Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
208 detections
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Detects when Node.js or NPM processes access sensitive credential files such as .npmrc, SSH private keys, or AWS credentials, followed by an outbound public network connection from the same device within a 15-minute window.
Detects indicators of ToolShell web shell creation (spinstall0.aspx) and ASP.NET machine key harvesting activities (reading web.config or accessing validationkey/decryptionkey materials via w3wp child processes or file access audits) on SharePoint servers.
Detects when Node.js or NPM processes access sensitive credential files such as .npmrc, SSH private keys, or AWS credentials, followed by an outbound public network connection from the same device within a 15-minute window.
The following analytic detects the creation of files with extensions commonly associated with the Mimikatz Crypto module. It leverages the Endpoint.Filesystem data model to identify specific file names indicative of certificate export activities. This behavior is significant as it may indicate the use of Mimikatz to export cryptographic keys, which is a common tactic for credential theft. If confirmed malicious, this activity could allow an attacker to exfiltrate sensitive cryptographic material, potentially leading to unauthorized access and further compromise of the environment.
The following analytic detects the export of a certificate from the Windows Certificate Store. It leverages the Certificates Lifecycle log channel, specifically event ID 1007, to identify this activity. Monitoring certificate exports is crucial as certificates can be used for authentication to VPNs or private resources. If malicious actors export certificates, they could potentially gain unauthorized access to sensitive systems or data, leading to significant security breaches.
The following analytic detects the use of the PowerShell Cmdlet `export-certificate` by leveraging Script Block Logging. This activity is significant as it may indicate an adversary attempting to exfiltrate certificates from the local Certificate Store on a Windows endpoint. Monitoring this behavior is crucial because stolen certificates can be used to impersonate users, decrypt sensitive data, or facilitate further attacks. If confirmed malicious, this activity could lead to unauthorized access to encrypted communications and sensitive information, posing a severe security risk.
The following analytic detects the use of the PowerShell cmdlet `export-pfxcertificate` by leveraging Script Block Logging. This activity is significant as it may indicate an adversary attempting to exfiltrate certificates from the Windows Certificate Store. Monitoring this behavior is crucial for identifying potential certificate theft, which can lead to unauthorized access and impersonation attacks. If confirmed malicious, this activity could allow attackers to compromise secure communications, authenticate as legitimate users, and escalate their privileges within the network.
The following analytic detects the use of the PowerShell cmdlet `export-pfxcertificate` on the command line, indicating an attempt to export a certificate from the local Windows Certificate Store. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs and command-line arguments. This activity is significant as it may indicate an attempt to exfiltrate authentication certificates, which can be used to impersonate users or decrypt sensitive data. If confirmed malicious, this could lead to unauthorized access and potential data breaches.
Detects when an AI agent or assistant process attempts to access sensitive local configuration or credential files (e.g., .aws/credentials, .env, id_rsa, service account keys, .netrc) that typically fall outside the scope of its intended function. This behavior is indicative of unauthorized access, potentially due to prompt injection or malicious exploitation of the agent's file system permissions.
Detects runtime processes associated with AI agents or scripting environments (e.g., python, node, deno) accessing sensitive credential storage paths and files, such as SSH keys, cloud provider configuration directories, and local environment variables, which may indicate credential exfiltration.
Detects unauthorized access, reading, or downloading of sensitive NetScaler system files, including configuration files (ns.conf), licensing files, and cryptographic material (private keys/certificates). This activity often indicates post-exploitation reconnaissance, staging, or data theft attempts following initial access.
Detects anomalous file access patterns by Semantic Kernel agent processes attempting to read sensitive host files such as SSH keys, configuration files, and credential stores. This activity is indicative of malicious use of agent file-transfer capabilities, potentially exploiting path traversal vulnerabilities or prompt injection to exfiltrate sensitive data from the host environment into the agent sandbox.
Detects potential Golden SAML activity by correlating Azure AD SAML sign-in events for privileged accounts with a lack of corresponding server-side ADFS authentication logs, unusual SAML issuer URIs, lack of on-premises authentication logs, or evidence of direct access to ADFS token-signing certificate private key material.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects bulk file access or modifications involving sensitive files such as certificates (.pfx, .p12, .pem, .key), password manager vaults (.kdbx, .kdb), and files containing keywords related to credentials or logins. This behavior is indicative of an adversary staging or exfiltrating sensitive security material for further credential access.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects anomalous file access patterns by Semantic Kernel agent processes attempting to read sensitive host files such as SSH keys, configuration files, and credential stores. This activity is indicative of malicious use of agent file-transfer capabilities, potentially exploiting path traversal vulnerabilities or prompt injection to exfiltrate sensitive data from the host environment into the agent sandbox.
Detects anomalous file access patterns by Semantic Kernel agent processes attempting to read sensitive host files such as SSH keys, configuration files, and credential stores. This activity is indicative of malicious use of agent file-transfer capabilities, potentially exploiting path traversal vulnerabilities or prompt injection to exfiltrate sensitive data from the host environment into the agent sandbox.
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