Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

4,230 detections

Detects directory brute force tools like Gobuster, ffuf, feroxbuster
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Darshan Thummar@Mighty
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Detections.ai Community
4 months ago
002
Detects browsers loading external anomalous scripts from known malvertising domains while visiting plaintext HTTP sites (Router injection). This rule specifically looks for network connections on port 80 (HTTP) that are joined with device network events where the remote URL matches a regex for known malvertising domains (.xyz, .top, .site) and ends with '.js', indicating an injected script.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
208
Detects the multi-stage execution chain associated with the Gamaredon group's PteroEffigy loader. The rule monitors for PowerShell or scriptrunner instances originating from suspicious directories (AppData/Temp) that employ .NET reflection to load DLLs into memory. It then detects the subsequent creation of a scheduled task with a random alphanumeric name and the eventual execution of regsvr32 or rundll32 by that task to load the malicious DLL. Additionally, the rule identifies potential command-and-control activity by detecting specific Kazuar malware HTTP User-Agent strings.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects many unique, high-entropy URL paths that each receive a small number of requests before redirecting to authentication. This behavior is indicative of adversaries like Volt Typhoon (Tycoon) using one-time session paths for each victim in phishing campaigns.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
4 months ago
208
Detects a user navigating to the Microsoft devicelogin portal immediately after clicking a link from an email, a precursor to Device Code OAuth phishing.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
706
This rule monitors network logs (from proxies and firewalls) for web traffic (HTTP GET requests) containing suspicious JavaScript code injection patterns in the request context or message fields. It specifically looks for common XSS indicators such as <script tags, eval(), document.write(), fromCharCode(), and atob().
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
002
Detects a single source issuing at least eight HTTP PUT requests to five or more distinct Ghost Admin post objects within a ten-minute window. This activity is indicative of the Ghost ClickFix attack chain, which involves mass modification of blog posts.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
4 months ago
1010
Detects non-browser HTTP POST requests containing both 'access_token' and step-style parameters (e.g., 'step', 'stage', 'counter' followed by a number) in proxy or firewall telemetry. This rule specifically targets patterns associated with malware communication, such as SessionGate, Remus, or AnimateClipper, by excluding common browser user agents.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
4 months ago
1010
Detects curl.exe where system metadata is concatenated into User-Agent/Referer fields with specific delimiters.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
008
Detection rule monitoring for indicators of compromise related to SolarWinds Serv-U, including anomalous Content-Encoding headers, unexpected child process execution, large file staging indicative of data exfiltration (Cl0p-style), outbound exfiltration, SQL injection artifacts, and unauthorized LDAP/Active Directory object enumeration by the Serv-U process.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
002
This rule monitors Cisco Unified Communications Manager (UCM) environments for multiple stages of an attack chain, including potential Server-Side Request Forgery (SSRF) attempts against administrative interfaces, suspicious file modifications by service accounts, indicators of privilege escalation, and anomalous outbound network connections from core Cisco processes.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
002
Detects a specific two-step HTTP pattern characteristic of OysterLoader's initial C2 communication. The malware first sends a registration request containing a 'WordPressAgent' User-Agent string, followed by a login request with a 'FingerPrint' User-Agent string to the same destination. This version checks for the User-Agent strings in the 'AdditionalFields' column.
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nomit vyas@xoxo
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Detections.ai Community
4 months ago
306
Infostealer distributed via fake open-source tool impersonation sites
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
Supply chain worm targeting npm packages and GitHub Actions, linked to Shai-Hulud/Hades lineage
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
IoT botnet malware family used for DDoS and proxy infrastructure
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
ClickFix style social engineering cluster delivering Mistic and ModeloRAT
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
Infostealer-as-a-service targeting browser credentials and crypto wallets
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
Fraud framework powering scam domains for crypto and gambling schemes
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
AI-powered phishing-as-a-service abusing device-code authentication
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
000
Fraud framework powering scam domains for crypto and gambling schemes
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
Form-grabbing and credential stealing malware-as-a-service
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
000
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