Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

4,311 detections

This rule detects suspicious activity where an Azure CLI session, initially interactive, is followed by non-interactive access from a different IP address. This could indicate an attacker using a stolen token or session from a legitimate user's interactive login to perform automated actions. The rule specifically looks for a pivot from interactive to non-interactive access where the non-interactive access occurs after the interactive access and from a different IP address, within a 30-day lookback window.
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F S@Fsdr
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Detections.ai Community
10 months ago
12912850
Detects the execution of Mimikatz for credential dumping shortly after the WDigest 'UseLogonCredential' registry key is enabled. This combination of TTPs is associated with the Qilin ransomware group.
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Georg Lauenstein@gsec
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SecOps Signals
10 months ago
62220
Detects suspicious process access to common credential storage locations such as certificate stores, PCPKSP keys, and CloudAPCache for AzureAD credentials. The severity of the alert is escalated based on the initiating process and command line arguments, specifically looking for keywords like 'mimikatz', 'dump', or 'export'.
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Benjamin Zulliger@benscha
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Detections.ai Community
10 months ago
747483
Detects a sequence of events where an AWS IAM Role Trust Policy or a Role's managed policy is modified (UpdateAssumeRolePolicy, PutRolePolicy) and is immediately followed by a successful assumption of that role (AssumeRole, AssumeRoleWithSAML, etc.) within a 10-minute window. This behavior is characteristic of an attacker setting up a backdoor or escalating privileges by granting a new, unauthorized principal (user, service, or account) permission to assume a critical role.
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tayvion payton@tayontech
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Detections.ai Community
10 months ago
146262
This rule detects when known code scanning tools like Trufflehog, Gitleaks, or Gittyleaks attempt to read the AWS credentials file. This activity could indicate an adversary or an internal security tool searching for sensitive AWS access keys and tokens.
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Lacey Cochrane@NullVectorX
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XQL Threat Forge
10 months ago
122309
This rule detects suspicious activity related to Microsoft 365 Device Code OAuth consent flows. It specifically looks for device code authentications that are single-factor or lack MFA, and then groups these by IP address and client application. The rule identifies suspicious patterns such as a high number of logins, unique users, or unique applications from a single IP address, or rapid login attempts within a short timeframe, which could indicate enumeration or phishing attempts.
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Lacey Cochrane@NullVectorX
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XQL Threat Forge
10 months ago
253291
Detects the creation of a browser process in headless mode and in a suspended state. This technique is used by infostealers like AuraStealer to inject code into the browser process to bypass Application-Bound Encryption (ABE) and steal credentials.
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Tim Peck@timpeck
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Detections.ai Community
10 months ago
43115
Detects the ToddyCat APT group's technique of using PowerShell to connect to remote hosts via SMB admin shares (C$) and steal web browser credentials. This is associated with a variant of the TomBerBil tool and is particularly significant when observed originating from a domain controller.
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Tim Peck@timpeck
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Detections.ai Community
10 months ago
103155
Detects RAT command structure
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Daniel Jeremiah@daniyyell
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Detections.ai Community
10 months ago
0015
This rule detects patterns indicative of an Evilginx-style Adversary-in-the-Middle (AiTM) phishing attack. It specifically looks for HTTP requests to hostnames ending in suspicious top-level domains (TLDs) such as .click, .online, .cloud, or .shop, combined with specific URI paths like /wlc/, /load/, or /success/. These patterns are commonly used by AiTM redirectors to capture credentials and session tokens.
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Tim Peck@timpeck
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Detections.ai Community
10 months ago
102180
This rule detects attempts to enable WDigest credential caching by modifying the 'UseLogonCredential' registry value to '1' under a key containing 'WDigest'. The detection specifically looks for this modification being performed by a process whose image name matches a custom batch file pattern (e.g., ending with '!light*.bat'). This activity is associated with Qilin ransomware, which has been observed using this technique for credential access.
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Lacey Cochrane@NullVectorX
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XQL Threat Forge
10 months ago
112351
This detection monitors for the creation or deletion of files within the TokenBroker and AAD Broker Plugin cache folders. These folders store authentication tokens that, if accessed or manipulated by an unauthorized process, could indicate credential theft activity.
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James Eduard Andaya@JamesEduard
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Detections.ai Community
10 months ago
340221
Detects the DriverFixer0428 macOS credential stealer, attributed to the North Korean 'Contagious Interview' campaign. This rule identifies the malware based on unique internal strings, network IOCs related to Dropbox exfiltration, and social engineering text.
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Tim Peck@timpeck
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Detections.ai Community
10 months ago
40106
Detects successful Microsoft 365 sign-ins using the OAuth 2.0 device code grant flow for applications with low prevalence. This technique is used by threat actors to gain unauthorized access to accounts, bypassing some MFA controls.
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Tim Peck@timpeck
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Detections.ai Community
11 months ago
123287
This detection identifies network connections to known first-stage Microsoft 365 phishing domains associated with an active Adversary-in-the-Middle (AiTM) campaign.
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Ranger007 _@Ranger007
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Detections.ai Community
11 months ago
612382
Identifies JSON Web Tokens (JWTs) where the signing algorithm in the header ('alg') is set to 'none'. A server that incorrectly trusts this header may skip signature validation, allowing an attacker to create arbitrary tokens and bypass authentication controls.
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Tim Peck@timpeck
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Detections.ai Community
10 months ago
5054
Detects AWS IAM roles whose trust policies were newly created or updated to allow cross account AWS principals to assume the role without any confused deputy protections in place.
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tayvion payton@tayontech
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Detections.ai Community
11 months ago
82231
Detects when an AWS IAM role is assumed by an identity that has not used that specific role within a historical 7-day window. This behavior can indicate lateral movement, privilege escalation, compromised credentials, or a deviation from normal workload patterns. The rule excludes AWS internal service identities to focus on human and workload actors.
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tayvion payton@tayontech
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Detections.ai Community
11 months ago
71180
This detection identifies cases where a successful device registration event in Azure AD occurs shortly after a successful Resource Owner Password Credentials (ROPC) authentication to Microsoft Intune Enrollment via the Microsoft Authentication Broker.

Microsoft allows specific application and resource combinations access without a previously registered device.

An access token issued for the Microsoft Authentication Broker application and the Intune Enrollment resource can be used to authenticate and initiate the device join process.

An attacker can leverage the token to bypass CA, register device, and establish persistence. Once registered, attacker gets a Primary Refresh Token (PRT), valid for 90 days.

The following query joins ROPC successful sign-ins, to successful device registrations. Registrations that occur soon after a ROPC event (2 days in this instance) could be an indicator of abuse.
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Will Shaw@SheffShaw94
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Detections.ai Community
11 months ago
381286
Detects the creation of a new domain user account that is immediately added to a high-privilege group, such as Domain Admins. This pattern is a strong indicator of persistence and privilege escalation, as observed in the Lynx Ransomware campaign.
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Tim Peck@timpeck
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Detections.ai Community
11 months ago
71193
This rule detects potential Browser-in-the-Browser (BITB) phishing attacks, specifically targeting the 'Sneaky2FA' technique. It looks for HTTP responses containing an iframe, base64 encoded image data, and the string ';base64,', which are indicators of a malicious page attempting to mimic a legitimate login portal within an iframe to steal credentials.
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Tim Peck@timpeck
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Detections.ai Community
11 months ago
42183
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