CVE-2025-31494
[AutoGPT] Cross-user sharing of node execution results through WebSockets API
Executive Summary
CVE-2025-31494 is a low severity vulnerability affecting pii-secrets, ai-code. It is classified as Information Exposure. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"The fundamental weakness here is traced back to within ### Impact, allowing bypassed validation checks on external interactions. Exploitation typically involves an attacker attempting to compromise the entire application stack, rendering traditional defenses ineffective. Precogs automatically detects reversible cryptographic functions and hardcoded secrets to prevent unauthorized logical exploitation."
What is this vulnerability?
CVE-2025-31494 is categorized as a critical Sensitive Data Exposure flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Impact The AutoGPT Platform's WebSocket API transmitted node execution updates to subscribers based on the graph_id+graph_version. Additionally, t.
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 | 3 (LOW) |
| Vector String | N/A |
| Published | April 11, 2025 |
| Last Modified | April 11, 2025 |
| Related CWEs | CWE-200, CWE-284 |
Impact on Systems
✅ Authentication Bypass: Leaked credentials allow attackers to impersonate legitimate users or systems.
✅ Data Breach: Exposed PII triggers regulatory violations (GDPR/CCPA) and massive reputational damage.
✅ Lateral Movement: Exposed API tokens can be used to pivot deeper into internal infrastructure.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Secret Management Migrate all hardcoded secrets to a secure vault (e.g., AWS Secrets Manager, HashiCorp Vault).
2. Data Masking Implement automated redaction for logs to prevent PII/credentials from leaking into observability platforms.
3. Automated Scanning Deploy Precogs Secrets Scanner in pre-commit hooks and CI pipelines to prevent secret commits.
Vulnerability Signature
// Generic Secrets Exposure Vector
// DANGEROUS: Hardcoded secrets in source control or logs
const apiKey = "sk_live_1234567890abcdef";
console.log(`Connecting to API with key $\{apiKey\}`);
// SECURED: Secrets fetched from environment at runtime
const apiKey = process.env.API_SECRET_KEY;
if (!apiKey) throw new Error("API configuration missing");
// Never log secrets
console.log('Connecting to API... [REDACTED]');
References and Sources
- NVD — CVE-2025-31494
- MITRE — CVE-2025-31494
- CWE-200 — MITRE CWE
- CWE-200 Details
- CWE-284 — MITRE CWE
- CWE-284 Details
- PII and Secrets Exposure
- AI Code Security Vulnerabilities
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Application error or debug endpoint |
| Vector | Verbose error messages or sensitive metadata returned to the client |
| Sink | HTTP response |
| Impact | Information gathering, aids in further attacks |
Vulnerable Code Pattern
# ❌ VULNERABLE: Information Exposure
@app.errorhandler(500)
def internal_error(error):
# Taint sink: returns stack trace to user
return f"Internal Server Error: {error}", 500
Secure Code Pattern
# ✅ SECURE: Generic error message
@app.errorhandler(500)
def internal_error(error):
# Log the detailed error internally
app.logger.error(f"Server Error: {error}")
# Return a generic message to the user
return "An internal server error occurred.", 500
How Precogs Detects This
Precogs API Security Engine comprehensively audits all web endpoints to ensure verbose error messages and sensitive metadata are not exposed.\n