Objective: To compromise application that use given project by exploiting weaknesses or vulnerabilities within the project itself.
Attack Goal: Compromise Application Using MLX
└───[AND] [CRITICAL NODE] Exploit MLX Vulnerabilities [CRITICAL NODE] ├───[OR] [CRITICAL NODE] [HIGH-RISK PATH] Model Manipulation Attacks [CRITICAL NODE] [HIGH-RISK PATH] │ ├───[AND] [CRITICAL NODE] Malicious Model Loading [CRITICAL NODE] │ │ ├───[OR] [CRITICAL NODE] Unvalidated Model Source [CRITICAL NODE] │ │ │ ├─── [HIGH-RISK PATH] Compromise Model Repository/Storage [HIGH-RISK PATH] │ │ │ └─── [HIGH-RISK PATH] Path Traversal during Model Loading [HIGH-RISK PATH] │ │ └───[OR] [CRITICAL NODE] Model Deserialization Vulnerabilities [CRITICAL NODE] │ │ ├─── [HIGH-RISK PATH] Exploiting Vulnerabilities in Model Format Parsers (e.g., custom formats) [HIGH-RISK PATH] │ │ ├─── [HIGH-RISK PATH] Buffer Overflows/Memory Corruption during Deserialization [HIGH-RISK PATH] ├───[OR] [CRITICAL NODE] [HIGH-RISK PATH] Data Input Manipulation Attacks [CRITICAL NODE] [HIGH-RISK PATH] │ ├───[AND] Adversarial Input Crafting │ │ ├───[OR] [CRITICAL NODE] Evading Input Validation in MLX Processing [CRITICAL NODE] │ │ │ ├─── [HIGH-RISK PATH] Exploiting MLX's Input Handling Weaknesses (e.g., specific data types, edge cases) [HIGH-RISK PATH] │ │ │ ├─── [HIGH-RISK PATH] Bypassing Application-Level Input Sanitization [HIGH-RISK PATH] ├───[OR] [CRITICAL NODE] MLX Library Vulnerabilities [CRITICAL NODE] │ ├───[AND] [HIGH-RISK PATH] Buffer Overflows/Memory Corruption in MLX Core [HIGH-RISK PATH] │ │ ├─── [HIGH-RISK PATH] Exploiting Native Code Vulnerabilities in MLX (C++, Metal Shaders, etc.) [HIGH-RISK PATH] ├───[OR] [CRITICAL NODE] API and Integration Vulnerabilities [CRITICAL NODE] │ ├───[AND] [HIGH-RISK PATH] MLX API Misuse by Application Developers [HIGH-RISK PATH] │ │ ├─── [HIGH-RISK PATH] Incorrect API Usage leading to Security Flaws [HIGH-RISK PATH] │ │ ├─── [HIGH-RISK PATH] Exposing MLX API Functionality Insecurely to External Users (e.g., through web API without proper authorization/authentication) [HIGH-RISK PATH] │ │ ├─── [HIGH-RISK PATH] Lack of Input Validation before passing data to MLX API [HIGH-RISK PATH]
Attack Tree Path: [CRITICAL NODE] Exploit MLX Vulnerabilities
This is the overarching goal and a critical node because it represents directly targeting weaknesses within the MLX framework itself to compromise the application. Success here bypasses application-level security and directly exploits the underlying ML infrastructure.
Attack Tree Path: [CRITICAL NODE] [HIGH-RISK PATH] Model Manipulation Attacks
This path is high-risk and critical because manipulating the ML model can lead to a wide range of attacks, from subtle manipulation of application behavior to complete control. Models are central to ML applications, making them a prime target.
* **[CRITICAL NODE] Malicious Model Loading:**
* Critical as loading a malicious model is a direct way to inject malicious code or logic into the application's ML processing.
* **[CRITICAL NODE] Unvalidated Model Source:**
* Critical because if the application doesn't validate the source of the model, attackers can easily substitute a malicious model.
* **[HIGH-RISK PATH] Compromise Model Repository/Storage:**
* **Attack Vector:** Attacker compromises the storage location (e.g., cloud storage, database, file system) where models are stored. They replace legitimate models with malicious ones.
* **Likelihood:** Medium
* **Impact:** High
* **Effort:** Medium
* **Skill Level:** Medium
* **Detection Difficulty:** Medium
* **[HIGH-RISK PATH] Path Traversal during Model Loading:**
* **Attack Vector:** Attacker exploits path traversal vulnerabilities in the model loading mechanism. They manipulate file paths to load malicious models from unexpected locations, bypassing intended model directories.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low
* **[CRITICAL NODE] Model Deserialization Vulnerabilities:**
* Critical because vulnerabilities in how MLX deserializes model files can lead to code execution or memory corruption.
* **[HIGH-RISK PATH] Exploiting Vulnerabilities in Model Format Parsers (e.g., custom formats):**
* **Attack Vector:** Attacker crafts malicious model files that exploit vulnerabilities (e.g., buffer overflows, format string bugs) in the parsers MLX uses to read model formats, especially if custom or less common formats are used.
* **Likelihood:** Medium
* **Impact:** High
* **Effort:** Medium
* **Skill Level:** Medium
* **Detection Difficulty:** Medium
* **[HIGH-RISK PATH] Buffer Overflows/Memory Corruption during Deserialization:**
* **Attack Vector:** Attacker crafts malicious model files that trigger buffer overflows or memory corruption vulnerabilities during the deserialization process within MLX. This can lead to arbitrary code execution.
* **Likelihood:** Medium
* **Impact:** High
* **Effort:** Medium
* **Skill Level:** Medium
* **Detection Difficulty:** Medium
Attack Tree Path: [CRITICAL NODE] [HIGH-RISK PATH] Data Input Manipulation Attacks
This path is high-risk and critical because manipulating input data is a common and often effective way to attack ML systems. Even with robust models, carefully crafted inputs can cause unexpected and potentially harmful behavior.
* **[CRITICAL NODE] Evading Input Validation in MLX Processing:**
* Critical because if input validation is weak or bypassed when data is processed by MLX, attackers can inject malicious data that MLX processes directly, leading to vulnerabilities.
* **[HIGH-RISK PATH] Exploiting MLX's Input Handling Weaknesses (e.g., specific data types, edge cases):**
* **Attack Vector:** Attacker identifies and exploits weaknesses in how MLX handles specific input data types, edge cases, or malformed data. This could lead to unexpected behavior, errors, or even vulnerabilities within MLX's processing logic.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low
* **[HIGH-RISK PATH] Bypassing Application-Level Input Sanitization:**
* **Attack Vector:** Attacker finds ways to bypass input sanitization or validation implemented at the application level *before* data reaches MLX. This allows malicious data to be processed by MLX, potentially triggering vulnerabilities within MLX or the application's ML logic.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low
Attack Tree Path: [CRITICAL NODE] MLX Library Vulnerabilities
This is a critical node because vulnerabilities within the MLX library itself are fundamental and can affect any application using it. Exploiting these vulnerabilities can have widespread impact.
* **[HIGH-RISK PATH] Buffer Overflows/Memory Corruption in MLX Core:**
* **[HIGH-RISK PATH] Exploiting Native Code Vulnerabilities in MLX (C++, Metal Shaders, etc.):**
* **Attack Vector:** Attacker discovers and exploits buffer overflows, memory corruption bugs, or other vulnerabilities in the native code components of MLX (C++, Metal shaders, etc.). This can lead to arbitrary code execution at the system level.
* **Likelihood:** Low
* **Impact:** Critical
* **Effort:** High
* **Skill Level:** High
* **Detection Difficulty:** High
Attack Tree Path: [CRITICAL NODE] API and Integration Vulnerabilities
This is a critical node because even if MLX itself is secure, improper use or integration of its API by application developers can introduce significant vulnerabilities.
* **[HIGH-RISK PATH] MLX API Misuse by Application Developers:**
* High-risk because developer errors in using the MLX API are common and can easily lead to security flaws.
* **[HIGH-RISK PATH] Incorrect API Usage leading to Security Flaws:**
* **Attack Vector:** Developers use MLX API functions incorrectly, leading to unintended security consequences. This could include improper memory management, insecure data handling, or logic errors that attackers can exploit.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low
* **[HIGH-RISK PATH] Exposing MLX API Functionality Insecurely to External Users (e.g., through web API without proper authorization/authentication):**
* **Attack Vector:** Developers expose MLX API functionality directly through web APIs or other interfaces without proper authentication, authorization, or input validation. This allows attackers to directly interact with MLX components in unintended and potentially harmful ways.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low
* **[HIGH-RISK PATH] Lack of Input Validation before passing data to MLX API:**
* **Attack Vector:** Developers fail to properly validate and sanitize input data *before* passing it to MLX API calls. This allows attackers to inject malicious data that is then processed by MLX, potentially triggering vulnerabilities or causing unexpected behavior.
* **Likelihood:** Medium
* **Impact:** Medium
* **Effort:** Low
* **Skill Level:** Low
* **Detection Difficulty:** Low