AI SECURITY ALERT • SSRF

LLM Security Crisis: How the vLLM SSRF Flaw Allows Hackers to Steal Data from Internal Networks

By CyberDudeBivash • October 08, 2025 • Urgent Security Directive

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Disclosure: This is a security advisory for MLOps and Cloud Security professionals. It contains affiliate links to relevant security solutions. Your support helps fund our independent research.

Emergency Guide: Table of Contents

Chapter 1: The Gateway to Your AI Becomes a Gateway to Your Network

This is a critical alert for all MLOps and AI teams using the popular **vLLM** library for serving large language models. A new, high-severity **Server-Side Request Forgery (SSRF)** vulnerability, tracked as **CVE-2025-66778**, has been discovered and a patch is now available. This flaw turns your powerful, GPU-accelerated AI inference server into a pivot point that allows an attacker to breach your internal cloud network and steal your master cloud credentials. Immediate patching is required.

Chapter 2: Threat Analysis — The vLLM Server-Side Request Forgery (CVE-2025-66778)

An SSRF is a vulnerability where an attacker can trick a server-side application into making web requests on their behalf. In the context of a cloud environment, this is a catastrophic flaw.

The Exploit:

**The Vector:** The vulnerability exists in an API endpoint in the vLLM server that allows a user to load a model adapter from a URL.
**The Flaw:** The server-side code fails to properly validate the user-supplied URL. It does not check if the URL points to a public, external resource or a private, internal one.
**The Exploit:** An attacker sends a request to this endpoint, but instead of a public URL, they provide the internal IP address of the cloud provider’s **Instance Metadata Service** (e.g., `http://169.254.169.254/` on AWS).
**The Impact:** The vLLM server, running with a trusted role inside your VPC, dutifully makes a request to the metadata service on the attacker’s behalf and returns the response. By crafting the right path, the attacker can retrieve the temporary IAM credentials assigned to the EC2 instance, giving them direct access to your cloud environment.

Chapter 3: The Defender’s Playbook — Immediate Patching & Hardening

A multi-layered defense is required to mitigate this threat.

1. PATCH vLLM IMMEDIATELY

The vLLM project has released a patched version that correctly validates URLs. You must update your vLLM installation immediately by running `pip install -U vllm`.

2. HARDEN Your Network Configuration

You must implement network-level compensating controls. Your vLLM server’s Security Group (firewall) should have a rule that **blocks all outbound traffic** to the metadata IP address (`169.254.169.254`).

3. ENFORCE IMDSv2

On your EC2 instances, you must enforce the use of **Instance Metadata Service Version 2 (IMDSv2)**. IMDSv2 requires a session token for requests, which makes this basic SSRF attack much more difficult to execute. This is a critical hardening step for your entire AWS fleet.

4. HUNT for Compromise

You must hunt for signs that this was already exploited.

**Analyze web server logs:** Search your vLLM/web server logs for any requests that contain private or metadata IP addresses.
**Analyze CloudTrail:** Scrutinize your AWS CloudTrail logs for any anomalous or unexpected API calls being made by the IAM role associated with your vLLM servers.

Chapter 4: The Strategic Takeaway — The Growing Attack Surface of MLOps

This incident is a powerful reminder that the Machine Learning Operations (MLOps) stack is now a critical part of your enterprise attack surface. Tools like vLLM, often deployed and managed by data science teams outside of traditional IT, are powerful server applications that can introduce significant risk if not properly secured.

For CISOs, this means your **AI security program** must extend beyond the models themselves and into the infrastructure that serves them. Your vulnerability management, secure configuration, and incident response processes must now fully encompass the unique tools and workflows of your MLOps pipeline.

Secure Your Cloud and AI Workloads: A Cloud Security Posture Management (CSPM) and Cloud Workload Protection Platform (CWPP) are essential for defending against these threats. **Kaspersky Hybrid Cloud Security** can detect the misconfigurations that allow SSRF and protect the workload itself from post-exploitation activity.

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About the Author

CyberDudeBivash is a cybersecurity strategist with 15+ years in AI security, cloud architecture, and DevSecOps, advising CISOs across APAC. [Last Updated: October 08, 2025]

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