Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
181 detections
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Detects a single Entra ID session (SessionId) being used from two different countries within one hour at a travel velocity no physical journey could achieve. This is a signature of a stolen session/refresh token being replayed by an actor from a different location than the legitimate user.
Detects non-interactive sign-in events using specific Microsoft application IDs (Intune for Education, Intune portal) to access Microsoft Graph that do not have a corresponding successful or failed Conditional Access policy record. This suggests potential circumvention of Conditional Access policies or service-level activity bypassing standard authentication auditing.
Detects non-interactive sign-in events using specific Microsoft application IDs (Intune for Education, Intune portal) to access Microsoft Graph that do not have a corresponding successful or failed Conditional Access policy record. This suggests potential circumvention of Conditional Access policies or service-level activity bypassing standard authentication auditing.
Detects sign-in events using 'deviceCode' authentication or single-factor authentication via mobile/desktop clients where the device identifier has not been seen in the previous 30 days. This pattern can indicate an adversary using a new device to access an account, potentially utilizing stolen sessions or bypassing MFA.
Detects instances where an Azure Automation Runbook interacts with or initiates a sign-in log activity that does not correspond to its own Managed Identity. This anomaly may indicate the abuse of a managed identity token to access unauthorized resources or perform lateral movement within the Azure environment.
Detects instances where an Azure Automation Runbook interacts with or initiates a sign-in log activity that does not correspond to its own Managed Identity. This anomaly may indicate the abuse of a managed identity token to access unauthorized resources or perform lateral movement within the Azure environment.
This rule detects the generation of 2-Step Verification (2SV) backup/scratch codes in Google Workspace. Backup codes allow a user to bypass standard MFA, making their generation a significant security event that may indicate an attacker is attempting to maintain persistent access to an account, often following a compromise or as a preparation for further malicious activity.
Detects a suspicious proxy authentication negotiation pattern involving multiple HTTP 407 challenges followed by a WebSocket upgrade and the establishment of a SOCKS5 tunnel, indicative of the BridgeHead adversary toolset.
Detects the presence of specific Microsoft Entra (formerly Azure AD) authentication session cookies (ESTSAUTH, ESTSAUTHPERSISTENT, ESTSAUTHLIGHT) in web proxy traffic. This activity is indicative of session cookie theft and potential replay attacks (Pass-the-Cookie) where an adversary attempts to authenticate to Microsoft services using stolen session material from an unauthorized or non-enrolled device.
This rule detects potential session token theft or replay attacks by identifying non-interactive sign-in events that occur from a different IP or geographic location than the user's most recent successful MFA-authenticated interactive session. It flags cases where a non-interactive token is used within a short timeframe (1 hour) of an interactive session from a different location, which may indicate the exfiltration and subsequent use of session cookies or OAuth tokens.
This rule detects potentially malicious use of libcurl or curl.exe involving mTLS-related flags (e.g., --cert, --key, --cacert) in non-browser processes. It specifically flags instances where such processes perform repeated HTTPS connections to remote hosts, which may indicate exploitation of CVE-2026-8932 related to mTLS connection reuse and authentication bypass.
Detects AzureHound or roadtx bulk enumeration of Microsoft Graph API endpoints using tokens obtained via CVE-2025-0309 CA policy bypass, characterized by high-frequency GET requests to /v1.0/users, /v1.0/groups, /v1.0/devices, /v1.0/servicePrincipals from Edge client IDs (f44b1140-bc5e-48c6-8dc0-5cf5a53c0e34 or 22098786-6e16-43cc-a27d-191a01a1e3b5) with password-only amr claim and no MFA.
Detects bulk enumeration of Microsoft Graph API endpoints (users, groups, devices, service principals) characteristic of tools like AzureHound or roadtx. The detection focuses on high-frequency GET requests originating from known Edge browser client IDs associated with CA policy bypass (CVE-2025-0309) where tokens lack MFA claims, indicating unauthorized reconnaissance in an Azure/Entra ID environment.
Detects stolen session token reuse to bypass MFA by correlating a successful SSO/VPN login from one IP with a subsequent successful login from a different IP using the same user agent context, or a user-agent change between sessions for the same user within a short window. Targets access broker technique where infostealer-harvested session cookies are replayed from different source IPs.
Detects network logon events (Logon Type 3) using NTLM authentication where the source IP address is local (127.0.0.1 or ::1). This behavior can be indicative of attempts to interact with local services or perform lateral movement within the same host using credential-based techniques such as 'Pass-the-Hash' or unauthorized access to local resources.
Detects successful authentication events from accounts identified as service, managed, or robot accounts (e.g., svc_, sa_, msol, robot) originating from external IP addresses or exhibiting an unusually high number of distinct source IP addresses. This behavior is indicative of potential credential theft, token replay attacks, or unauthorized usage of service account identities.
Detects the use of the RoadTx tool to perform a Resource Owner Password Credential (ROPC) grant against Microsoft Graph while bypassing MFA. This behavior leverages CVE-2025-0309 by abusing hidden Conditional Access exclusions for specific client IDs, resulting in an authentication token issued without an MFA claim.
Detects browser/node subprocesses spawned by AutoGen/Python processes making loopback WebSocket connections to the AutoGen Studio MCP control plane, which is indicative of the AutoJack exploit chain. This rule specifically looks for Python processes associated with 'autogen' or 'autogenstudio' that initiate network connections to loopback addresses on ports 8080 or 8081, often with specific URL paths related to the MCP WebSocket API.
Detects sign-in events where Conditional Access was not applied for Microsoft Graph access using low-privileged client IDs known to trigger hidden CA exclusions. Tokens issued with only single-factor authentication to Graph indicate exploitation of the hidden scope exclusion behavior introduced when any exclusion is added to an 'All resources' CA policy (CVE-2025-0309). Additionally, this rule identifies audit log events for Conditional Access policy modifications that add exclusions.
Detects network logon events (Logon Type 3) using NTLM authentication where the source IP address is local (127.0.0.1 or ::1). This behavior can be indicative of attempts to interact with local services or perform lateral movement within the same host using credential-based techniques such as 'Pass-the-Hash' or unauthorized access to local resources.
Detects successful authentication events from accounts identified as service, managed, or robot accounts (e.g., svc_, sa_, msol, robot) originating from external IP addresses or exhibiting an unusually high number of distinct source IP addresses. This behavior is indicative of potential credential theft, token replay attacks, or unauthorized usage of service account identities.
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