Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a 'git checkout' command targeting a specific commit SHA that is not followed within five minutes by a 'git rev-parse HEAD' integrity check. This behavior, known as 'Plugin4Shell', involves an attacker replacing a pinned commit with a malicious branch of the same name, potentially leading to unauthorized code execution if verification steps are absent.
Detects automated searching (via grep, findstr, or select-string) for sensitive strings (e.g., API keys, private keys, wallet data) across multiple occurrences on a single host, or the creation of suspicious sensitive files (e.g., .env, credentials, wallet.dat) on devices where such automated sweeping activity has been observed. This pattern indicates an adversary staging data for exfiltration.
Detects unauthorized access and data retrieval attempts from a MinIO object storage instance using default administration credentials (minioadmin:minioadmin). The rule monitors both command-line execution of MinIO client (mc) operations and network connections to MinIO service ports (9000/9001) that involve the use of the default credential pair.
Detects unauthorized access and data retrieval attempts from a MinIO object storage instance using default administration credentials (minioadmin:minioadmin). The rule monitors both command-line execution of MinIO client (mc) operations and network connections to MinIO service ports (9000/9001) that involve the use of the default credential pair.
Detects lateral movement activity where a host identified as running the Langflow framework attempts to connect to internal MySQL (3306) or Nacos (8848) services while utilizing root credentials, potentially indicating an attacker pivoting from a compromised application server.
Detects lateral movement activity where a host identified as running the Langflow framework attempts to connect to internal MySQL (3306) or Nacos (8848) services while utilizing root credentials, potentially indicating an attacker pivoting from a compromised application server.
Detects the execution of PostgreSQL dump utilities (pg_dump, pg_dumpall) initiated directly by application-level processes like Langflow or Python, rather than through standard system-level task schedulers. This behavior is indicative of unauthorized data collection or staging of database contents by an application process.
Detects the execution of PostgreSQL dump utilities (pg_dump, pg_dumpall) initiated directly by application-level processes like Langflow or Python, rather than through standard system-level task schedulers. This behavior is indicative of unauthorized data collection or staging of database contents by an application process.
Detects the execution of PostgreSQL dump utilities (pg_dump, pg_dumpall) initiated directly by application-level processes like Langflow or Python, rather than through standard system-level task schedulers. This behavior is indicative of unauthorized data collection or staging of database contents by an application process.
Detects suspicious process execution patterns originating from Langflow or Nacos AI orchestration services, including the spawning of sensitive binaries like cmd, powershell, or scripts (python/bash/sh) with suspicious command-line arguments. Additionally, it identifies potential exploitation attempts targeting known-vulnerable API endpoints (code validation and Nacos user authentication).
This rule detects the use of the VS Code command line interface to install extensions, specifically by monitoring for the 'workbench.extensions.installExtension' command. This activity can be indicative of automated installation of extensions, which could be used for malicious purposes or persistence if an attacker installs a malicious extension.
This rule detects the use of the VS Code command line interface to install extensions, specifically by monitoring for the 'workbench.extensions.installExtension' command. This activity can be indicative of automated installation of extensions, which could be used for malicious purposes or persistence if an attacker installs a malicious extension.
Detects instances where LiteLLM, or related Python application processes (uvicorn, python), spawn a shell or command-line utility (bash, sh, id) under the root user account. This behavior is indicative of potential container breakout, application exploitation, or privilege escalation attempts originating from a web-accessible service.
Matches known HOOKEDGE malware samples attributed to BlueDelta (APT28) via SHA256 hash comparison
Detects a network connection to potentially malicious infrastructure or non-standard ports following a request to ipify.org, which is commonly used for external IP reconnaissance by malware and C2 frameworks.
Rileva la presenza di stringhe riconducibili a un toolkit di persistenza Linux (pid file di monitoraggio, binari grub typo-squattati) all'interno del contenuto di script eseguiti sull'host.
Detects Linux processes masquerading as 'php-fpm' or 'postgres' that match known SHA-256 hashes associated with the RedTail malware family. The rule identifies processes attempting to hide their identity using techniques similar to prctl(PR_SET_NAME) to rename themselves while running malicious code.
This rule detects successful user authentication events within the environment. It acts as a base filter to capture login success, which can be further refined with context such as IP addresses or usernames to monitor for anomalous login patterns, though it does not inherently provide detection of complex attacks like session token hijacking on its own.
Detects a successful authentication event where standard endpoint identification metadata (endpoint name and IP address) is absent. This often indicates logs originating from sources without proper endpoint telemetry integration or potential attempts to obfuscate the source of an authentication request.
This rule monitors DNS requests and network connections for activity targeting domains identified as malicious: 'gg-steelseries.com.cn' and 'org-bcut.com.cn'. These domains are often associated with command and control infrastructure or malware distribution, and their presence in network logs is a high-fidelity indicator of a potential compromise.
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.
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