VAITP Dataset

← Back to the dataset

CVE-2022-29216

TensorFlow saved_model_cli code injection

  • CVSS 7.8
  • CWE-94 Improper Control of Generation of Code ('Code Injection')
  • Input Validation and Sanitization
  • Remote

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

CVSS base score
7.8
Published
2022-05-21
OWASP
A03 Injection
Orthogonal defect classification
Function
Code defect classification
Incorrect Functionality
Category
Input Validation and Sanitization
Subcategory
Insecure Parsing or Deserialization
Accessibility scope
Remote
Impact
Arbitrary Code Execution
Affected component
TensorFlow
Fixed by upgrading
Yes

Solution

Update TensorFlow to version 2.9.0, 2.8.1, 2.7.2, or 2.6.4.

Vulnerable code sample

import tensorflow as tf

def load_model(model_path):
    model = tf.saved_model.load(model_path)
    return model

model_path = "path/to/saved_model"
model = load_model(model_path)

Patched code sample

import tensorflow as tf
import os

def load_model(model_path):
    allowed_dir = "/models/"
    
    if not model_path.startswith(allowed_dir):
        raise ValueError("Untrusted model path detected!")

    if not os.path.isdir(model_path):
        raise ValueError("Invalid model directory!")

    model = tf.saved_model.load(model_path)
    return model

model_path = "path/to/saved_model"
model = load_model(model_path)

Cite this entry

@misc{vaitp:cve202229216,
  title        = {{TensorFlow saved_model_cli code injection}},
  author       = {Bogaerts, Fr\'ed\'eric and Ivaki, Naghmeh and Fonseca, Jos\'e},
  year         = {2022},
  note         = {VAITP Python Vulnerability Dataset, entry CVE-2022-29216},
  howpublished = {\url{https://netpack.pt/vaitp/vulnerability/CVE-2022-29216/}}
}
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.

The supreme art of war is to subdue the enemy without fighting.

Sun Tzu – “The Art of War”

:: Shaping the future through research and ingenuity ::