Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
This rule identifies browser extensions installed on devices that are either explicitly known as malicious or exhibit suspicious naming patterns potentially associated with unauthorized or malicious extensions.
This rule identifies browser extensions installed on devices that are either explicitly known as malicious or exhibit suspicious naming patterns potentially associated with unauthorized or malicious extensions.
Detects instances where a browser process (chrome.exe) accesses the microphone or camera within a 2-minute temporal window of communicating with 'gemini.google.com'. This rule is intended to identify potential unauthorized use of system peripherals in the context of an AI-agent session.
Detects instances where a browser process (chrome.exe) accesses the microphone or camera within a 2-minute temporal window of communicating with 'gemini.google.com'. This rule is intended to identify potential unauthorized use of system peripherals in the context of an AI-agent session.
This rule detects potential exploitation attempts (CVE-2026-59822) against LiteLLM MCP tool endpoints. It identifies HTTP requests where the authorization bearer token is unusually short (<= 12 chars), lacks the 'sk-' prefix, and does not appear to be a valid JWT, yet successfully results in a 200 OK status, indicating a potential bypass of authentication logic.
Detects the use of the default, hardcoded 'sk-1234' secret key for HS256 JWT signing in LiteLLM proxy logs. This configuration is insecure and allows for the forgery of arbitrary user session tokens.
Detects the creation or update of LiteLLM custom code guardrails that include suspicious Python snippets, specifically 'import os' and 'os.popen', which are indicative of attempts to execute arbitrary OS commands via guardrail logic (CVE-2026-59821).
Detects a GitLab personal access token used from multiple distinct source IPs or from IPs associated with the leaked gitlab-triage token, inconsistent with expected CI runner infrastructure.
Detects a single GitLab token/account holding Owner-level access across an unusually large number of projects (50+), the standing-privilege condition that turned one leaked token into a 55-project supply-chain exposure.
Detects high-value wire transfers (>= €600,000) directed to beneficiaries in Hong Kong that contain suspicious memo or description fields related to confidential acquisitions or professional service retainers, potentially indicating business email compromise (BEC) or fraudulent financial activity.
Detects high-value wire transfers (>= €600,000) directed to beneficiaries in Hong Kong that contain suspicious memo or description fields related to confidential acquisitions or professional service retainers, potentially indicating business email compromise (BEC) or fraudulent financial activity.
Detects GitLab CI job shell commands that redirect the environment to a .tmp file, a pattern identified in the GnuTLS GitLab token leak.
Detects GitLab CI job shell commands that redirect the environment to a .tmp file, a pattern identified in the GnuTLS GitLab token leak.
Detects activity from Anthropic network range across multiple event types
This rule detects potential Server-Side Request Forgery (SSRF) activity where web application or runtime processes attempt to access the Cloud Instance Metadata Service (IMDS) or container task metadata endpoints. By monitoring network connections and application logs, the rule filters out known legitimate metadata clients and identifies suspicious processes frequently associated with web-based vulnerabilities that are repeatedly querying sensitive metadata paths.
This rule detects potential Server-Side Request Forgery (SSRF) activity where web application or runtime processes attempt to access the Cloud Instance Metadata Service (IMDS) or container task metadata endpoints. By monitoring network connections and application logs, the rule filters out known legitimate metadata clients and identifies suspicious processes frequently associated with web-based vulnerabilities that are repeatedly querying sensitive metadata paths.
Detects a user performing a high volume of SharePoint site discovery queries within a one-hour window. This behavior often indicates an adversary attempting to map site structures and discover content across an organization's SharePoint environment.
Detects unauthorized remote access sessions within N-able N-central by monitoring the Windows Application log for events indicating usage of the default 'MSP Support' account or source IP addresses associated with active exploitation of CVE-2026-18577.
Detects the installation of software packages in build or CI pipelines where the package was published to its registry between 30 and 90 days prior to being first used in the environment. This pattern is indicative of potential dependency confusion or typosquatting attacks, where adversaries use newly created packages to deliver malicious code.
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