Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors for suspicious activity often associated with credential or sensitive information discovery in development environments. It identifies: 1) Access to configuration files or directories related to AI-powered development tools (e.g., Cursor, Windsurf, Zed) which may store environment variables or API keys; 2) Network connections to common cloud instance metadata endpoints; and 3) Execution of command-line tools attempting to access AWS secrets or configuration management APIs (Secrets Manager, SSM).
This rule monitors for processes making requests to cloud instance metadata services (GCP) or accessing sensitive secrets and parameters via AWS CloudTrail. Such activity may indicate an attacker attempting to enumerate instance identities, retrieve temporary security credentials, or access managed configuration secrets.
Detects process command lines using curl to query the Azure Instance Metadata Service (IMDS) endpoint (169.254.169.254) for OAuth tokens. This behavior is indicative of an attacker attempting to leverage an Azure Managed Identity associated with a compromised virtual machine to obtain temporary security tokens for unauthorized access to other Azure resources.
Detects incoming HTTP POST requests to the /PSEMHUB/hub endpoint on Oracle PeopleSoft servers, which is indicative of exploitation attempts related to the Server-Side Request Forgery (SSRF) vulnerability identified as CVE-2026-35273.
Detects a potential SSRF-based exfiltration attempt by correlating DNS traffic. The rule identifies a browser session that accesses M365 Copilot (m365.cloud.microsoft) followed by a connection to Bing (bing.com), which is indicative of the exfiltration technique associated with CVE-2026-42824 involving the Bing 'searchbyimage' feature.
Detects incoming HTTP POST requests to the /PSEMHUB/hub endpoint on Oracle PeopleSoft servers, which is indicative of exploitation attempts related to the Server-Side Request Forgery (SSRF) vulnerability identified as CVE-2026-35273.
Detects Server-Side Request Forgery (SSRF) attempts exploiting URL parser differentials. Attackers append a double-slash sequence to a legitimate github.com blob URL to trick the backend into resolving an absolute local filesystem path. The rule specifically targets sensitive paths such as /proc/self/environ, /var/task/, and application source files to perform Local File Read (LFR) or access internal cloud metadata services.
This rule detects outbound network traffic from an instance or container to the Google Cloud metadata service (metadata.google.internal or 169.254.169.254). Such activity is highly indicative of Server-Side Request Forgery (SSRF) exploitation, where an attacker attempts to retrieve service account credentials or instance metadata from an internal service.
Detects web requests containing patterns indicative of Server-Side Request Forgery (SSRF) attempts targeting the Google Cloud Platform (GCP) Instance Metadata API (metadata.google.internal). The rule monitors for attempts to access metadata endpoints, including token retrieval paths.
This rule detects attempts to exfiltrate GCP service account credentials by performing a Server-Side Request Forgery (SSRF) attack targeting the GCP metadata server or local system files. It correlates suspicious outbound request patterns with subsequent response bodies containing standard GCP credential fields, excluding known legitimate authentication traffic to cloud APIs.
Detects processes attempting to connect to the Cloud Instance Metadata Service (IMDS) IP address (169.254.169.254) or referencing it in the command line. This behavior is often associated with credential theft or reconnaissance on cloud instances.
Detects processes attempting to connect to the Cloud Instance Metadata Service (IMDS) IP address (169.254.169.254) or referencing it in the command line. This behavior is often associated with credential theft or reconnaissance on cloud instances.
Detects instances where language-related processes (amazonq-language-server, node) or common tools (bash, sh, curl, aws) execute commands containing AWS access credentials or perform potential data exfiltration via curl POST requests.
Detects Server-Side Request Forgery (SSRF) attempts exploiting URL parser inconsistencies. Attackers use a 'github.com@' prefix within a URL parameter to trick backend fetchers into connecting to unintended, potentially internal, hosts like 'metadata.google.internal', bypassing validation logic that incorrectly parses the URL authority.
Detects attempts by processes to access the Google Cloud Platform Instance Metadata Service (IMS) at 169.254.169.254 or via the 'metadata.google.internal' DNS entry. This is often an indicator of reconnaissance, SSRF exploitation, or credential theft attempts by an adversary on a compromised cloud instance.
Detects Server-Side Request Forgery (SSRF) attempts against the Google Cloud metadata server (169.254.169.254 or metadata.google.internal) within GCP Cloud Run request logs. This rule identifies inbound requests attempting to access sensitive cloud metadata paths or tokens, often indicative of an adversary attempting to extract service account credentials or instance information.
This rule monitors for process creations spawned by common web application servers (e.g., nginx, python, java, php) where the command line arguments contain indicators of a Server-Side Request Forgery (SSRF) attempt. Specifically, it looks for suspicious URL schemes (file:, gopher:, dict:, ftp:), potential authority confusion patterns (targeting cloud metadata IPs), and encoded directory traversal characters when paired with sensitive paths like 'etc' or 'proc'.
Detects HTTP requests attempting to access sensitive internal IP addresses (RFC-1918) or cloud metadata services (e.g., 169.254.169.254) which are common indicators of Server-Side Request Forgery (SSRF) exploitation attempts.
Detects attempts to access the GCP instance metadata service (metadata.google.internal) by exploiting Server-Side Request Forgery (SSRF) vulnerabilities. The rule looks for URI patterns often used to bypass filters by manipulating the authority component or using specific protocols like 'gcs://' to target internal cloud infrastructure.
This rule monitors web and proxy traffic for patterns indicative of Server-Side Request Forgery (SSRF) attempts. It searches for specific URL parameters designed to manipulate requests toward internal cloud metadata services (e.g., 169.254.169.254), exploit protocol schemes like 'gcs://', or leverage URL parsing discrepancies such as unauthorized authority or fragment-at-sign confusion to bypass security filters.
This rule detects potential Server-Side Request Forgery (SSRF) probing attempts against web applications where unauthenticated requests contain a URL parameter used to request external or internal resources. It flags high-volume probing activity and correlates the source IP with concurrent anomalous Azure Active Directory (Azure AD) sign-in events from the same source, such as failed logins or high-risk sign-in attempts.
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