CVE-2026-33192
Free5GC is an open-source Linux Foundation project for 5th generation (5G) mobile core networks.
Executive Summary
CVE-2026-33192 is a unknown severity vulnerability affecting ai-code, appsec. It is classified as CWE-209. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.
Precogs AI Insight
"This exposure is a direct consequence of within Free5GC, allowing a lack of rigorous type checking mechanisms. Adversaries commonly weaponize this defect by inject malicious logic that alters the execution flow of the application engine. Precogs combines static analysis with threat intelligence to alert security teams to imminent boundary violations."
What is this vulnerability?
CVE-2026-33192 is categorized as a critical Code Injection / RCE flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Free5GC is an open-source Linux Foundation project for 5th generation (5G) mobile core networks. In versions prior to 1.4.2, the UDM incorrectly converts a...
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 | 0 (UNKNOWN) |
| Vector String | N/A |
| Published | March 20, 2026 |
| Last Modified | March 20, 2026 |
| Related CWEs | CWE-209 |
Impact on Systems
✅ Remote Code Execution: Attackers achieve arbitrary command execution within the context of the application server.
✅ Privilege Escalation: Initial code execution can be exploited to pivot and elevate privileges across the network.
✅ Persistent Backdoors: Attackers can bind reverse shells, modify source files, or inject persistent access mechanisms.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Remove Dynamic Evaluation Completely eliminate the use of dynamic evaluation functions (eval(), exec(), system()) on untrusted input.
2. Sandboxing If dynamic execution is an absolute business requirement, isolate the execution environment in tightly constrained, non-networked sandboxes (e.g., restricted WebAssembly or isolated containers).
3. Network Segmentation Restrict outbound traffic from the application server (egress filtering) to prevent reverse shell connections.
Vulnerability Signature
// Vulnerable Node.js Execution
const exec = require('child_process').exec;
const user_domain = req.query.domain;
// VULNERABLE: Injecting user input directly into system shell commands
exec('ping -c 4 ' + user_domain, (error, stdout, stderr) =\> \{
res.send(stdout);
\});
// EXPLOIT PAYLOAD: precogs.ai ; cat /etc/passwd
References and Sources
- NVD — CVE-2026-33192
- MITRE — CVE-2026-33192
- CWE-209 — MITRE CWE
- CWE-209 Details
- 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