attack-tree.md

Attack Tree Analysis for xianyi/openblas

Objective: Compromise Application Using OpenBLAS to Gain Unauthorized Access and Control of Application/Data.

Attack Tree Visualization

Compromise Application via OpenBLAS [CRITICAL NODE]
├───[1.0] Exploit Vulnerabilities in OpenBLAS Code [CRITICAL NODE, HIGH RISK PATH]
│   ├───[1.1] Memory Corruption Vulnerabilities [CRITICAL NODE, HIGH RISK PATH]
│   │   ├───[1.1.1] Buffer Overflow [HIGH RISK PATH]
│   │   │   ├───[1.1.1.1] Input Data Overflow [HIGH RISK PATH]
│   │   │   │   └───[1.1.1.1.a] Provide overly large input matrices/vectors exceeding buffer limits in OpenBLAS functions (e.g., `sgemv`, `dgemm`). [HIGH RISK PATH, CRITICAL NODE]
│   │   │   └───[1.1.1.2] Integer Overflow leading to Buffer Overflow [HIGH RISK PATH]
│   │   │       └───[1.1.1.2.a] Manipulate input dimensions to cause integer overflow in size calculations, leading to undersized buffer allocation and subsequent overflow. [HIGH RISK PATH, CRITICAL NODE]
│   ├───[1.2] Input Validation Vulnerabilities [CRITICAL NODE, HIGH RISK PATH]
│   │   ├───[1.2.1] Lack of Input Sanitization [HIGH RISK PATH]
│   │   │   └───[1.2.1.a] Application passes unsanitized/unvalidated user-controlled data directly to OpenBLAS functions, allowing malicious input to trigger vulnerabilities. [HIGH RISK PATH, CRITICAL NODE]
├───[2.0] Supply Chain Compromise [CRITICAL NODE, CRITICAL RISK PATH]
│   ├───[2.1] Compromised OpenBLAS Distribution [CRITICAL RISK PATH]
│   │   ├───[2.1.1] Maliciously Modified OpenBLAS Binary [CRITICAL RISK PATH, CRITICAL NODE]
│   │   │   └───[2.1.1.a] Attacker replaces legitimate OpenBLAS binary in distribution channels (e.g., package repositories, download mirrors) with a backdoored version. [CRITICAL RISK PATH, CRITICAL NODE]

Attack Tree Path: 1.0 Exploit Vulnerabilities in OpenBLAS Code [CRITICAL NODE, HIGH RISK PATH]:

• This is the overarching category of attacks that directly target weaknesses within the OpenBLAS library itself. Success here can lead to significant compromise of the application.

Attack Tree Path: 1.1 Memory Corruption Vulnerabilities [CRITICAL NODE, HIGH RISK PATH]:

• Memory corruption vulnerabilities are a primary concern in C and Assembly code like OpenBLAS. They can allow attackers to overwrite critical data or inject malicious code.

  • 1.1.1 Buffer Overflow [HIGH RISK PATH]:

    • Buffer overflows occur when data written to a memory buffer exceeds its allocated size, corrupting adjacent memory. This is a classic and often exploitable vulnerability.

      • 1.1.1.1 Input Data Overflow [HIGH RISK PATH]:
        • This specific type of buffer overflow is triggered by providing overly large input data to OpenBLAS functions.

          • 1.1.1.1.a Provide overly large input matrices/vectors exceeding buffer limits in OpenBLAS functions (e.g., sgemv, dgemm). [HIGH RISK PATH, CRITICAL NODE]:

            • Attack Vector: An attacker crafts malicious input matrices or vectors with dimensions or data sizes exceeding the expected buffer limits within OpenBLAS functions like sgemv (matrix-vector multiplication) or dgemm (matrix-matrix multiplication).
            • Exploitation: If OpenBLAS lacks sufficient bounds checking or input validation, the oversized input can cause a buffer overflow when processed by these functions. This overflow can overwrite adjacent memory regions, potentially allowing the attacker to:
              • Overwrite return addresses on the stack, leading to control-flow hijacking and Remote Code Execution (RCE).
              • Overwrite function pointers or other critical data structures in memory, leading to arbitrary code execution or application crashes.
            • Impact: Remote Code Execution (RCE), full application compromise.

          • 1.1.1.2 Integer Overflow leading to Buffer Overflow [HIGH RISK PATH]:

            • This is a more subtle form of buffer overflow where an integer overflow in size calculations leads to an undersized buffer allocation.
              • 1.1.1.2.a Manipulate input dimensions to cause integer overflow in size calculations, leading to undersized buffer allocation and subsequent overflow. [HIGH RISK PATH, CRITICAL NODE]:
                • Attack Vector: An attacker manipulates the input dimensions (e.g., number of rows, columns) of matrices or vectors in a way that causes an integer overflow during size calculations within OpenBLAS. For example, multiplying very large dimensions might wrap around to a small value due to integer overflow.
                • Exploitation: If OpenBLAS uses these overflowed, small size values to allocate memory buffers, it will allocate a buffer that is too small for the intended data. When the subsequent operations attempt to write the expected amount of data into this undersized buffer, a buffer overflow occurs.
                • Impact: Remote Code Execution (RCE), full application compromise, similar to direct input data overflow.

Attack Tree Path: 1.2 Input Validation Vulnerabilities [CRITICAL NODE, HIGH RISK PATH]:

• These vulnerabilities arise from the application's failure to properly validate user-provided input before passing it to OpenBLAS. This makes the application vulnerable to attacks targeting OpenBLAS weaknesses.

  • 1.2.1 Lack of Input Sanitization [HIGH RISK PATH]:
    • This is a common application security flaw where user-controlled data is directly used without proper validation or sanitization. * 1.2.1.a Application passes unsanitized/unvalidated user-controlled data directly to OpenBLAS functions, allowing malicious input to trigger vulnerabilities. [HIGH RISK PATH, CRITICAL NODE]: * Attack Vector: The application directly takes user-provided input (e.g., matrix dimensions, matrix elements, function parameters) and passes it to OpenBLAS functions without any validation or sanitization. * Exploitation: If the application fails to validate input, an attacker can inject malicious input designed to trigger vulnerabilities in OpenBLAS, such as buffer overflows (as described in 1.1.1.1 and 1.1.1.2), or other exploitable conditions. This essentially makes the application a conduit for attacks against OpenBLAS. * Impact: High, as it can enable exploitation of any underlying vulnerability in OpenBLAS that can be triggered by malicious input, potentially leading to Remote Code Execution (RCE) and full application compromise.

Attack Tree Path: 2.0 Supply Chain Compromise [CRITICAL NODE, CRITICAL RISK PATH]:

• Supply chain attacks target the software development and distribution process. Compromising the supply chain for OpenBLAS can have a widespread and devastating impact.

  • 2.1 Compromised OpenBLAS Distribution [CRITICAL RISK PATH]:

    • This attack vector focuses on compromising the channels through which OpenBLAS is distributed to users.

      • 2.1.1 Maliciously Modified OpenBLAS Binary [CRITICAL RISK PATH, CRITICAL NODE]:
        • This is a direct and highly impactful supply chain attack where the actual binary files of OpenBLAS are replaced with malicious versions.
          • 2.1.1.a Attacker replaces legitimate OpenBLAS binary in distribution channels (e.g., package repositories, download mirrors) with a backdoored version. [CRITICAL RISK PATH, CRITICAL NODE]:
            • Attack Vector: An attacker compromises distribution channels for OpenBLAS. This could involve:
              • Compromising package repositories (e.g., APT, YUM, PyPI, NPM mirrors).
              • Compromising download mirrors for OpenBLAS.
              • Setting up fake or malicious websites that appear to distribute OpenBLAS.
            • Exploitation: The attacker replaces the legitimate OpenBLAS binary files in these distribution channels with backdoored versions. These backdoored binaries contain malicious code injected by the attacker. When users download and install OpenBLAS from these compromised channels, they unknowingly install the malicious version.
            • Impact: Critical. A compromised OpenBLAS binary can grant the attacker complete control over any system that uses it. This can lead to:
              • Remote Code Execution (RCE) on all affected systems.
              • Data theft and espionage.
              • System disruption and denial of service.
              • Installation of backdoors for persistent access.