CVE-2025-59417
[lobe-chat] Remote Code Execution via XSS in Chat Messages in Lobe Chat Desktop
Executive Summary
CVE-2025-59417 is a medium severity vulnerability affecting ai-code, appsec. It is classified as an undisclosed flaw. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"The underlying mechanism of this vulnerability involves within ### Summary, allowing the insecure processing of malicious payloads. An attacker can craft a specific payload to seize control of the underlying infrastructure and pivot to adjacent networks. The Precogs multi-engine scanning approach is specifically built to identify exploitable weaknesses before attackers do."
What is this vulnerability?
CVE-2025-59417 is categorized as a critical Cross-Site Scripting (XSS) flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Summary
We identified a cross-site scripting (XSS) vulnerability when handling chat message in lobe-chat that can be escalated to remote code execut.
This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.
Risk Assessment
| Metric | Value |
|---|---|
| CVSS Base Score | 5.5 (MEDIUM) |
| Vector String | N/A |
| Published | September 18, 2025 |
| Last Modified | September 18, 2025 |
| Related CWEs | N/A |
Impact on Systems
✅ Session Hijacking: Attackers can steal active user session tokens (cookies) to impersonate the victim.
✅ Phishing Execution: Malicious scripts can dynamically alter DOM content to present fraudulent login forms.
✅ Worm Propagation: Stored XSS can spread autonomously as users visit the infected page.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Output Encoding Implement strict context-aware output encoding (HTML, JavaScript, Attribute, CSS) before rendering user data.
2. Content Security Policy (CSP) Deploy a rigorous CSP header to restrict script execution exclusively to trusted domains.
3. Framework Defenses Utilize native UI framework protections (e.g., React DOM escaping) and avoid dangerouslySetInnerHTML.
Vulnerability Signature
// Example DOM-based XSS vulnerability
const user_input = new URLSearchParams(window.location.search).get('q');
// VULNERABLE: Direct insertion into innerHTML
document.getElementById('results').innerHTML = "Results for: " + user_input;
// EXPLOIT PAYLOAD: ?q=\<img src=x onerror=alert(document.cookie)\>
References and Sources
- NVD — CVE-2025-59417
- MITRE — CVE-2025-59417
- AI Code Security Vulnerabilities
- Application Security Vulnerabilities
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Untrusted User Input |
| Vector | Input flows through the application logic without sanitization |
| Sink | Execution or Rendering Sink |
| Impact | Application compromise, Logic Bypass, Data Exfiltration |
Vulnerable Code Pattern
# ❌ VULNERABLE: Unsanitized Input Flow
def process_request(request):
user_input = request.GET.get('data')
# Taint sink: processing untrusted data
execute_logic(user_input)
return {"status": "success"}
Secure Code Pattern
# ✅ SECURE: Input Validation & Sanitization
def process_request(request):
user_input = request.GET.get('data')
# Sanitized boundary check
if not is_valid_format(user_input):
raise ValueError("Invalid input format")
sanitized_data = sanitize(user_input)
execute_logic(sanitized_data)
return {"status": "success"}
How Precogs Detects This
Precogs AI Analysis Engine maps untrusted input directly to execution sinks to catch complex application security vulnerabilities.\n