{"id":86270,"date":"2026-01-12T23:30:01","date_gmt":"2026-01-12T23:30:01","guid":{"rendered":""},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-30T06:00:00","slug":"cve-2025-30202-vllm-denial-of-service-and-data-exposure-vulnerability","status":"publish","type":"post","link":"https:\/\/www.ameeba.com\/blog\/cve-2025-30202-vllm-denial-of-service-and-data-exposure-vulnerability\/","title":{"rendered":"<strong>CVE-2025-30202: vLLM Denial of Service and Data Exposure Vulnerability<\/strong>"},"content":{"rendered":"<p><strong>Overview<\/strong><\/p>\n<p>CVE-2025-30202 is a critical vulnerability affecting vLLM, a high-throughput and memory-efficient inference and serving engine. It exposes the system to potential denial of service (DoS) attacks and data leakage via ZeroMQ in multi-node vLLM deployment. This vulnerability poses a significant threat to all entities utilizing vLLM versions from 0.5.2 and prior to 0.8.5. It is noteworthy due to its potential to compromise system integrity and confidentiality.<\/p>\n<p><strong>Vulnerability Summary<\/strong><\/p>\n<p>CVE ID: CVE-2025-30202<br \/>\nSeverity: High (7.5)<br \/>\nAttack Vector: Network<br \/>\nPrivileges Required: None<br \/>\nUser Interaction: None<br \/>\nImpact: Potential system compromise and data leakage<\/p>\n<p><strong>Affected Products<\/strong><\/p><div id=\"ameeb-1197495352\" class=\"ameeb-content-2 ameeb-entity-placement\"><div style=\"border-left: 4px solid #555; padding-left: 20px; margin: 48px 0; font-family: Roboto, sans-serif; color: #ffffff; line-height: 1.6; max-width: 720px;\">\r\n  <h2 style=\"margin-top: 0; font-size: 22px; font-weight: 600; display: flex; align-items: center; letter-spacing: -0.02em;\">\r\n    <a href=\"https:\/\/www.ameeba.com\/chat\" style=\"display: inline-flex; align-items: center; margin-right: 10px;\">\r\n      <img decoding=\"async\" src=\"https:\/\/www.ameeba.com\/blog\/wp-content\/uploads\/2025\/10\/Best-App-icon-Ameeba.png\" alt=\"Ameeba Chat Icon\" style=\"width: 42px; height: 42px;\" \/>\r\n    <\/a>\r\n    Share secrets securely\r\n  <\/h2>\r\n\r\n  <p style=\"margin-bottom: 14px; color: #d1d5db;\">\r\n    Ameeba is private infrastructure for communication and sensitive work built on encrypted identity instead of exposed corporate identity systems.\r\n  <\/p>\r\n\r\n  <p style=\"margin-bottom: 18px; color: #a1a1aa;\">\r\n    Passwords, credentials, confidential files, screenshots, internal discussions, sensitive AI context, and private coordination should not become exposed across ordinary communication platforms.\r\n  <\/p>\r\n\r\n  <ul style=\"list-style: none; padding-left: 0; margin-bottom: 24px; color: #e4e4e7;\">\r\n    <li style=\"margin-bottom: 8px;\">\u2022 Encrypted identity<\/li>\r\n    <li style=\"margin-bottom: 8px;\">\u2022 Private Spaces for organizations and teams<\/li>\r\n    <li style=\"margin-bottom: 8px;\">\u2022 End-to-end encrypted chat, calls, files, and notes<\/li>\r\n    <li style=\"margin-bottom: 8px;\">\u2022 Sensitive AI work and protected collaboration<\/li>\r\n    <li>\u2022 Built for information that cannot leak<\/li>\r\n  <\/ul>\r\n\r\n  <p style=\"font-style: italic; font-weight: 600; margin-bottom: 24px; color: #ffffff;\">\r\n    Our mission is to secure human work alongside AI.\r\n  <\/p>\r\n\r\n  <div style=\"display: flex; flex-wrap: wrap; gap: 12px;\">\r\n    <a href=\"https:\/\/www.ameeba.com\/chat\/download\" style=\"background-color: #ffffff; color: #000000; padding: 10px 20px; text-decoration: none; border-radius: 8px; font-weight: 500;\">\r\n      Download Ameeba\r\n    <\/a>\r\n\r\n    <a href=\"https:\/\/www.ameeba.com\/chat\" style=\"border: 1px solid #ffffff; color: #ffffff; padding: 10px 20px; text-decoration: none; border-radius: 8px; font-weight: 500;\">\r\n      Learn More\r\n    <\/a>\r\n  <\/div>\r\n<\/div><\/div>\n<p>Product | Affected Versions<\/p>\n<p>vLLM | 0.5.2 to 0.8.4<\/p>\n<p><strong>How the Exploit Works<\/strong><\/p>\n<p>In a multi-node vLLM deployment, vLLM makes use of ZeroMQ for certain multi-node communication functions. The primary vLLM host opens an XPUB ZeroMQ socket and binds it to all interfaces. While the socket is typically opened for a multi-node deployment, it is only utilized when conducting tensor parallelism across multiple hosts.<br \/>\nAny client with network access to this host can connect to this XPUB socket unless its port is blocked by a firewall. Once connected, these arbitrary clients will receive all of the same data broadcasted to all of the secondary vLLM hosts. This data is internal vLLM state information that is not useful to an attacker. However, by potentially connecting to this socket many times and not reading the data published to them, an attacker can cause a DoS attack by slowing down or potentially blocking the publisher.<\/p>\n<p><strong>Conceptual Example Code<\/strong><\/p><div id=\"ameeb-1783396544\" class=\"ameeb-content ameeb-entity-placement\"><div class=\"poptin-embedded\" data-id=\"f6b387694f681\"><\/div>\r\n\r\n\r\n\r\n\r\n\r\n<\/div>\n<p>The following conceptual code represents how an attacker might continuously connect to the XPUB socket without reading the data, leading to potential DoS:<\/p>\n<pre><code class=\"\" data-line=\"\">import zmq\ncontext = zmq.Context()\nsocket = context.socket(zmq.SUB)\nsocket.connect(&quot;tcp:\/\/target_host:target_port&quot;)\nwhile True:\n# Continuously connect without reading the data\nsocket.recv_string(flags=zmq.NOBLOCK)<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>Overview CVE-2025-30202 is a critical vulnerability affecting vLLM, a high-throughput and memory-efficient inference and serving engine. It exposes the system to potential denial of service (DoS) attacks and data leakage via ZeroMQ in multi-node vLLM deployment. This vulnerability poses a significant threat to all entities utilizing vLLM versions from 0.5.2 and prior to 0.8.5. It [&hellip;]<\/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,"footnotes":""},"categories":[],"tags":[],"vendor":[],"product":[],"attack_vector":[],"asset_type":[],"severity":[],"exploit_status":[],"class_list":["post-86270","post","type-post","status-publish","format-standard","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/posts\/86270","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/comments?post=86270"}],"version-history":[{"count":0,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/posts\/86270\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/media?parent=86270"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/categories?post=86270"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/tags?post=86270"},{"taxonomy":"vendor","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/vendor?post=86270"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/product?post=86270"},{"taxonomy":"attack_vector","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/attack_vector?post=86270"},{"taxonomy":"asset_type","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/asset_type?post=86270"},{"taxonomy":"severity","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/severity?post=86270"},{"taxonomy":"exploit_status","embeddable":true,"href":"https:\/\/www.ameeba.com\/blog\/wp-json\/wp\/v2\/exploit_status?post=86270"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}