attack-tree.md

Attack Tree Analysis for facebook/rocksdb

Objective: Compromise Application using RocksDB vulnerabilities (High-Risk Paths and Critical Nodes only).

Attack Tree Visualization

Compromise Application via RocksDB [CRITICAL NODE]
├── Exploit RocksDB Vulnerabilities [CRITICAL NODE]
│   ├── Code Bugs in RocksDB [CRITICAL NODE]
│   │   ├── Buffer Overflow/Underflow [HIGH-RISK PATH]
│   │   ├── Integer Overflow/Underflow [HIGH-RISK PATH]
│   │   ├── Use-After-Free/Double-Free [HIGH-RISK PATH]
│   ├── Race Conditions and Concurrency Issues [HIGH-RISK PATH] [CRITICAL NODE]
│   │   ├── Data Corruption due to Race Conditions [HIGH-RISK PATH]
│   │   ├── Denial of Service due to Deadlocks/Livelocks [HIGH-RISK PATH]
│   ├── Vulnerabilities in Dependencies of RocksDB [HIGH-RISK PATH] [CRITICAL NODE]
│   │   ├── Exploiting vulnerabilities in Snappy, Zstd, or other compression libraries [HIGH-RISK PATH]
├── Exploit Application's Misuse of RocksDB API [HIGH-RISK PATH] [CRITICAL NODE]
│   ├── Input Validation Issues leading to RocksDB Exploits [HIGH-RISK PATH] [CRITICAL NODE]
│   │   ├── Injection Attacks via Key/Value Input [HIGH-RISK PATH]
│   │   │   ├── Key Injection [HIGH-RISK PATH]
│   │   │   ├── Value Injection [HIGH-RISK PATH]
│   │   ├── Path Traversal via Filename Options [HIGH-RISK PATH]
│   │   ├── Resource Exhaustion via Input [HIGH-RISK PATH]
│   │   │   ├── Large Key/Value Sizes [HIGH-RISK PATH]
│   │   │   ├── High Write Volume [HIGH-RISK PATH]
│   │   │   ├── Unbounded Iteration/Read Requests [HIGH-RISK PATH]
│   ├── API Misuse leading to Unexpected Behavior [HIGH-RISK PATH]
│   │   ├── Incorrect API Parameter Usage [HIGH-RISK PATH]
│   │   ├── Improper Error Handling [HIGH-RISK PATH]
│   │   ├── Lack of Resource Management [HIGH-RISK PATH]
│   │   ├── Insecure Data Handling Post-RocksDB Retrieval [HIGH-RISK PATH]
├── Denial of Service Attacks against RocksDB [HIGH-RISK PATH] [CRITICAL NODE]
│   ├── Resource Exhaustion [HIGH-RISK PATH]
│   │   ├── Memory Exhaustion [HIGH-RISK PATH]
│   │   ├── Disk Space Exhaustion [HIGH-RISK PATH]
│   │   ├── IOPS Exhaustion [HIGH-RISK PATH]
│   │   ├── CPU Exhaustion [HIGH-RISK PATH]
│   ├── Crash RocksDB Process [HIGH-RISK PATH]
│   │   ├── Triggering Known Bugs leading to Crashes [HIGH-RISK PATH]
└── Information Disclosure via RocksDB [HIGH-RISK PATH] [CRITICAL NODE]
    ├── Direct File Access [HIGH-RISK PATH]
    ├── Error Messages and Logging [HIGH-RISK PATH]
    ├── Data Exfiltration via Backup/Export Features [HIGH-RISK PATH]

Attack Tree Path: 1. Exploit RocksDB Vulnerabilities [CRITICAL NODE]:

• Code Bugs in RocksDB [CRITICAL NODE]:
  • Buffer Overflow/Underflow [HIGH-RISK PATH]:
    • Attack Vector: Attacker crafts malicious input (keys or values) that, when processed by RocksDB's C++ code, exceeds the allocated buffer size. This can overwrite adjacent memory regions.
    • Exploitation: By carefully controlling the overflow, an attacker might overwrite critical data structures, function pointers, or even inject malicious code to gain control of the application process.
  • Integer Overflow/Underflow [HIGH-RISK PATH]:
    • Attack Vector: Attacker provides input that causes integer calculations within RocksDB (e.g., size calculations, offset calculations) to overflow or underflow.
    • Exploitation: This can lead to incorrect memory allocation sizes, buffer boundaries, or loop conditions, resulting in memory corruption, unexpected behavior, or exploitable conditions like buffer overflows.
  • Use-After-Free/Double-Free [HIGH-RISK PATH]:
    • Attack Vector: Exploiting race conditions or specific sequences of API calls in a multi-threaded environment to trigger a use-after-free or double-free vulnerability. This occurs when memory is accessed after it has been freed or freed multiple times.
    • Exploitation: Memory corruption vulnerabilities like use-after-free can be leveraged to gain arbitrary code execution. Attackers can manipulate freed memory to point to attacker-controlled data, which is then executed when the program attempts to use the freed memory.
• Race Conditions and Concurrency Issues [CRITICAL NODE]:
  • Data Corruption due to Race Conditions [HIGH-RISK PATH]:
    • Attack Vector: Exploiting the concurrent nature of RocksDB operations (writes, reads, compaction) to introduce race conditions. This happens when the outcome of operations depends on the unpredictable order of events in concurrent execution.
    • Exploitation: Race conditions can lead to data inconsistencies, where data is written or read in an incorrect order, corrupting the database's integrity. This corruption can lead to application malfunction or exploitable states if the application relies on data integrity.
  • Denial of Service due to Deadlocks/Livelocks [HIGH-RISK PATH]:
    • Attack Vector: Crafting specific sequences of operations that trigger deadlocks or livelocks within RocksDB's internal locking mechanisms. Deadlocks occur when two or more operations are blocked indefinitely, waiting for each other. Livelocks occur when operations repeatedly yield to each other, preventing progress.
    • Exploitation: Deadlocks and livelocks can cause the RocksDB instance to become unresponsive, leading to application unavailability and denial of service.
• Vulnerabilities in Dependencies of RocksDB [CRITICAL NODE]:
  • Exploiting vulnerabilities in Snappy, Zstd, or other compression libraries [HIGH-RISK PATH]:
    • Attack Vector: Targeting known or zero-day vulnerabilities in compression libraries (like Snappy or Zstd) that RocksDB uses for data compression.
    • Exploitation: Vulnerabilities in these libraries can lead to memory corruption, code execution, or denial of service when RocksDB processes compressed data. If a vulnerability allows for code execution, the attacker can gain control of the application process.

Attack Tree Path: 2. Exploit Application's Misuse of RocksDB API [CRITICAL NODE]:

• Input Validation Issues leading to RocksDB Exploits [CRITICAL NODE]:
  • Injection Attacks via Key/Value Input [HIGH-RISK PATH]:
    • Key Injection [HIGH-RISK PATH]:
      • Attack Vector: If the application doesn't properly sanitize or validate user-provided input that becomes part of RocksDB keys, attackers can craft keys to manipulate data access or storage in unintended ways.
      • Exploitation: Attackers might be able to overwrite or access data associated with different keys than intended, potentially leading to data manipulation, privilege escalation, or information disclosure within the application's data model.
    • Value Injection [HIGH-RISK PATH]:
      • Attack Vector: If the application doesn't properly sanitize or validate user-provided input that becomes RocksDB values, and if these values are later interpreted or processed in a vulnerable manner by the application.
      • Exploitation: If the application later deserializes or interprets values as code (e.g., SQL, scripts), value injection can lead to code execution vulnerabilities within the application's context.
  • Path Traversal via Filename Options [HIGH-RISK PATH]:
    • Attack Vector: If the application allows user-controlled input to influence RocksDB configuration options, particularly file paths (e.g., for WAL directory, SSTable directory, backup paths).
    • Exploitation: Attackers can use path traversal techniques (e.g., ../../) to manipulate these file paths to point outside the intended RocksDB storage area. This could allow them to access, modify, or delete arbitrary files on the server, leading to data breaches or system compromise.
  • Resource Exhaustion via Input [HIGH-RISK PATH]:
    • Large Key/Value Sizes [HIGH-RISK PATH]:
      • Attack Vector: Sending excessively large keys or values to the application, which are then passed to RocksDB for storage.
      • Exploitation: This can overwhelm RocksDB's memory or disk resources, leading to memory exhaustion, disk space exhaustion, and ultimately denial of service.
    • High Write Volume [HIGH-RISK PATH]:
      • Attack Vector: Flooding the application with a high volume of write requests that are then processed by RocksDB.
      • Exploitation: This can exhaust disk IOPS, disk space, and CPU resources, causing performance degradation or complete denial of service.
    • Unbounded Iteration/Read Requests [HIGH-RISK PATH]:
      • Attack Vector: Crafting read requests that cause RocksDB to perform unbounded iterations or scans over large portions of the database.
      • Exploitation: Unbounded reads can consume excessive CPU, memory, and IO resources, leading to performance degradation or denial of service.
• API Misuse leading to Unexpected Behavior [HIGH-RISK PATH]:
  • Incorrect API Parameter Usage [HIGH-RISK PATH]:
    • Attack Vector: Application developers using RocksDB APIs incorrectly, such as providing wrong data types, incorrect options, or misunderstanding API semantics.
    • Exploitation: Incorrect API usage can lead to unexpected behavior in RocksDB, data corruption, crashes, or exploitable states that attackers can leverage.
  • Improper Error Handling [HIGH-RISK PATH]:
    • Attack Vector: Insufficient or incorrect error handling in the application's code that interacts with RocksDB.
    • Exploitation: If errors from RocksDB operations are not properly handled, they can propagate through the application, leading to unexpected states, information disclosure (e.g., exposing internal error messages), or exploitable conditions.
  • Lack of Resource Management [HIGH-RISK PATH]:
    • Attack Vector: Application code failing to properly manage RocksDB resources, such as not closing iterators, not releasing handles, or leaking memory associated with RocksDB objects.
    • Exploitation: Resource leaks can accumulate over time, leading to memory exhaustion, file descriptor exhaustion, and ultimately denial of service.
  • Insecure Data Handling Post-RocksDB Retrieval [HIGH-RISK PATH]:
    • Attack Vector: Vulnerabilities in how the application processes data after retrieving it from RocksDB.
    • Exploitation: If the application performs insecure deserialization on data read from RocksDB, or if it has other vulnerabilities in its data processing logic, attackers can exploit these vulnerabilities after the data is retrieved from the database. This can lead to code execution, data manipulation, or other application-specific compromises.

Attack Tree Path: 3. Denial of Service Attacks against RocksDB [CRITICAL NODE]:

• Resource Exhaustion [HIGH-RISK PATH]: (Detailed in Input Validation and API Misuse - Large Key/Value Sizes, High Write Volume, Unbounded Iteration/Read Requests)
  • Memory Exhaustion [HIGH-RISK PATH]:
    • Attack Vector: Forcing RocksDB to allocate excessive memory.
    • Exploitation: Leads to Out-Of-Memory (OOM) errors, causing RocksDB and the application to crash or become unresponsive.
  • Disk Space Exhaustion [HIGH-RISK PATH]:
    • Attack Vector: Filling up the disk space used by RocksDB.
    • Exploitation: Prevents further writes to RocksDB, potentially causing application errors or crashes, and leading to denial of service.
  • IOPS Exhaustion [HIGH-RISK PATH]:
    • Attack Vector: Overwhelming RocksDB with a high volume of IO requests.
    • Exploitation: Slows down RocksDB performance significantly, leading to application timeouts, unresponsiveness, and denial of service.
  • CPU Exhaustion [HIGH-RISK PATH]:
    • Attack Vector: Triggering CPU-intensive operations within RocksDB, such as compaction or complex queries.
    • Exploitation: Consumes excessive CPU resources, degrading application performance and potentially leading to denial of service.
• Crash RocksDB Process [HIGH-RISK PATH]:
  • Triggering Known Bugs leading to Crashes [HIGH-RISK PATH]:
    • Attack Vector: Exploiting publicly known bugs in specific versions of RocksDB that are known to cause crashes when triggered by certain inputs or operations.
    • Exploitation: Causes the RocksDB process to terminate unexpectedly, leading to application unavailability and denial of service.

Attack Tree Path: 4. Information Disclosure via RocksDB [CRITICAL NODE]:

• Direct File Access [HIGH-RISK PATH]:
  • Attack Vector: If file system permissions for RocksDB data directories (SSTables, WAL, etc.) are misconfigured and overly permissive.
  • Exploitation: Attackers can directly access and read RocksDB data files from the file system. SSTables and WAL files contain the raw data stored in RocksDB, allowing attackers to extract sensitive information.
• Error Messages and Logging [HIGH-RISK PATH]:
  • Attack Vector: Overly verbose error messages or logging configurations that expose sensitive information.
  • Exploitation: Error messages or logs might inadvertently leak sensitive data stored in RocksDB, internal system paths, configuration details, or other information that can be valuable to an attacker for further attacks or direct information disclosure.
• Data Exfiltration via Backup/Export Features [HIGH-RISK PATH]:
  • Attack Vector: If the application exposes RocksDB's backup or export features (if any are implemented) without proper authorization or security controls.
  • Exploitation: Attackers can abuse these features to create backups or export data from RocksDB and exfiltrate it, leading to a data breach.