Lacey Cochrane
@NullVectorXUSTrusted contributorCompletionist
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232 detections
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Azure AD Device Code Flow Token Phishing
Cortex XDR
Detects potential device code phishing attacks by identifying OAuth token requests associated with the device code flow that originate from unmanaged or non-compliant devices. The rule specifically monitors for suspicious Cmsi (Client Managed Service Identity) activity or the use of unbound sign-in tokens within the device code flow for targeted Microsoft productivity and management applications.
Detects the creation of scheduled tasks on remote hosts by monitoring for the NetrJobAdd function call (opnum 0) against the ATSVC RPC interface (UUID: 1FF70682-0A51-30E8-076D-740BE8CEE98B). This interface is associated with the legacy Windows AT scheduler, which is frequently abused by offensive security tools like Impacket's atexec for remote command execution and lateral movement.
Detects unauthorized or suspicious use of the DsGetNCChanges (opnum 3) function on the DRSUAPI interface. This RPC method is commonly abused in DCSync attacks to replicate domain controller data, including sensitive password hashes, from an Active Directory environment.
Unsigned LDAP Bind
Cortex XDR
Detects Lightweight Directory Access Protocol (LDAP) binds that are performed without signing or encryption. Attack tools such as NetExec, ldapdomaindump, and Impacket frequently use simple, unencrypted LDAP binds over port 389, which can result in the transmission of credentials in cleartext. This rule monitors Windows Event ID 2889 on Domain Controllers, which logs cleartext LDAP bind attempts.
This rule monitors NetScaler ADC logs for indicators associated with the PitScaler campaign, specifically targeting exploitation of CVE-2026-88771 and CVE-2026-88772. It detects exploitation artifacts (DTLS handshake errors, NSPPE crashes), deployment of WHIPSHOT/SLAPSHOT malware, web shell installation, httpd.conf configuration tampering, persistence mechanisms involving privilege escalation (chmod), and connections to known malicious infrastructure.
This rule detects indicators of the PitScaler campaign targeting Citrix NetScaler ADC and Gateway appliances, exploiting vulnerabilities (CVE-2026-88771, CVE-2026-88772). It identifies the full attack chain including initial DTLS heap corruption exploitation, WHIPSHOT web shell C2 patterns, SLAPSHOT tunneling artifacts, web shell deployment files, httpd.conf PHP configuration tampering for persistence, privilege escalation via setuid /bin/sh modification, and anti-forensic log tampering.
ShadowCoerce NTLM Coercion via FssAgent
Cortex XDR
Detects unauthorized attempts to coerce the File Server VSS Agent (FssAgent) into authenticating to an attacker-controlled host. This is achieved by invoking the IsPathSupported (opnum 8) or IsPathShadowCopied (opnum 9) functions on the FssAgent RPC interface, which can be leveraged to capture NTLM hashes.
This rule monitors NetScaler ADC logs for indicators associated with the PitScaler campaign, specifically targeting exploitation of CVE-2026-88771 and CVE-2026-88772. It detects exploitation artifacts (DTLS handshake errors, NSPPE crashes), deployment of WHIPSHOT/SLAPSHOT malware, web shell installation, httpd.conf configuration tampering, persistence mechanisms involving privilege escalation (chmod), and connections to known malicious infrastructure.
This rule detects indicators of the PitScaler campaign targeting Citrix NetScaler ADC and Gateway appliances, exploiting vulnerabilities (CVE-2026-88771, CVE-2026-88772). It identifies the full attack chain including initial DTLS heap corruption exploitation, WHIPSHOT web shell C2 patterns, SLAPSHOT tunneling artifacts, web shell deployment files, httpd.conf PHP configuration tampering for persistence, privilege escalation via setuid /bin/sh modification, and anti-forensic log tampering.
Detects anomalous AWS Bedrock activity indicative of LLMjacking by correlating multiple phases of an attack chain (Model Enablement, Reconnaissance, Probing, and Execution) performed by a single identity within a short timeframe. This rule identifies attackers leveraging stolen IAM credentials to discover available AI models, probe for vulnerabilities, and execute unauthorized inference requests at scale.
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