{"id":87041,"date":"2026-06-04T15:18:34","date_gmt":"2026-06-04T15:18:34","guid":{"rendered":""},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-30T00:00:00","slug":"cve-2025-55559-tensorflow-v2-18-0-vulnerability-leads-to-denial-of-service-attacks","status":"publish","type":"post","link":"https:\/\/www.ameeba.com\/blog\/cve-2025-55559-tensorflow-v2-18-0-vulnerability-leads-to-denial-of-service-attacks\/","title":{"rendered":"CVE-2025-55559: TensorFlow v2.18.0 Vulnerability Leads to Denial of Service Attacks<\/strong>"},"content":{"rendered":"

Overview<\/strong><\/p>\n

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.<\/p>\n

Vulnerability Summary<\/strong><\/p>\n

CVE ID: CVE-2025-55559
\nSeverity: High (7.5 CVSS Score)
\nAttack Vector: Network
\nPrivileges Required: None
\nUser Interaction: None
\nImpact: Potential system compromise or data leakage<\/p>\n

Affected Products<\/strong><\/p>\n

Product | Affected Versions<\/p>\n

TensorFlow | v2.18.0<\/p>\n

How the Exploit Works<\/strong><\/p>\n

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.<\/p>\n

Conceptual Example Code<\/strong><\/p>\n

The following pseudocode outlines a potential exploitation scenario:<\/p>\n

import tensorflow as tf\n# Create a maliciously configured Conv2D layer\nlayer = tf.keras.layers.Conv2D(64, (3, 3), padding='valid')\n# Prepare a large input tensor\ninput = tf.random.uniform((1, 3000, 3000, 3))\n# Apply the malicious layer\noutput = layer(input)<\/code><\/pre>\n
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.<\/p>\n","protected":false},"excerpt":{"rendered":"
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: […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[],"tags":[],"vendor":[],"product":[],"attack_vector":[],"asset_type":[],"severity":[],"exploit_status":[],"class_list":["post-87041","post","type-post","status-publish","format-standard","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t