (non-private) IPs, with extra scrutiny on processes like lsass.exe and svchost.exe that, if abused, may indicate system-level compromise or protocol exploitation.
The detection is filtered to DC naming conventions (DC*) to reduce false positives and maintain high fidelity.
Stage 1 logic integrated from SlimKQL.
This rule consolidates multiple detections related to a widespread malspam campaign delivering the Nova infostealer. It hunts for activity across email, network, DNS, and firewall logs associated with known malicious domains, IPs, and specific TTPs like suspicious archive attachments from impersonated brands.
Detects DNS query requests to Devtunnels domains. Attackers can abuse that feature to establish a reverse shell or persistence on a machine. Devtunnels can be used for command and control or data exfiltration by tunneling traffic over legitimate-looking DNS requests.
Detects unusual domain resolutions originating from CScript/WScript that can identify malicious javascript files executing in an environment, often as a result from a phishing or watering hole attack.
Detects DNS requests to Cloudflared tunnels domains. Attackers can abuse this feature to establish a reverse shell or persistence on a machine.
Detects DNS queries for domains known to be used by the DarkCloud campaign for payload delivery and C2 communication. This rule specifically targets domains used for initial payload download, final payload delivery, and public IP address determination.
Detects DNS queries to domains that are suspiciously similar to trusted ones, which may indicate typosquatting, phishing, or user deception tactics. The detection compares unknown domains to a known safe allowlist using a fuzzy character-difference heuristic.
Detects DNS lookups to common Tor proxy gateways such as tor2web and onion.* mirrors. These domains are often used to proxy access to hidden services from non-Tor browsers and are frequently used by threat actors for staging, data exfiltration or ransomware payments.
Detects DNS queries to a command and control (C2) domain used by the AK47C2 backdoor, which is part of the Project AK47 toolset associated with the CL-CRI-1040 (Storm-2603) threat actor.
This analytic detects DNS queries to domains associated with known remote access software such as AnyDesk, GoToMyPC, LogMeIn, and TeamViewer. This detection is crucial as adversaries often use these tools to maintain access and control over compromised environments. Identifying such behavior is vital for a Security Operations Center (SOC) because unauthorized remote access can lead to data breaches, ransomware attacks, and other severe impacts if these threats are not mitigated promptly.
This rule detects network connections and DNS queries to domains impersonating legitimate services, which are known to be used in the Epsilon Red ransomware campaign to deliver malicious HTA files.
Detects DNS requests to Cloudflared tunnels domains.
Attackers can abuse that feature to establish a reverse shell or persistence on a machine.
Attackers can abuse that feature to establish a reverse shell or persistence on a machine.
Detects DNS query requests to Devtunnels domains. Attackers can abuse that feature to establish a reverse shell or persistence on a machine.
The following analytic identifies DNS queries to known TOR proxy websites, such as "*.torproject.org" and "www.theonionrouter.com". It leverages Sysmon EventCode 22 to detect these queries by monitoring DNS query events from endpoints. This activity is significant because adversaries often use TOR proxies to disguise the source of their malicious traffic, making it harder to trace their actions. If confirmed malicious, this behavior could indicate an attempt to obfuscate network traffic, potentially allowing attackers to exfiltrate data or communicate with command and control servers undetected.
Identifies DNS queries to non-standard ports, often used for DNS tunneling or C2. **Validation**: High - DNS to non-53 ports is rarely legitimate.
Page 68 of 77