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Attack Tree Analysis for nlohmann/json

Objective: Execute Arbitrary Code, Exfiltrate Data, or Cause DoS via nlohmann/json

Attack Tree Visualization

Attacker's Goal: Execute Arbitrary Code, Exfiltrate Data, or Cause DoS via nlohmann/json
├── 1.  Denial of Service (DoS)
│   ├── 1.1  Resource Exhaustion
│   │   ├── 1.1.1  Deeply Nested JSON [CRITICAL]
│   │   │   └── 1.1.1.1  Craft deeply nested JSON input exceeding library/system limits (stack overflow, memory exhaustion).
│   │   ├── 1.1.2  Large JSON Payload [CRITICAL]
│   │   │   └── 1.1.2.1  Send extremely large JSON object/array exceeding memory allocation limits.
│   └── 1.2  Logic Errors
│       ├── 1.2.2  Missing Value Handling [CRITICAL]
│       │   └── 1.2.2.1  Send JSON with missing required fields, leading to null pointer dereferences or unhandled exceptions if the application doesn't validate.
├── 2.  Code Execution (RCE)
│   ├── 2.2  Deserialization of Untrusted Data to Native Objects (If custom "to_json/from_json" are used) [CRITICAL]
│   │   └── 2.2.1  If the application uses custom `to_json` and `from_json` methods for serialization/deserialization of custom C++ objects:
│   │       ├── 2.2.1.1  Craft malicious JSON that, when deserialized, calls unexpected constructors or methods with attacker-controlled data.
│   │       ├── 2.2.1.2  Exploit vulnerabilities in the custom `from_json` implementation (e.g., buffer overflows, format string bugs).
│   │       └── 2.2.1.3  Trigger object instantiation with side effects that compromise the system (e.g., opening files, executing commands).
└── 3.  Data Exfiltration
    └── 3.3  Exploiting Logic Flaws After Successful Parsing [CRITICAL]
        └── 3.3.1  If the application uses parsed JSON data in database queries or other sensitive operations without proper sanitization:
            └── 3.3.1.1  Inject malicious data via JSON to perform SQL injection, command injection, or other attacks. (This is *application logic*, but triggered by JSON input).

Attack Tree Path: 1.1.1 Deeply Nested JSON (DoS - Resource Exhaustion)

  • Description: The attacker sends a JSON payload with an extremely deep nesting structure (e.g., many nested objects or arrays). This can overwhelm the parser, leading to a stack overflow or excessive memory consumption, causing the application or server to crash.
  • Likelihood: High - Easy to craft such a payload.
  • Impact: High - Can lead to complete denial of service.
  • Effort: Low - Requires minimal effort to create the malicious JSON.
  • Skill Level: Novice - No specialized knowledge is needed.
  • Detection Difficulty: Medium - Can be detected through monitoring for unusual resource usage (CPU, memory) or by analyzing crash dumps.

Attack Tree Path: 1.1.2 Large JSON Payload (DoS - Resource Exhaustion)

  • Description: The attacker sends a very large JSON payload (e.g., a huge array or object with massive strings). This can exhaust the server's memory, leading to a denial-of-service condition.
  • Likelihood: High - Easy to generate a large JSON payload.
  • Impact: High - Can lead to complete denial of service.
  • Effort: Low - Requires minimal effort.
  • Skill Level: Novice - No specialized knowledge is needed.
  • Detection Difficulty: Medium - Can be detected through monitoring network traffic and memory usage.

Attack Tree Path: 1.2.2 Missing Value Handling (DoS - Logic Errors)

  • Description: The attacker sends JSON that omits required fields. If the application doesn't properly validate the presence of these fields before accessing them, it can lead to null pointer dereferences, unhandled exceptions, or other undefined behavior, potentially crashing the application.
  • Likelihood: High - Very common vulnerability if input validation is lacking.
  • Impact: High - Can cause application crashes and denial of service.
  • Effort: Low - Trivial to create JSON with missing fields.
  • Skill Level: Novice - Basic understanding of JSON structure is sufficient.
  • Detection Difficulty: Easy - Application logs will typically show errors related to null pointers or missing data.

Attack Tree Path: 2.2 Deserialization of Untrusted Data to Native Objects (RCE)

  • Description: This is the most dangerous scenario. If the application uses nlohmann/json's to_json and from_json functionality to serialize and deserialize custom C++ objects, and it does so with untrusted JSON input, an attacker can potentially achieve remote code execution. The attacker crafts malicious JSON that, when deserialized, triggers unintended behavior in the object's constructors, destructors, or other methods. This could involve:
    • 2.2.1.1: Calling unexpected methods with attacker-controlled arguments.
    • 2.2.1.2: Exploiting vulnerabilities (like buffer overflows) within the custom from_json implementation.
    • 2.2.1.3: Creating objects that have dangerous side effects upon instantiation.
  • Likelihood: Medium - Requires the application to use custom serialization/deserialization and to be vulnerable in its implementation.
  • Impact: Very High - Can lead to complete system compromise.
  • Effort: High - Requires significant understanding of the application's code and the from_json implementations.
  • Skill Level: Advanced - Requires expertise in C++ and secure coding practices.
  • Detection Difficulty: Hard - Requires thorough code review, static analysis, and potentially dynamic analysis (e.g., fuzzing) of the deserialization logic.

Attack Tree Path: 3.3 Exploiting Logic Flaws After Successful Parsing (Data Exfiltration)

  • Description: Even if the JSON is parsed correctly, the application might still be vulnerable if it uses the parsed data insecurely. This is not a vulnerability in nlohmann/json itself, but rather in how the application uses the data. The most common example is SQL injection: if the application takes values from the JSON and inserts them directly into SQL queries without proper sanitization or parameterization, an attacker can inject malicious SQL code. Similar issues can arise with command injection, path traversal, etc.
  • Likelihood: High - Very common vulnerability if developers don't treat all user input as untrusted.
  • Impact: Very High - Can lead to data breaches, data modification, or even complete system compromise.
  • Effort: Low to Medium - Depends on the specific vulnerability and how the application uses the data.
  • Skill Level: Intermediate to Advanced - Requires understanding of injection vulnerabilities and how to exploit them.
  • Detection Difficulty: Medium - Can be detected through security testing (e.g., penetration testing, code review) and by monitoring database queries for suspicious patterns.