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Attack Tree Analysis for home-assistant/core

Objective: Gain unauthorized control of devices and/or exfiltrate sensitive data managed by a Home Assistant instance.

Attack Tree Visualization

Gain Unauthorized Control/Exfiltrate Data
└── 2. Exploit Integrations
    ├── 2.1 Custom Integration Vulnerabilities (High Risk)
    │   ├── 2.1.1 Code Injection Vulnerabilities (High Risk)
    │   └── 2.1.2 Supply Chain Vulnerabilities (High Risk)
    └── 2.2 Official Integration Vulnerabilities
        └── 2.2.1 Known Vulnerabilities (High Risk)
└── 3. Leverage Configuration Weaknesses
    ├── 3.1 Weak/Default Credentials (High Risk)
    └── 3.2 Exposed Secrets in Configuration (High Risk)
└── 1. Compromise Core Functionality
    └── 1.2 Authentication Bypass / State Manipulation
        └── 1.2.1 Token Theft (High Risk)

Attack Tree Path: 1.2.1 Token Theft (High Risk)

  • Description: An attacker gains access to a valid authentication token, allowing them to impersonate a legitimate user and control Home Assistant.
  • Likelihood: High. Tokens can be stolen through various means, including phishing, malware, network sniffing (if not using HTTPS), or exploiting vulnerabilities in other applications on the same network.
  • Impact: High. Full control over the Home Assistant instance, including all connected devices and data.
  • Effort: Medium. The effort depends on the method used to steal the token. Phishing might be low effort, while exploiting a network vulnerability could be higher.
  • Skill Level: Medium. Requires some technical knowledge, but readily available tools and techniques can be used.
  • Detection Difficulty: Medium to High. Detecting token theft can be difficult without proper logging and monitoring. Unusual activity from a legitimate user account might be a sign.

Attack Tree Path: 2.1 Custom Integration Vulnerabilities (High Risk)

  • Description: Exploiting vulnerabilities in third-party integrations installed by the user.
  • Likelihood: High. Custom integrations are not subject to the same level of scrutiny as official integrations, and many are developed by individuals with varying levels of security expertise.
  • Impact: High. A compromised integration can grant the attacker full control over Home Assistant.
  • Effort: Low to Medium. Finding and exploiting vulnerabilities in custom integrations may be easier than in core components.
  • Skill Level: Low to Medium. Depends on the complexity of the vulnerability.
  • Detection Difficulty: High. Difficult to detect unless the integration's behavior is obviously malicious. Requires monitoring of integration activity and potentially code analysis.

Attack Tree Path: 2.1.1 Code Injection Vulnerabilities (High Risk)

  • Description: The custom integration contains code that allows an attacker to inject and execute arbitrary commands on the Home Assistant server.
  • Likelihood: High. Lack of code review and secure coding practices in custom integrations increases the likelihood of injection vulnerabilities.
  • Impact: High. Complete system compromise.
  • Effort: Medium. Requires finding and exploiting the injection point.
  • Skill Level: Medium. Requires understanding of the integration's code and how to craft malicious input.
  • Detection Difficulty: High. Can be difficult to detect without code analysis or intrusion detection systems.

Attack Tree Path: 2.1.2 Supply Chain Vulnerabilities (High Risk)

  • Description: The developer of a custom integration is compromised, and malicious code is injected into an update.
  • Likelihood: Medium to High. This is a growing threat across the software industry. Developers of custom integrations may not have robust security practices for their own systems.
  • Impact: High. Complete system compromise for all users of the compromised integration.
  • Effort: High. Requires compromising the developer's accounts or infrastructure.
  • Skill Level: High. Requires advanced hacking skills.
  • Detection Difficulty: Very High. Extremely difficult to detect without proactive monitoring of integration updates and code integrity checks.

Attack Tree Path: 2.2.1 Known Vulnerabilities in Official Integrations (High Risk)

  • Description: Exploiting publicly known vulnerabilities in official integrations that have not been patched by the user.
  • Likelihood: High. Many users do not update their software regularly.
  • Impact: High (Variable). Depends on the specific vulnerability, but could range from data leakage to full system compromise.
  • Effort: Low. Exploits for known vulnerabilities are often publicly available.
  • Skill Level: Low. Script kiddies can often exploit known vulnerabilities using publicly available tools.
  • Detection Difficulty: Medium. Intrusion detection systems and vulnerability scanners can detect attempts to exploit known vulnerabilities.

Attack Tree Path: 3.1 Weak/Default Credentials (High Risk)

  • Description: Gaining access to the Home Assistant instance using default or easily guessable passwords.
  • Likelihood: High. Many users fail to change default credentials or use weak passwords.
  • Impact: High. Full control over the Home Assistant instance.
  • Effort: Low. Brute-force attacks or credential stuffing attacks are easy to automate.
  • Skill Level: Low. Requires minimal technical skills.
  • Detection Difficulty: Medium. Failed login attempts can be logged, but attackers may use slow brute-force techniques to avoid detection.

Attack Tree Path: 3.2 Exposed Secrets in Configuration (High Risk)

  • Description: Sensitive information (API keys, passwords) stored in plain text in the configuration.yaml file are exposed.
  • Likelihood: High. Users may not be aware of the best practices for storing secrets. Accidental exposure through misconfigured file sharing or backups is also possible.
  • Impact: High. Leads to compromise of connected services and potentially the Home Assistant instance itself.
  • Effort: Low. If the configuration file is accessible, the secrets are easily obtained.
  • Skill Level: Low. No special skills required.
  • Detection Difficulty: Medium to High. Requires monitoring file access and potentially implementing data loss prevention (DLP) measures.