Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects automated post-compromise activity associated with Bluekit Browser-in-the-Middle (BitM) attacks. The rule identifies a pattern of a successful user login followed rapidly (within 10 minutes) by a password change and new passkey enrollment, indicating an adversary is securing their persistence after initial session hijacking.
Detects unauthorized or suspicious processes attempting to open a handle to the Local Security Authority Subsystem Service (lsass.exe) with access rights required for memory reading, such as PROCESS_VM_READ or PROCESS_QUERY_INFORMATION. This behavior is a common prerequisite for credential dumping techniques like Minidump or direct memory extraction used by malicious tools.
Detects potential credential harvesting attempts by monitoring for the usage of Windows credential management tools (cmdkey.exe and vaultcmd.exe) and the loading of sensitive DLLs (vaultcli.dll, dpapi.dll) by non-Microsoft signed processes, which is commonly used to access stored credentials in the Windows Vault or by DPAPI-protected stores.
Detects successful ROPC (Resource Owner Password Credential) token acquisitions targeting Microsoft Graph (00000003-0000-0000-c000-000000000000) where Conditional Access was not applied and only single-factor authentication was satisfied. This pattern indicates abuse of hidden CA policy scope exclusions introduced by CVE-2025-0309, enabling token issuance without MFA or device compliance enforcement.
Detects attempts to modify the WDigest UseLogonCredential registry value, which can be used to force Windows to store plaintext credentials in LSASS memory. Adversaries use this technique to facilitate credential dumping.
Detects modifications to the 'UseLogonCredential' registry value under the WDigest security provider. Enabling this setting allows Windows to store plaintext credentials in memory (LSASS), which facilitates credential theft and credential dumping attacks.
This rule detects potential password spraying attacks against Azure Active Directory by identifying sign-in failures from a single source IP address targeting a large number of distinct user accounts within a short time window. It specifically filters for common authentication failure codes and checks for low volume of failures per account, which is characteristic of password spraying behavior.
This rule detects potential Kerberoasting activity by monitoring for high volumes of Kerberos TGS (Ticket Granting Service) requests (Event ID 4769) using the RC4 encryption type (0x17) within a short timeframe. Kerberoasting involves requesting tickets for service accounts to offline crack their passwords. The rule filters out known service accounts and system-level accounts ending in '$'.
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 attempts to list, read, create, update, or delete Kubernetes secrets through the Kubernetes API server. This activity could indicate an adversary attempting to gain access to sensitive credentials or manipulate application configurations.
Detects Kerberoasting attempts by identifying suspicious Ticket Granting Service (TGS) requests (Event ID 4769) for the 'krbtgt' service or other services where the ticket encryption type is RC4 (0x17) or older/weaker encryption types (0x18), especially when these requests are not preceded by a corresponding Ticket Granting Ticket (TGT) request (Event ID 4768).
Detects the use of legitimate Windows system utilities (ntdsutil.exe, vssadmin.exe, esentutl.exe) to interact with the Active Directory database file (ntds.dit). This behavior is commonly associated with offline credential harvesting, where an attacker attempts to create a copy of the database to extract hashes offline.
Detects Kerberos Ticket Granting Service (TGS) requests using RC4 encryption (etype 0x17) by non-service accounts, which is a common indicator of a Kerberoasting attack where adversaries attempt to crack service account passwords offline.
This rule detects various methods used to copy or access the Active Directory database (NTDS.dit), a common technique used by attackers to dump domain credentials. The rule monitors for the use of ntdsutil with 'ifm' (install from media) arguments, vssadmin to create volume shadow copies of the NTDS file, esentutl directly interacting with the NTDS database path, and common file copy utilities attempting to copy the NTDS.dit file.
This rule monitors Active Directory Certificate Services (AD CS) event logs for signs of potential privilege escalation and credential abuse. It specifically targets indicators of ESC1 (AD CS misconfigurations allowing requester-supplied SANs), identifies requests for certificates by non-owners for privileged accounts, and monitors for the use of PKI-based Kerberos authentication against high-privilege targets.
Detects successful password spraying attempts against Entra ID using the Resource Owner Password Credentials (ROPC) flow where multi-factor authentication (MFA) is bypassed. This rule specifically looks for multiple failed ROPC sign-in attempts from an IP address followed by a successful ROPC sign-in from the same IP address, where the authentication method reference (amr) claim does not include 'mfa'. This pattern is consistent with potential abuse of Conditional Access policy hidden exclusions, as described in CVE-2025-0309.
Detects suspicious device registrations to Azure AD's Device Registration Service (DRS) using the device code flow. This rule identifies registrations where the device OS attributes are suspicious (e.g., version 0.0.0.0) or where a non-Windows OS claims a Windows identity, potentially indicating an adversary attempting to bypass conditional access policies or gain persistent access.
Detects unauthorized processes attempting to access sensitive browser credential files (Login Data and Cookies) for Chrome, Edge, and Firefox. The rule applies risk scoring based on whether the accessing process is located in suspicious directories (e.g., Temp, Downloads) or if specific indicators associated with the Millenium RAT are present.
Detects suspicious subprocesses spawned by IDE or extension host processes (like VS Code or Amazon Q) that execute AWS CLI commands to enumerate identity or immediately exfiltrate data via curl/wget, indicating potential credential abuse by malicious plugins or MCP servers.
Detects a multi-stage attack where an adversary reads local AWS credentials or configuration files (e.g., .aws/credentials, mcp.json) on a developer workstation and subsequently performs unauthorized AWS API calls from the same source IP. The rule correlates initial credential access on the endpoint with a sequence of AWS CloudTrail events starting with identity verification (GetCallerIdentity) followed by enumeration and potentially high-impact API calls (e.g., RunInstances, AssumeRole).
Detects processes accessing sensitive files on a Linux system, such as SSH private keys, shell history files, and various application-specific configuration or credential files (e.g., Claude, Codex, Gemini, Cline, Opencode, Kilo). The rule excludes common system processes like shells, SSH daemons, git, and curl to minimize noise while identifying suspicious file access.
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