Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a multi-stage exploit chain targeting iOS Safari clients, characterized by the sequential fetching of specific JavaScript modules (platform_module.js, utility_module.js, Stage1, Stage3, and bootstrap.dylib) and subsequent callback communication to a remote server. This pattern is consistent with a browser-based exploit framework targeting iOS devices.
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.
This rule detects potentially malicious POST requests to SharePoint endpoints (such as AddGallery.aspx) that include indicators of WebPartMarkup or ToolPane payloads. This activity attempts to bypass the SPUtility.EnsureAuthentication() check that is typically enforced on the ToolPane.aspx page, potentially allowing unauthorized code execution or configuration manipulation.
Hunts telemetry for published NeedyMantis indicators: three known SHA-256 hashes (WinSparkle.dll first-stage loader and its encrypted archive, plus the older libcurl archive), the C2 domain corp.tripswithengine[.]com, and the C2 URL path /library/zip/ on that domain. Domain/URL matching parses the actual host out of RemoteUrl and requires an EXACT match (not substring 'has/contains'), so a different domain that merely contains 'corp.tripswithengine.com' as a suffix of a longer label (e.g. 'notcorp.tripswithengine.com') or as a prefix of an unrelated domain (e.g. 'corp.tripswithengine.com.evil.net') cannot match. No malicious IP address has been published for this campaign, so IP-based matching is intentionally not included.
Detects outbound HTTP POST requests destined for 'aware-cr1.com' targeting the URI '/api/beacon', which is indicative of command-and-control (C2) communication associated with the 2CLoader malware.
Detects a sequential pattern where a browser process (Chrome, Edge, or Safari) accesses an AI chat platform's conversation API, followed within 5 minutes by a network connection to a known unauthorized exfiltration destination (api.pbapi.xyz). This pattern suggests the potential use of a browser-based tool or extension (e.g., Poper Blocker or similar) to intercept and exfiltrate AI chat history.
This rule performs a point-in-time sweep for known Indicators of Compromise (IOCs) associated with the NeedyMantis threat actor group. The detection logic searches for specific file, process, and image-load SHA256 hashes, communication with a known C2 domain (tripswithengine.com), and the use of a hard-coded user-agent string (Firefox/21.0) across various telemetry sources within the last 30 days.
Detects high-volume POST requests or traffic flagged by DLP mechanisms destined for known public generative AI platforms (e.g., OpenAI, Claude, Google Gemini). This rule identifies potential unauthorized transmission of sensitive or regulated data, such as PII or confidential information, to third-party AI services.
Detects incoming HTTP POST requests to the 'diffpatch' endpoint in Gitea that contain suspicious 'diff --git' patterns combined with path traversal sequences ('../') targeting 'hooks/' directories. This indicates an attempt to exploit CVE-2026-60004 to achieve unauthorized file system access or remote code execution via repository hooks.
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.
This rule detects high-frequency API endpoint access originating from a single source IP address within a one-minute window, where the User-Agent does not match common browser strings. This behavior is indicative of automated scanning, scraping, or brute-force enumeration of API resources by non-browser clients.
This rule detects administrative or user activity within Azure via AzureActivity logs and web request patterns in AppServiceHTTPLogs that originate from a predefined list of known malicious IP addresses.
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.
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