Overview
This report focuses on CVE-2025-55559, a high-severity vulnerability discovered in TensorFlow v2.18.0. This vulnerability, if exploited, can lead to a Denial of Service (DoS) attack, potentially compromising systems or leading to data leakage. It affects all systems utilizing TensorFlow v2.18.0, highlighting the urgent need for mitigation and patching.
Vulnerability Summary
CVE ID: CVE-2025-55559
Severity: High (7.5 CVSS Score)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Potential system compromise or data leakage
Affected Products
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Product | Affected Versions
TensorFlow | v2.18.0
How the Exploit Works
The vulnerability is triggered when padding is set to ‘valid’ in tf.keras.layers.Conv2D within TensorFlow v2.18.0. This incorrect configuration can lead to a buffer overflow condition, causing the system to become unresponsive, leading to a Denial of Service (DoS) situation. Attackers can exploit this vulnerability remotely over a network connection, without requiring any user interaction.
Conceptual Example Code
The following pseudocode outlines a potential exploitation scenario:
import tensorflow as tf
# Create a maliciously configured Conv2D layer
layer = tf.keras.layers.Conv2D(64, (3, 3), padding='valid')
# Prepare a large input tensor
input = tf.random.uniform((1, 3000, 3000, 3))
# Apply the malicious layer
output = layer(input)In this example, the attacker creates a Conv2D layer with ‘valid’ padding and applies this to a large input tensor. This can cause the system to overflow, leading to the Denial of Service (DoS) condition.