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attack-tree.md

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Attack Tree Analysis for cocoalumberjack/cocoalumberjack

Objective: Exfiltrate sensitive data OR disrupt the application's availability/integrity by manipulating the logging system.

Attack Tree Visualization

                                     +-----------------------------------------------------+
                                     |  Exfiltrate Sensitive Data OR Disrupt Application   |
                                     +-----------------------------------------------------+
                                                  /                      |
         ---------------------------------------------------     -------------------------
        |  1. Access Logged Data  |                   | 2. Manipulate Logging  |
         ---------------------------------------------------     -------------------------
               /              \                                     /
  -----------------   -----------------                   -----------------
 | 1.1 Unauthorized| | 1.3 Log Injection|                 | 2.1 Log Flooding|
 | File Access    | | (Data Exposure) |                 | (DoS)          |
  -----------------   -----------------                   -----------------
      /                       | [CRITICAL]                        |
-------------           -------------                   -------------
|1.1.1     |           |1.3.1      |                   |2.1.1      |
|Exploit   |           |Untrusted  |                   |High Volume|
|OS Vuln. |           |Input to   |                   |of Logs    |
|to Gain  |           |Log Fields |                   |           |
-------------           -------------                   -------------
      | [HIGH RISK]            | [HIGH RISK]                    | [HIGH RISK]
-------------           -------------                   -------------
|1.1.1.1   |           |1.3.1.1   |                   |2.1.1.1   |
|CVE-XXXXX |           |Crafted    |                   |Resource  |
|          |           |Payload    |                   |Exhaustion|
-------------           -------------                   -------------

Attack Tree Path: 1. Access Logged Data

  • 1.1 Unauthorized File Access [HIGH RISK]
    • Description: The attacker gains unauthorized access to the log files stored on the system.
    • 1.1.1 Exploit OS Vulnerability to Gain Access
      • Description: The attacker leverages a vulnerability in the operating system (e.g., a privilege escalation bug, a remote code execution flaw) to gain access to the file system where the log files are stored.
      • 1.1.1.1 CVE-XXXXX: A specific, known vulnerability (represented by a CVE identifier) is exploited. This could be any vulnerability that allows the attacker to gain unauthorized file system access.
      • Likelihood: Low (if the system is regularly patched), Medium (if patching is infrequent)
      • Impact: High to Very High (full system compromise is possible, leading to complete log data access)
      • Effort: Medium to High (depends on the specific vulnerability and its exploitability)
      • Skill Level: Intermediate to Advanced (requires knowledge of OS vulnerabilities and exploit development)
      • Detection Difficulty: Medium to Hard (depends on the presence and effectiveness of intrusion detection/prevention systems, security logging, and anomaly detection)

Attack Tree Path: 1.3 Log Injection (Data Exposure) [CRITICAL] [HIGH RISK]

  • Description: The attacker injects malicious data into the log files by exploiting vulnerabilities in the application's input handling.
    • 1.3.1 Untrusted Input to Log Fields
      • Description: The application logs data from untrusted sources (e.g., user input, HTTP headers, external API responses) without proper sanitization, validation, or encoding. This allows an attacker to inject arbitrary content into the log files.
      • 1.3.1.1 Crafted Payload: The attacker crafts a specific input string designed to exploit a vulnerability or achieve a specific malicious goal. This could be:
        • Cross-Site Scripting (XSS) Payload: If log files are displayed in a web interface without proper output encoding, an attacker can inject JavaScript code that will be executed in the context of the user viewing the logs.
        • Command Injection Payload: If log files are parsed by another script or process, an attacker might be able to inject commands that will be executed by that script.
        • SQL Injection Payload: If log data is later used in database queries without proper sanitization, an attacker could inject SQL code.
        • Data Exfiltration Payload: The attacker could inject data that, when logged, reveals sensitive information from the application's environment or memory.
      • Likelihood: Medium to High (very common vulnerability in web applications)
      • Impact: Medium to High (depends on what is logged and how the logs are used; can lead to XSS, command injection, SQL injection, data exfiltration, and other attacks)
      • Effort: Low to Medium (crafting the payload may require some understanding of the application's logic)
      • Skill Level: Intermediate (requires knowledge of web application vulnerabilities and injection techniques)
      • Detection Difficulty: Medium (requires careful analysis of log content, application logic, and input validation mechanisms; may be difficult to distinguish from legitimate log entries)

Attack Tree Path: 2. Manipulate Logging

  • 2.1 Log Flooding (DoS) [HIGH RISK]
    • Description: The attacker overwhelms the logging system by generating a large volume of log entries, leading to resource exhaustion and denial of service.
    • 2.1.1 High Volume of Logs
      • Description: The attacker sends a large number of requests to the application, or triggers actions within the application, that cause excessive logging activity.
      • 2.1.1.1 Resource Exhaustion: The primary goal is to exhaust system resources, such as:
        • Disk Space: Filling up the disk space allocated for log files, preventing the application from writing new log entries and potentially causing other application failures.
        • CPU and Memory: While CocoaLumberjack is efficient, excessive logging can still consume CPU and memory resources, especially if complex formatting or filtering is involved.
        • Network Bandwidth: If logs are sent to a remote logging server, excessive logging can saturate the network connection.
      • Likelihood: Medium to High (depends on the application's attack surface, rate limiting, and input validation)
      • Impact: Medium (service disruption, potential data loss if logging is critical for auditing or recovery)
      • Effort: Low to Medium (can often be achieved with simple scripts or automated tools)
      • Skill Level: Novice to Intermediate (requires basic scripting or knowledge of automated testing tools)
      • Detection Difficulty: Easy (monitoring disk space usage, log volume, and application performance metrics will quickly reveal this type of attack)