Linux Intrusion Detection Playbook
Introduction: The Need for Effective Linux Intrusion Detection Capabilities
Linux systems are a fundamental part of enterprise infrastructure, powering cloud environments, servers, and critical applications. As their adoption increases, so do the threats targeting them, ranging from privilege escalation and unauthorised access to rootkits, fileless malware, and advanced persistent threats (APTs). Attackers often leverage stealthy techniques such as living-off-the-land (LotL) tactics, kernel-level exploits, and misconfiguration abuse to evade detection, making traditional security approaches insufficient for Linux environments.
Effective Linux intrusion detection capabilities and processes are essential for identifying, analysing, and mitigating security threats before they escalate into full-scale incidents. A robust detection strategy should combine real-time system monitoring, anomaly-based detection, log analysis, behavioural analytics, and integration with Security Information and Event Management (SIEM) solutions. Additionally, leveraging Endpoint Detection and Response (EDR), host-based intrusion detection systems (HIDS), and proactive threat-hunting methodologies enhances visibility into suspicious activities.
To stay ahead of adversaries, security teams must implement continuous monitoring, automated alerting, and forensic investigation processes tailored to Linux environments. By establishing a well-defined intrusion detection framework, organisations can improve their security resilience, minimise attack dwell time, and protect critical assets from evolving cyber threats.
Table of Contents
Initial Compromise Detection
Detect Suspicious Processes
Identify Exploited Services
Advanced Suspicious Command Detection
Persistence Mechanisms
Detect Cronjob Modifications
Monitor SSH Key Additions
Advanced Persistence Detection via Startup Scripts
Privilege Escalation and Credential Theft
Detect Sudo Abuse
Credential Dumping Attempts
Advanced Kernel Exploit Detection
Lateral Movement Detection
Detect SSH Lateral Movement
Monitor File Transfers via SCP or Rsync
Monitor File Transfers via SCP or Rsync
Advanced Detection of Exploited Protocols
Data Exfiltration Indicators
Large Data Transfers via Network
Use of Compression Tools
DNS or HTTPS Exfiltration
Post-Incident Investigation
Correlation of File Hashes
Compromised User Accounts
Incident Timeline Reconstruction
Conclusion
This playbook provides a structured approach to investigating Linux-based intrusions in an enterprise environment. Each section focuses on specific detection and analysis phases using advanced queries and techniques.
1. Initial Compromise Detection
The first step is identifying the initial point of compromise, often involving malicious processes or exploited services.
Query Option 1: Detect Suspicious Processes
Description: Detects processes with unusually high CPU or memory usage. Results include timestamps, hostnames, and resource utilization details.
Query Option 2: Identify Exploited Services
Description: Identifies active listening services on common ports (SSH, HTTP, HTTPS). Results include process details and ports.
Query Option 3: Advanced Suspicious Command Detection
Description: Searches for potentially malicious commands executed in the shell. Results include timestamps, users, and command details.
2. Persistence Mechanisms
Attackers often use persistence techniques to maintain access.
Query Option 1: Detect Cronjob Modifications
Description: Tracks cronjob modifications. Results show command-line entries associated with cron edits.
Query Option 2: Monitor SSH Key Additions
Description: Identifies modifications to SSH authorized_keys files. Results display timestamps, hosts, and file paths.
Query Option 3: Advanced Persistence Detection via Startup Scripts
Description: Detects changes in startup scripts, which may indicate persistence. Results show modified or created files.
3. Privilege Escalation and Credential Theft
Detecting privilege escalation and credential theft attempts is crucial to mitigating further damage.
Query Option 1: Detect Sudo Abuse
Description: Identifies sudo command usage. Results include command details, users, and timestamps.
Query Option 2: Credential Dumping Attempts
Description: Detects potential credential dumping attempts. Results display commands executed by users.
Query Option 3: Advanced Kernel Exploit Detection
Description: Analyzes kernel logs for signs of exploit attempts. Results provide timestamps and messages.
4. Lateral Movement Detection
Attackers often spread across the network after the initial compromise.
Query Option 1: Detect SSH Lateral Movement
Description: Identifies SSH public key logins. Results include source and destination IPs.
Query Option 2: Monitor File Transfers via SCP or Rsync
Description: Tracks file transfer activities. Results display commands and associated users.
Query Option 3: Advanced Detection of Exploited Protocols
Description: Monitors network traffic on commonly exploited protocols. Results highlight large data transfers.
5. Data Exfiltration Indicators
Signs of data exfiltration should be promptly identified to mitigate loss.
Query Option 1: Large Data Transfers via Network
Description: Identifies large outbound data transfers. Results display destinations and transfer sizes.
Query Option 2: Use of Compression Tools
Description: Detects the use of compression tools, often a precursor to exfiltration. Results show commands and users.
Query Option 3: DNS or HTTPS Exfiltration
Description: Monitors DNS and HTTPS traffic for anomalies. Results display domain names and data volumes.
6. Post-Incident Investigation
Once the threat is contained, further investigation can determine the scope and impact.
Query Option 1: Correlation of File Hashes
Description: Compares file hashes with known malicious hashes. Results include file paths and matching hashes.
Query Option 2: Compromised User Accounts
Description: Tracks invalid login attempts targeting non-existent users. Results include usernames and source IPs.
Query Option 3: Incident Timeline Reconstruction
Description: Combines multiple data sources to reconstruct an incident timeline. Results provide a comprehensive view of activities.
Conclusion
The playbook offers a good approach to detecting and analysing compromises in an environment. However, its usefulness depends on the environment and tools at your disposal. For an environment where KQL is an option, the queries may require some adaptation to specific data sources and infrastructure setup.
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