CVE-2025-31490

What is this vulnerability?

CVE-2025-31490 is categorized as a critical Application Verification Flaw flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

Description =========== AutoGPT uses a wrapper around the requests python library, located in [autogpt_platform/backend/backend/util/request.py](http.

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

Impact on Systems

✅ Unauthorized Access: Flaws in application logic can permit unauthorized interaction with protected APIs.

✅ Data Manipulation: Adversaries may alter critical application states, such as user roles or configurations.

✅ Service Disruption: Improper error handling or unvalidated inputs can lead to resource exhaustion.

How to fix this issue?

Implement the following strategic mitigations immediately to eliminate the attack surface.

1. Defense in Depth Implement multi-layered validation (client-side, API gateway, and server-side).

2. Least Privilege Ensure backend service accounts operate with the absolute minimum rights required.

3. Security Regression Testing Integrate automated semantic security scanning into the deployment pipeline.

Vulnerability Signature

// Generic Application Security Flaw (Node.js)
app.post('/api/update-profile', (req, res) =\> \{
    // DANGEROUS: Mass Assignment / Object Injection
    // Attacker can pass \{ "isAdmin": true, "email": "..." \}
    User.update(\{ id: req.user.id \}, req.body);
    
    // SECURED: Explicitly select permitted fields
    const \{ email, displayName, bio \} = req.body;
    User.update(\{ id: req.user.id \}, \{ email, displayName, bio \});
\});

References and Sources

• NVD — CVE-2025-31490
• MITRE — CVE-2025-31490
• CWE-918 — MITRE CWE
• CWE-918 Details
• Application Security Vulnerabilities
• AI Code Security Vulnerabilities
• Binary Analysis Vulnerabilities
• PII and Secrets Exposure

Vulnerability Code Signature

Attack Data Flow

Vulnerable Code Pattern

// ❌ VULNERABLE: Server-Side Request Forgery
app.get('/proxy', async (req, res) => {
  const targetUrl = req.query.url;
  // Taint sink: unvalidated outbound request
  const response = await fetch(targetUrl);
  res.send(await response.text());
});

Secure Code Pattern

// ✅ SECURE: Allowlist validation
const ALLOWED_DOMAINS = ['api.partner.com'];
app.get('/proxy', async (req, res) => {
  const targetUrl = new URL(req.query.url);
  
  if (!ALLOWED_DOMAINS.includes(targetUrl.hostname)) {
    return res.status(403).send("Domain not allowed");
  }
  
  // Sanitized outbound request
  const response = await fetch(targetUrl.href);
  res.send(await response.text());
});

How Precogs Detects This

Precogs API Security Engine actively detects SSRF vulnerabilities by tracking unvalidated URL sinks and enforcing strict allowlist policies.\n