Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
208 detections
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Detects techniques associated with Golden SAML attacks, including the use of Mimikatz for ADFS token-signing certificate extraction, the execution of AADInternals PowerShell cmdlets for SAML token forgery, and unauthorized access to the ADFS configuration database (AdfsConfiguration.mdf).
Detects unauthorized access (creation, modification, renaming, or deletion) to sensitive local credential files by the Node.js runtime process (node.exe/node). This behavior is indicative of infostealers, specifically noted in the Miasma/MYRA activity associated with the Polymarket Trap campaign, where malicious packages attempt to exfiltrate AWS, SSH, NPM, Python, Docker, and GPG credentials.
This rule detects potentially malicious activities related to Active Directory Certificate Services (AD CS). It identifies suspicious certificate export commands (certutil, PowerShell), non-privileged processes writing to system certificate stores, and dangerous AD CS enrollment patterns such as Subject Alternative Name (SAN) modifications, often associated with ESC1 privilege escalation techniques.
Detects processes attempting to read or open sensitive SSH files (keys and configuration) that are not recognized as legitimate SSH-related utilities (e.g., ssh, sshd, rsync, git). This behavior is often indicative of credential harvesting or unauthorized reconnaissance of authentication artifacts.
Detects Python or Node.js processes reading sensitive SSH private key files (id_rsa, id_ed25519) followed by an outbound network connection within a one-minute window. This behavior is indicative of credential theft and exfiltration, such as that observed in the InvisibleFerret campaign.
Detects Python scripts, launched by code.exe or node.exe (common IDE-related processes), accessing SSH private key files (id_rsa, id_ed25519, id_ecdsa) followed by an outbound network connection within 60 seconds. This behavior is indicative of credential theft and potential exfiltration or lateral movement.
Detects instances where scripting processes (Python, Node.js) accessed SSH key files or configuration files and subsequently initiated an outbound network connection within 60 seconds, which may indicate potential exfiltration of credentials or unauthorized access.
Identifies unauthorized attempts to leverage ssh-add or access the SSH agent socket to dump or forward local developer identities.
Detects rapid access (three or more distinct files within a 60-second window) to sensitive files typically containing credentials or configuration data (e.g., SSH keys, AWS credentials, environment files, container configurations). This pattern is often associated with credential dumping or reconnaissance activity by an adversary attempting to harvest secrets.
Detects reconnaissance and credential harvesting activities associated with the Lambsys cryptominer campaign. The rule monitors for unauthorized enumeration of SSH directories, key files, and the use of SSH utilities for lateral movement, specifically triggered by the presence of 'isp.sh' or 'lambsys' in command arguments or related patterns.
Identifies the Python script explicitly reading developer secrets including AWS credentials, SSH private keys, and Kubernetes configuration files.
Detects anomalous process execution patterns where a database process (postgres or postmaster) or a common system utility (nc, python, bash) is observed initiating unauthorized network connections to a known external C2 IP or accessing sensitive cryptographic files (e.g., server.key). This behavior is indicative of potential post-exploitation activity, specifically the exfiltration of credentials or sensitive data via database-level command execution (sys_eval) or direct file manipulation.
Detects anomalous activity associated with Amazon Q processes, including unauthorized access to SSH agent binaries, attempts to read SSH configuration files or keys in ~/.ssh/, and suspicious outbound network connections over port 22, potentially indicating lateral movement.
This rule detects suspicious activities related to SSH credential theft and lateral movement on Linux systems. It monitors for interactive shells or utilities like cat, python, and bash accessing common SSH configuration files (~/.ssh/id_rsa, authorized_keys, etc.), as well as automated SSH/SCP sessions using suspicious configurations (BatchMode=yes, StrictHostKeyChecking=no) or specific malicious payloads.
Detects a sequence of suspicious activities characteristic of an SSH-based worm. The rule correlates non-standard processes reading SSH private keys, the presence of known cryptominer components (lambsys, procq, isp.sh), and subsequent SSH network fan-out activity from the same host, indicating lateral movement.
Detects the Lambsys cryptominer malware performing SSH credential harvesting by accessing user SSH keys (known_hosts, authorized_keys, id_rsa) with unauthorized processes, staging these files in temporary or hidden directories, and subsequently initiating outbound SSH connections for lateral movement, all correlated by process group ID.
This rule detects instances where 'python.exe' aggressively accesses files within '.ssh' directories. This behavior could indicate an attempt to harvest SSH keys, which are critical for secure remote access.
This rule detects instances where a Node.js process accesses sensitive files associated with web browsers (e.g., Login Data, Cookies) or SSH keys (e.g., id_rsa). This behavior is often indicative of credential theft or unauthorized data collection, where an adversary uses legitimate tooling like Node.js to stage or exfiltrate sensitive local files.
Detects instances where a process not associated with standard SSH operations (e.g., ssh, scp, git) accesses SSH private key files, followed by an outbound network connection to a non-private IP address within a 5-minute window. This behavior is indicative of credential theft and subsequent exfiltration of sensitive SSH keys, often associated with infostealer malware.
Detects instances where a process not associated with standard SSH operations (e.g., ssh, scp, git) accesses SSH private key files, followed by an outbound network connection to a non-private IP address within a 5-minute window. This behavior is indicative of credential theft and subsequent exfiltration of sensitive SSH keys, often associated with infostealer malware.
This rule detects when a Node.js process accesses sensitive files associated with SSH configurations, private keys, or package manager credentials (such as .npmrc or .pypirc). Such behavior is highly unusual for legitimate web application processes and may indicate an attacker attempting to steal credentials or secrets from a compromised system.
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