CDR

XSIAM-Prisma CDR Lab

Overview

This repository serves as a comprehensive lab environment for practicing Cloud Detection and Response (CDR) using XSIAM and Prisma Cloud. The labs are designed to simulate real-world cloud-native threats, leveraging Kubernetes, container orchestration platforms, and Palo Alto Networks technologies. These labs provide a hands-on approach to explore advanced detection techniques and response scenarios against cloud workloads, enabling users to master the application of cloud security tools and methodologies in a controlled environment.

Key scenarios include detection of containerized cryptominers, identifying vulnerable deployments, analyzing behavioral anomalies using ABIOC (Analytics Behavior Indicator of Compromise) techniques, and integrating WildFire threat intelligence for enhanced detection capabilities. By utilizing these labs, practitioners will gain practical experience with critical cloud security components that are essential for a robust security posture.

Summarization and Analysis of the Script for Container-Specific Detection

This script is a comprehensive simulation of malicious activity designed to test detection and response capabilities in a containerized environment. It encompasses multiple MITRE ATT&CK tactics and techniques while leveraging the capabilities of a lightweight container like BusyBox/Alpine. Below is a breakdown of the script activities:

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1. Initial Setup

• System Preparation: Updates and upgrades the Alpine package manager.
• Tool Installation: Installs various tools to enable scanning, enumeration, and exploitation:
  • Network tools: nmap, tor, socat
  • Script execution environments: bash, python3, busybox-extras
  • Build tools: gcc, clang, cmake, openssl-dev

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2. Simulated Scenarios

Scenario 1: Enumeration and Reconnaissance

• LinEnum and Linpeas Execution: Downloads and runs enumeration scripts to collect Linux system and privilege information.
• Objective: Simulate discovery and data collection activities (T1082, T1016).

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Scenario 2: Malware Simulation

• Unix Backdoor and Conti Malware:
  • Downloads, executes, and replicates backdoor binaries in suspicious directories (/bin, /loader.sh).
  • Simulates ransomware behavior with Conti and Unix backdoors (T1486).
• Objective: Test detection for malicious file downloads, privilege escalations, and persistence mechanisms.

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Scenario 3: MITRE ATT&CK TTP Demonstrations

• Initial Access and Execution:
  • Attempts SSH access (T1078).
  • Creates a reverse shell using Bash and Netcat (T1059.004).
• Persistence:
  • Adds cron jobs and modifies .profile for backdoor access (T1053.005).
• Privilege Escalation:
  • Modifies sudoers and switches to root (T1548.002).
• Defense Evasion:
  • Deletes logs and restricts access to /etc/shadow (T1070.001, T1070.004).
• Credential Access:
  • Dumps /etc/shadow and extracts passwords from .bash_history (T1003).
• Discovery:
  • Gathers system info, network interfaces, processes, and directory listings (T1083, T1049).
• Lateral Movement:
  • Attempts SSH to a target machine (T1021.001).
• Data Collection and Exfiltration:
  • Archives and exfiltrates data using tar and Netcat (T1560, T1041).

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Scenario 4: Container Enumeration and Exploitation

• DEEPCE Usage:
  • Downloads and runs container enumeration scripts (DEEPCE) to simulate privilege escalation (T1611).
• Objective: Test detection of container-specific exploits like privileged mode abuse.

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Scenario 5: Network Scanning

• Local and Remote Scans:
  • Performs network scanning using Nmap for local and external addresses (T1046).
• Objective: Simulate network discovery activities for detecting reconnaissance.

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Scenario 6: Execution of Malware

• Backdoors, C2 Clients, and Malware Execution:
  • Executes malicious binaries and scripts such as Conti ransomware and Unix backdoor (T1105).
• Error Handling: Suppresses errors during execution for resilience against detection failures.

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Detection and Behavioral Triggers

1. Network Activity:
   • Unusual outbound connections (e.g., reverse shells, C2 traffic).
   • Network scanning and reconnaissance.
2. File System Changes:
   • Creation of suspicious files and binaries in /bin or /loader.sh.
   • Modifications to /etc/sudoers and /etc/shadow.
3. Process Behavior:
   • Execution of enumeration scripts and malware binaries.
   • Privileged operations via sudo or capabilities.
4. Persistence Indicators:
   • Newly added cron jobs.
   • Modifications to .profile for backdoor access.
5. Exfiltration:
   • Use of tar, nc, and direct outbound transfers.

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Opportunities for Detection in Containers

• Container Escape: Monitoring for attempts to exploit privileged containers (DEEPCE, privileged shell operations).
• File Access Patterns: Detect unusual reads/writes to sensitive files like /etc/shadow.
• Network Anomalies: Alert on scanning, reverse shell attempts, or unauthorized outbound connections.
• Malware Artifacts: Scan for known malicious binaries or hashes.
• Log Tampering: Detect deletion of log files in /var/log.

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This script offers a robust way to simulate malicious activities and evaluate the effectiveness of your container-specific detection tools. It covers multiple attack vectors and provides opportunities to validate response mechanisms against real-world threats.

Reference Links

https://docs-cortex.paloaltonetworks.com/r/Cortex-XSIAM/Cortex-XSIAM-Documentation/Ingest-alerts-and-assets-from-Prisma-Cloud