Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
260 detections
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PA Threat Prevention for potential exploitation of PHP2Shell vulnerabilities CVE-2026-109618 and CVE-2026-109619.
Detects a high volume of authentication failures followed by a successful authentication from the same source IP address against edge devices like FortiGate or Palo Alto GlobalProtect within a specific time window.
Detects successful Palo Alto GlobalProtect VPN authentications where no Multi-Factor Authentication (MFA) challenge or related text is recorded in the firewall logs, and no corresponding successful MFA sign-in event is found in Entra ID (SigninLogs).
The following analytic detects network traffic associated with known remote access software applications, such as AnyDesk, GoToMyPC, LogMeIn, and TeamViewer.
It leverages Palo Alto traffic logs mapped to the Network_Traffic data model in Splunk. This activity is significant because adversaries often use remote access tools to maintain unauthorized access to compromised environments.
If confirmed malicious, this activity could allow attackers to control systems remotely, exfiltrate data, or deploy additional malware, posing a severe threat to the organization's security.
It leverages Palo Alto traffic logs mapped to the Network_Traffic data model in Splunk. This activity is significant because adversaries often use remote access tools to maintain unauthorized access to compromised environments.
If confirmed malicious, this activity could allow attackers to control systems remotely, exfiltrate data, or deploy additional malware, posing a severe threat to the organization's security.
Detects VPN connection events where the client hostname contains the string 'kali', which may indicate the use of a penetration testing operating system or a suspicious device connecting to the corporate network via Palo Alto Networks GlobalProtect.
Detects shell or interpreter processes spawned as children of the
PAN-OS management web service. Exploitation of CVE-2026-0322 (authenticated RCE,
CWE-94) in the management interface results in the web server process forking
unexpected /bin/sh, curl, wget or scripting interpreter children to run
post-exploitation commands on the management plane.
PAN-OS management web service. Exploitation of CVE-2026-0322 (authenticated RCE,
CWE-94) in the management interface results in the web server process forking
unexpected /bin/sh, curl, wget or scripting interpreter children to run
post-exploitation commands on the management plane.
The following analytic detects the execution of known remote access software within the environment.
It leverages network logs mapped to the Web data model, identifying specific URLs and user agents associated with remote access tools like AnyDesk, GoToMyPC, LogMeIn, and TeamViewer.
This activity is significant as adversaries often use these utilities to maintain unauthorized remote access. If confirmed malicious, this could allow attackers to control systems remotely, exfiltrate data, or further compromise the network, posing a severe security risk.
It leverages network logs mapped to the Web data model, identifying specific URLs and user agents associated with remote access tools like AnyDesk, GoToMyPC, LogMeIn, and TeamViewer.
This activity is significant as adversaries often use these utilities to maintain unauthorized remote access. If confirmed malicious, this could allow attackers to control systems remotely, exfiltrate data, or further compromise the network, posing a severe security risk.
The following analytic identifies ICMP traffic to external IP addresses with total bytes (sum of bytes in and bytes out) greater than 1,000 bytes.
It leverages the Network_Traffic data model to detect large ICMP packet that aren't blocked and are directed toward external networks. We use All_Traffic.bytes in the detection to capture variations in inbound versus outbound traffic sizes, as significant discrepancies or unusually large ICMP exchanges can indicate information smuggling, covert communication, or command-and-control (C2) activities.
If validated as malicious, this could signal ICMP tunneling, unauthorized data transfer, or compromised endpoints requiring immediate investigation.
It leverages the Network_Traffic data model to detect large ICMP packet that aren't blocked and are directed toward external networks. We use All_Traffic.bytes in the detection to capture variations in inbound versus outbound traffic sizes, as significant discrepancies or unusually large ICMP exchanges can indicate information smuggling, covert communication, or command-and-control (C2) activities.
If validated as malicious, this could signal ICMP tunneling, unauthorized data transfer, or compromised endpoints requiring immediate investigation.
Suspicious Connection to Custom GPT
Cortex XDR
Detects outbound web traffic to OpenAI ChatGPT Custom GPTs where the URL slug contains keywords potentially indicative of unauthorized or non-standard usage, such as keywords implying premium, professional, or official status, which could be used as a cover for data exfiltration or credential gathering via malicious or typo-squatted GPT instances.
Detects network activity (DNS queries, HTTP Host headers, and TLS SNI) directed towards the known Blinder Tunnel staging domain 'asdfafadafg.online'. This behavior is indicative of command-and-control (C2) communication or initial staging of malicious payloads.
Detects signs of exploitation targeting a PAN-OS GlobalProtect authentication bypass vulnerability (CVE-2026-0257). The rule identifies an initial network request with invalid or malformed session cookies aimed at GlobalProtect endpoints, followed immediately by unauthorized access attempts to administrative portal interfaces from the same source IP address.
Detects potential Cobalt Strike or Sliver command and control (C2) beaconing behavior by analyzing network proxy, firewall, and flow logs for common C2 URI patterns, known malicious JA3/JA3S TLS fingerprints, and consistent periodic communication intervals (low jitter) characteristic of automated beacons.
Detects repeated SSH authentication failures originating from an external source on port 22, where the username pattern appears to be programmatically generated or enumerated (e.g., username followed by digits). This behavior is characteristic of automated brute-force attempts targeting common SSH services.
Detects network activity (DNS queries, HTTP Host headers, and TLS SNI) directed towards the known Blinder Tunnel staging domain 'asdfafadafg.online'. This behavior is indicative of command-and-control (C2) communication or initial staging of malicious payloads.
Detects network activity (DNS queries, HTTP Host headers, and TLS SNI) directed towards the known Blinder Tunnel staging domain 'asdfafadafg.online'. This behavior is indicative of command-and-control (C2) communication or initial staging of malicious payloads.
Detects network activity (DNS queries, HTTP Host headers, and TLS SNI) directed towards the known Blinder Tunnel staging domain 'asdfafadafg.online'. This behavior is indicative of command-and-control (C2) communication or initial staging of malicious payloads.
This rule detects potential unauthorized account creation by correlating suspicious administrative activity on network edge devices (VPNs, firewalls) with subsequent local administrator account creation on an internal host within a one-hour window. This behavior is indicative of ransomware affiliates exploiting internet-facing infrastructure to gain initial access and escalate privileges.
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects potential AI-targeted cloaking, a technique where a web server serves different content to AI crawlers versus human users, identified by comparing HTTP response sizes or hashes across session logs. The rule uses Microsoft Sentinel's ASIM Web Session schema to correlate web requests, identifying discrepancies that suggest malicious or evasive intent. Covers T1036 & T1027
Detects outbound network requests from endpoints to known 'uncensored' or jailbroken LLM-as-a-Service domains (e.g., WormGPT, FraudGPT). These platforms are specifically marketed to threat actors for illicit purposes like generating malware, phishing kits, or exploit code, and identifying access to them serves as a leading indicator of adversarial activity.
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