Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects HTTP GET requests to known malicious domains or URI patterns associated with fake video-conferencing lures. These lures redirect users to download RMM (Remote Monitoring and Management) MSI installers, often masquerading as legitimate software like Adobe Reader or video conferencing tools, as part of a social engineering campaign for initial access.
Detects HTTP POST requests to Telegram Bot API and Discord webhooks containing large, Base64-encoded strings within request bodies, which may indicate exfiltration of reconnaissance data or sensitive information.
Detects HTTP POST requests directed at common Large Language Model (LLM) chat completion and completion endpoints that are not associated with authorized OpenAI or Azure OpenAI services. This behavior may indicate an attempt to exfiltrate potentially sensitive corporate or proprietary data to third-party or unauthorized Shadow-AI platforms.
Detects incoming HTTP POST requests to internal AI/LLM API endpoints containing common prompt injection strings, such as instructions to ignore previous system prompts or attempts to trigger jailbreak modes like 'DAN'.
Detects attempts to exploit a vulnerability (CVE-2026-68536) in the Apache MyFaces JSF resource handler. The rule monitors for malicious URI parameters ('ln' or 'library') that attempt Server-Side Request Forgery (SSRF) targeting cloud metadata services, path traversal, or URI-based injection attacks.
Detects attempts to exploit an unauthenticated OS command injection vulnerability in Cisco ISE (CVE-2026-20130). The rule monitors inbound HTTP traffic for shell metacharacters and common command-line binaries in the URI or request body, indicating an attempt to execute arbitrary commands on the underlying host.
Detects unauthenticated network requests targeting MLflow Model Registry and Ajax API endpoints on port 5000. These requests are characteristic of unauthorized reconnaissance against exposed machine learning management services.
Detects unauthorized attempts to access exposed Chroma or Weaviate vector database APIs via standard HTTP requests (GET/POST) targeting known API endpoints for collections or objects. This may indicate an adversary conducting reconnaissance on publicly accessible database infrastructure.
Detects a high volume of HTTP POST requests to common login endpoints (e.g., /login or /wp-login.php) from a single source IP address within a short time frame, which is indicative of a credential stuffing or automated brute-force attack.
This rule detects potential command and control (C2) beaconing activity by monitoring for high-frequency POST requests to OpenAI and Google Generative Language chat completion API endpoints. The rule triggers when a source host makes 5 or more requests within a 60-second window, which may indicate automated polling for commands or exfiltrated data transfer using legitimate LLM infrastructure.
Detects a potential automated exploit sweep or brute-force attempt, identified by a high frequency of HTTP requests (GET or POST) directed to the same URI from a single source IP address within a short time frame.
Detects inbound HTTP POST requests directed at common paths associated with self-hosted OpenAI-compatible LLM inference APIs, such as LocalAI or vLLM. This rule identifies potentially unauthorized or unintended public exposure of internal LLM infrastructure, which could lead to unauthorized model usage, information disclosure, or exploitation of the inference engine.
This rule detects HTTP GET requests initiated by the Windows PowerShell User-Agent where the destination host is a decimal-encoded IP address. This pattern is commonly associated with ClickFix-style social engineering attacks, where users are tricked into executing obfuscated PowerShell commands to download malicious payloads.
Detects network traffic associated with the ClickFix Traffic Distribution System (TDS), specifically targeting requests to known malicious domains like fsputnik.com and uasputnik.com, as well as associated fake Cloudflare verification lure pages.
Detects network traffic destined for api.telegram.org that follows the specific URL structure pattern associated with the CARBONATO Hermes Agent bot command-and-control channel.
Detects HTTP traffic where the Host header contains a decimal-encoded IP address, which is a technique often used in stager evasion and obfuscation (notably associated with 'ClickFix' or similar browser-based malvertising campaigns) to bypass domain-based filtering or reputation systems.
Detects potential credential stuffing activity by monitoring for a high volume of HTTP 401 (Unauthorized) or 403 (Forbidden) responses originating from a single source IP address within a 60-second window, specifically targeting URIs containing the path 'login'.
Detects unauthorized exfiltration of sensitive information, such as camera credentials or location data, directed to the Telegram Bot API as part of the 'Operation CameraSwarm' campaign.
Detects incoming HTTP traffic containing a custom 'X-Quad' header, which is indicative of exploitation attempts targeting PaperCut MF vulnerabilities (CVE-2026-82078/CVE-2026-81578). This header is associated with the deployment or interaction with a Java-based web shell to establish unauthorized access.
Detects HTTP POST requests originating from the internal network directed at a known suspicious C2 infrastructure IP address (156.227.0.13), indicating potential C2 check-in activity associated with AdaptixC2 malware.
This rule detects network traffic originating from internal hosts using a specific HTTP User-Agent string associated with the default configuration of the AdaptixC2 framework. This is a common indicator of a C2 implant performing heartbeat or command-and-control communication.
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