Detections

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

6,537 detections

This rule detects potential DNS tunneling or DNS-based command and control (C2) beaconing. It analyzes DNS query logs for characteristics typical of C2 traffic, such as high subdomain entropy, frequent use of TXT or NULL records, and a high volume of unique subdomains originating from a single source IP address within a 5-minute window.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
002
Detects Git clone or fetch operations targeting bitbucket.org where the requested branch or ref is formatted as a SHA hash. This specific pattern is identified as a potential precondition for exploitation attempts targeting vulnerabilities like Plugin4Shell, where malicious branch names are used to trigger code execution on the server-side.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects Server-Side Request Forgery (SSRF) attempts targeting SonicWall SMA1000 WorkPlace endpoints. The rule monitors both HTTP GET query parameters and HTTP request bodies for patterns indicating attempts to redirect the application to internal loopback addresses or local network ranges (e.g., 127.0.0.1, 169.254.169.254, RFC1918 private subnets).
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
008
Detects a multi-stage phishing attack targeting cryptocurrency users, specifically Ledger wallet holders. The detection identifies an initial request to a Vercel-hosted domain for a BIP-39 wordlist (a common recovery phrase standard) followed by a POST request to a similar Vercel-hosted endpoint, suggesting the exfiltration of a secret recovery phrase.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
005
Detects HTTP POST requests characteristic of the AgtaBackup RAT, specifically exfiltrating browser profiles or system information via the '/api/agents/' endpoint. The rule monitors for established connections targeting this specific URI structure.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects outbound network traffic from internal hosts to external destinations containing a specific, hard-coded User-Agent string (firefox/21.0). This behavior is characteristic of the NeedyMantis malware family, which utilizes this string to identify its own C2 communications, and is a strong indicator of compromise.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Identifies NetScaler ADC or Gateway software versions in the inventory that are known to be vulnerable to CVE-2026-88771 and CVE-2026-88772, despite having received the patch for CVE-2026-19490.
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Arnold Chan@slaz
Defender - KQL
1 month ago
004
This rule detects potentially malicious Command and Control (C2) traffic utilizing DNS over HTTPS (DoH) to interact with public resolvers like Cloudflare, Google, and Quad9. It identifies both high-frequency, repeated direct-to-resolver TLS sessions and specific HTTP requests to these resolvers that resolve domains associated with known C2 infrastructure, such as the ClickFix campaign.
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Arnold Chan@slaz
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Hunters
1 month ago
003
This rule detects network communication with known malicious infrastructure (C2 IPs and URLs), presence of malicious files identified by SHA256 hashes on disk, and execution of known malicious files. It also correlates these activities with specific operator email addresses involved in the malicious campaign.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
002
Detects outbound HTTP requests to api.github.com targeting the 'contents' API with patterns indicative of RUSTYSHADE malware command-and-control (C2) communication, including file extensions and filenames typical of its tasking mechanisms.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
Detects anomalous HTTP traffic patterns identified in the 'Ted' backdoor used by North Korean-affiliated threat actors (APT37/Kimsuky/Lazarus). The rule specifically monitors the 'Accept-Language' HTTP header for a specific construction containing 'mrt=' followed by 'msc=' or 'mst=', which is used as a covert mechanism for authentication or command signaling.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
This rule detects DNS queries for domains associated with DPRK-aligned threat actor backdoors, specifically identified in research as related to curlRAT or similar secondary-stage malware communication. Monitoring these domains can identify potential beaconing or C2 communication from compromised hosts.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
102
Detects the specific TCP handshake pattern characteristic of the Fast Reverse Proxy (FRP) client (frpc) initiating a connection to a command-and-control server. The rule inspects established traffic for specific metadata strings ('privilege_key', 'run_id', 'pool_count') within the initial handshake payload.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
003
This rule detects HTTP POST requests characteristic of the curlRAT malware used by DPRK-affiliated threat actors. The detection looks for a specific POST body format containing 'name=', '&value=', and '&type=' parameters, which indicates C2 communication patterns commonly associated with this specific backdoor.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
102
Detects potential NTLM relay attacks targeting Active Directory Certificate Services (AD CS) web enrollment endpoints, including subsequent certificate requests for sensitive templates. This pattern identifies attackers attempting to relay NTLM authentication to AD CS and potentially requesting certificates for high-privilege templates (e.g., DomainController, SubCA, Machine, or User) to facilitate privilege escalation.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
002
This rule detects potential adversarial reconnaissance activities targeting AI agents via multiple communication channels (e.g., email, collaboration tools). It identifies patterns where a sender transmits messages containing common 'jailbreak' or 'instruction-override' phrases (e.g., 'ignore previous instructions', 'bypass approval') across at least three distinct channels within a 24-hour window, indicating a concerted effort to manipulate or probe agent logic.
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Arnold Chan@slaz
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Detections.ai Community
1 month ago
002
Detects a sequence of potentially malicious activity targeting LLM-related API endpoints. The rule identifies a client IP performing rapid, distinct endpoint discovery, followed by a POST request to sensitive paths, and concluding with a spike in 5xx server-side errors, indicating potential exploitation attempts or fuzzing against Large Language Model interfaces.
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Arnold Chan@slaz
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Hunters
1 month ago
002
Detects a sequence of potentially malicious activity targeting LLM-related API endpoints. The rule identifies a client IP performing rapid, distinct endpoint discovery, followed by a POST request to sensitive paths, and concluding with a spike in 5xx server-side errors, indicating potential exploitation attempts or fuzzing against Large Language Model interfaces.
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Arnold Chan@slaz
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Detection & Hunting Community
1 month ago
102
Detects web servers serving significantly different content sizes to AI crawlers (e.g., ChatGPT-User, ClaudeBot) compared to human web browsers for the same URL, which is a technique used to serve benign content to automated scrapers while delivering malicious or deceptive content to human users.
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Arnold Chan@slaz
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Hunters
1 month ago
002
This rule detects suspicious HTTP POST requests to a /collect endpoint that contain tracking parameters (visitorId, stage, variant, events) associated with 'ClickFix' social engineering campaigns. These campaigns typically trick users into copying and pasting malicious code by simulating error prompts or CAPTCHAs.
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Ibrahim Saud@tektrix
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Detections.ai Community
1 month ago
005
Detects unauthorized HTTP requests to sensitive Cisco Identity Services Engine (ISE) API and administrative paths (/ers/, /admin/, /api/). The rule specifically looks for incoming requests that lack both an Authorization header and a Cookie header, which is indicative of potential exploitation attempts against vulnerabilities such as CVE-2026-76460, where authentication mechanisms might be bypassed or ignored.
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Ankit Mehta@Secvyn
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Detections.ai Community
1 month ago
007
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