Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous, high-value wire transfers involving keywords related to advance-payment or M&A-related fraud (e.g., 'advance retainer'), directed towards beneficiaries in Hong Kong using previously unseen bank accounts. The rule effectively filters out known, approved beneficiary accounts to focus on potentially malicious transactions.
Detects CI/CD job activity referencing shell commands that redirect the entire environment to a file (e.g. 'env > out.tmp'), the exact pattern that caused a GitLab CI job in the openconnect/ocserv project to dump secrets into a public build artifact, leaking a high-privilege personal access token with Owner access to GnuTLS and 55 other critical projects.
Detects a significant surge of bulk or spam mail quarantine events for a single mailbox within a 15-minute window. This behavior often indicates a mail-bombing attack intended to overwhelm the user or as a distraction technique (smokescreen) to hide concurrent malicious activities such as exfiltration, lateral movement, or ransomware staging in the M365 tenant.
Detects the creation of a WordPress administrator account within one hour of a recorded web request to a known web shell path (Mushr00w) or suspect plugin upload directory. This correlation is a high-fidelity indicator of post-exploitation persistence and administrative account hijacking.
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 invocations of the 'grafana_api_request' tool that lack a preceding valid bearer-token authentication event for the same session. This indicates a potential scenario where a server or service account token is being used on behalf of an unauthenticated caller, bypassing normal authentication requirements for the Grafana API.
Detects the presence of a specific sentinel string 'data.external.telemetry' within Terraform provisioner job logs, which indicates the execution of unauthorized data-collection logic within a compromised or backdoored Terraform module.
Detects anomalous, high-volume search query activity across multiple SharePoint sites or OneDrive locations, potentially indicating an adversary performing broad data discovery or enumeration across an organization's cloud document repositories.
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.
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 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 detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
This rule detects anomalous access patterns on a specific IIS host (agent.3bb.co.th) by comparing recent traffic against a 30-day historical baseline. It identifies requests from accounts or source IPs not seen in the baseline, activity occurring during off-hours, or traffic from external sources. The rule further filters for high-volume or high-path diversity requests, which are indicative of automated reconnaissance or potential brute-force activity against the web application.
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 instances where a LiteLLM proxy is utilized to invoke sensitive Model Context Protocol (MCP) tools (e.g., database, github, slack, jira, ci/cd) while authentication is bypassed ('allow_all_keys=true') and no explicit API key is provided. This indicates a potential unauthorized access attempt to sensitive integrations via a misconfigured proxy.
Detects instances where a LiteLLM proxy is utilized to invoke sensitive Model Context Protocol (MCP) tools (e.g., database, github, slack, jira, ci/cd) while authentication is bypassed ('allow_all_keys=true') and no explicit API key is provided. This indicates a potential unauthorized access attempt to sensitive integrations via a misconfigured proxy.
Detects instances where a LiteLLM proxy is utilized to invoke sensitive Model Context Protocol (MCP) tools (e.g., database, github, slack, jira, ci/cd) while authentication is bypassed ('allow_all_keys=true') and no explicit API key is provided. This indicates a potential unauthorized access attempt to sensitive integrations via a misconfigured proxy.
Detects instances where a LiteLLM proxy is utilized to invoke sensitive Model Context Protocol (MCP) tools (e.g., database, github, slack, jira, ci/cd) while authentication is bypassed ('allow_all_keys=true') and no explicit API key is provided. This indicates a potential unauthorized access attempt to sensitive integrations via a misconfigured proxy.
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.
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