Cyber Resilience

CVE-2025-66580

RCE in Openagentplatform Dive ≤ 0.11.1

Public PoCRCEXSS
Published
19 December 2025
Modified
02 January 2026
Patch / advisory
CVSS Score v3.1 9.6
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
EPSS Score 0.0050 40th percentile
Risk Priority 68 floored blend · peak EPSS

Summary

CVE-2025-66580 is a critical-severity Code Injection (CWE-94) vulnerability in Openagentplatform Dive. Its CVSS base score is 9.6 (Critical).

Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 40th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the Protocol-Specific Risks risk domain.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

Deeper analysis AI-assisted summary

Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.

Dive is an open-source Model Context Protocol (MCP) Host Desktop Application designed to enable integration with function-calling large language models (LLMs). A critical Stored Cross-Site Scripting (XSS) vulnerability, tracked as CVE-2025-66580, affects versions prior to 0.11.1 in its Mermaid diagram rendering component. This flaw allows the execution of arbitrary JavaScript code via javascript: protocols, as mapped to CWE-79 (XSS) and CWE-94 (code injection).

Attackers can exploit the vulnerability remotely without privileges by injecting a malicious MCP server configuration into the application. Exploitation requires user interaction, specifically clicking on the affected node in the diagram, which triggers the payload and results in remote code execution (RCE) on the victim's machine. The issue carries a CVSS v3.1 base score of 9.6 (AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H), reflecting high impacts on confidentiality, integrity, and availability with low attack complexity over the network.

The official GitHub security advisory (GHSA-xv8m-365j-x6h2) for the OpenAgentPlatform/Dive repository confirms that updating to version 0.11.1 resolves the vulnerability by addressing the javascript: execution in the Mermaid renderer.

Notably, the vulnerability occurs in a desktop application tailored for LLM integrations, underscoring security risks in emerging AI-agent tools that handle dynamic content like diagrams. No public reports of real-world exploitation were available as of the CVE publication on 2025-12-19.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

Dive is an open-source MCP Host Desktop Application that enables integration with function-calling LLMs. A critical Stored Cross-Site Scripting (XSS) vulnerability exists in versions prior to 0.11.1 in the Mermaid diagram rendering component. The application allows the execution of arbitrary…

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JavaScript via `javascript:`. An attacker can exploit this to inject a malicious Model Context Protocol (MCP) server configuration, leading to Remote Code Execution (RCE) on the victim's machine when the node is clicked. Version 0.11.1 fixes the issue.

CWE(s)

AI Security AnalysisAI

AI Category
AI Agent Protocols and Integrations
Risk Domain
Protocol-Specific Risks
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: llms, mcp, model context protocol

Related Threats

MITRE ATT&CK Enterprise Techniques

T1185 Browser Session Hijacking Collection
Adversaries may take advantage of security vulnerabilities and inherent functionality in browser software to change content, modify user-behaviors, and intercept information as part of various browser session hijacking techniques.
T1539 Steal Web Session Cookie Credential Access
An adversary may steal web application or service session cookies and use them to gain access to web applications or Internet services as an authenticated user without needing credentials.
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
T1059 Command and Scripting Interpreter Execution
Adversaries may abuse command and script interpreters to execute commands, scripts, or binaries.
T1059.001 PowerShell Execution
Adversaries may abuse PowerShell commands and scripts for execution.
T1059.002 AppleScript Execution
Adversaries may abuse AppleScript for execution.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-40809Shared CWE-79, CWE-94
CVE-2023-1030Shared CWE-79, CWE-94
CVE-2023-7035Shared CWE-79, CWE-94
CVE-2023-4709Shared CWE-79, CWE-94
CVE-2023-45144Shared CWE-79, CWE-94
CVE-2023-0625Shared CWE-79, CWE-94
CVE-2019-3929Shared CWE-79
CVE-2023-22288Shared CWE-79
CVE-2023-0776Shared CWE-79
CVE-2023-6164Shared CWE-79

Affected Assets

openagentplatform
dive
≤ 0.11.1

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.3.2
  • V1.3.1

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation finds code paths that accept and execute externally influenced strings.

Input validation directly stops untrusted data from being used to construct executable code without neutralization.

Output filtering can catch or sanitize unneutralized script content before it is served to users.

Least privilege limits the damage an injected code fragment can perform once executed.

Requiring documented secure development standards and tools enforces use of safe code-generation APIs and escaping.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

PR.PS-06's SDLC practices directly target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).

PR.PS-02 partial match
prevents

Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).

PR.DS-10 none match
prevents

PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

finds

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

prevents

Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.

prevents

Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.

prevents

Banning unapproved code samples and unauthenticated web services, combined with secure-coding standards and SAST, prevents the dynamic generation or inclusion of attacker-supplied code.

none

Controls that restrict unauthorized or malicious code from being introduced via external networks or removable media limit opportunities for an attacker to inject and execute arbitrary code.

References