attack-tree.md

Attack Tree Analysis for android/sunflower

Objective: To exfiltrate user data (specifically, plant data and potentially user-added notes/images) or to manipulate the application's state (e.g., marking plants as watered when they are not, deleting plants, adding malicious data).

Attack Tree Visualization

                                      Compromise Sunflower Application
                                                  |
                                      Data Exfiltration/Manipulation [HIGH]
                                                  |
                          -----------------------------------------------------
                          |                                                   |
                    Data Store                                      Intent Handling
                Vulnerabilities                                   Vulnerabilities
                          |                                                   |
                  -----------------                                   ---------------------
                  |                                                   |                     |
           **Unencrypted Data at Rest** [HIGH]                 **Malicious Intent Filters**  **Improper Intent Validation** [HIGH]

Attack Tree Path: Data Exfiltration/Manipulation [HIGH]

This is the primary attack vector, focusing on compromising the confidentiality and integrity of user data.

Attack Tree Path: Data Store Vulnerabilities

Attack Tree Path: Unencrypted Data at Rest (CRITICAL)

Description: The Sunflower application stores plant data in a local Room database (SQLite). If this database is not encrypted, an attacker with physical access to a compromised (rooted) device, or an attacker who has achieved arbitrary code execution through another vulnerability, can directly access the database file and extract all stored data. This includes plant names, descriptions, watering schedules, potentially user-added notes, and any other information stored in the database. * Attack Path: 1. Gain root access to the device (e.g., through a device vulnerability or social engineering). 2. Navigate to the application's data directory: /data/data/com.google.samples.apps.sunflower/databases/. 3. Locate the database file (e.g., sunflower-db). 4. Open the database file using a SQLite browser or command-line tools. 5. Extract the data from the tables. * Likelihood: Medium (High if encryption is not implemented; lower if it is). * Impact: High (Complete exposure of all user data stored in the database). * Effort: Low (If the device is rooted, accessing the file is trivial). * Skill Level: Low (Basic knowledge of Android file system and SQLite). * Detection Difficulty: High (Unless specific monitoring tools are in place, this is unlikely to be detected). * Mitigation: Implement strong database encryption using a library like SQLCipher or the AndroidX Security library's EncryptedFile (for associated files). The encryption key must be securely managed, ideally using the Android Keystore system, and never hardcoded in the application.

Attack Tree Path: Intent Handling Vulnerabilities

Attack Tree Path: Malicious Intent Filters (CRITICAL)

Description: If Sunflower declares intent filters in its AndroidManifest.xml that are too broad or do not specify the required permissions, a malicious application installed on the same device can send crafted intents to Sunflower. These intents could trigger unintended actions within Sunflower, potentially leading to data leakage or modification. For example, an intent filter designed to share plant data might be overly permissive, allowing a malicious app to request and receive sensitive information. * Attack Path: 1. A malicious application is installed on the device. 2. The malicious application constructs an intent that matches a vulnerable intent filter declared by Sunflower. 3. The malicious application sends the intent to Sunflower. 4. Sunflower's activity, service, or broadcast receiver handles the intent, potentially exposing data or performing unintended actions due to the overly permissive filter. * Likelihood: Low-Medium (Depends on the specificity of the intent filters). * Impact: Medium-High (Could lead to data leakage or unintended actions, depending on the targeted component). * Effort: Medium (Requires crafting a malicious intent and having another app installed). * Skill Level: Medium (Requires understanding of Android intents and application components). * Detection Difficulty: Medium (Might be detected through security audits of installed apps or by monitoring intent traffic). * Mitigation: Review all intent filters in AndroidManifest.xml. Use explicit intents whenever possible (targeting a specific component within Sunflower). Use exported="false" for components that do not need to be accessed by other applications. Define specific permissions for accessing sensitive components.

Attack Tree Path: Improper Intent Validation (CRITICAL) [HIGH]

Description: Even with well-defined intent filters, if the receiving component (Activity, Service, BroadcastReceiver) within Sunflower does not properly validate the data contained within the received intent, a malicious application can inject harmful data. This could lead to various issues, including data corruption, unexpected application behavior, or even code execution (though less likely in this specific application). The lack of validation allows the attacker to bypass intended security checks. * Attack Path: 1. A malicious application is installed on the device. 2. The malicious application constructs an intent, potentially matching a legitimate intent filter or exploiting a loosely defined one. 3. The intent contains malicious or unexpected data (e.g., excessively long strings, invalid data types, SQL injection attempts if data is passed to the database without further sanitization). 4. The malicious application sends the intent to Sunflower. 5. Sunflower's component receives the intent but fails to validate the data properly. 6. The malicious data is processed, leading to data corruption, application crashes, or other unintended consequences. * Likelihood: Medium (A very common vulnerability in Android applications). * Impact: Medium-High (Could lead to data corruption, application crashes, or potentially other vulnerabilities). * Effort: Medium (Requires crafting a malicious intent with invalid data). * Skill Level: Medium (Requires understanding of Android intents and data validation techniques). * Detection Difficulty: Medium (Might be detected through input validation logs or by monitoring application behavior; however, subtle data corruption might go unnoticed). * Mitigation: Implement thorough input validation in all activities, services, and broadcast receivers that handle intents. Check for: * Null values. * Unexpected data types. * Out-of-bounds values (e.g., string lengths, numerical ranges). * Unexpected characters or patterns (e.g., SQL injection attempts). * Data consistency with the application's expected state. Use a "fail-fast" approach: reject the intent immediately if any validation check fails.