CVE-2026-33304

OpenEMR is a free and open source electronic health records and medical practice management application.

Verified by Precogs Threat Research
Last Updated: Mar 20, 2026
Base Score
6.5MEDIUM

Executive Summary

CVE-2026-33304 is a medium severity vulnerability affecting appsec. It is classified as CWE-639. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.

Precogs AI Insight

"The fundamental weakness here is traced back to within OpenEMR, allowing the improper handling of untrusted input. An attacker can craft a specific payload to gain unauthorized read or write access, effectively hijacking underlying configurations. By intercepting insecure data flows from user input directly to rendering sinks, Precogs is designed to harden the environment against lateral movement."

Exploit Probability (EPSS)
Low (0.1%)
Public POC
Undisclosed
Exploit Probability
Low (<10%)
Public POC
Available
Affected Assets
appsecCWE-639

What is this vulnerability?

CVE-2026-33304 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.

OpenEMR is a free and open source electronic health records and medical practice management application. Prior to 8.0.0.2, an authorization bypass in the d...

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

MetricValue
CVSS Base Score6.5 (MEDIUM)
Vector StringCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
PublishedMarch 19, 2026
Last ModifiedMarch 20, 2026
Related CWEsCWE-639, CWE-862

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

Vulnerability Code Signature

Attack Data Flow

StageDetail
SourceUntrusted User Input
VectorInput flows through the application logic without sanitization
SinkExecution or Rendering Sink
ImpactApplication 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

Related Vulnerabilitiesvia CWE-639

CVE-2026-339316.5 MEDIUM

IDOR in OpenEMR Patient Portal payment page before 8.0.0.3. Authenticated patients can access other patients' payment and billing data (PHI) by manipulating the 'recid' parameter.

CWE-639
CVE-2026-339344.3 MEDIUM

IDOR in OpenEMR Patient Portal 'show-signature.php' before 8.0.0.3. Authenticated patients can retrieve staff member signature images by supplying arbitrary user values in the POST body.

CWE-639
CVE-2026-340558.1 HIGH

IDOR in OpenEMR library/pnotes.inc.php before 8.0.0.3. Legacy patient notes functions fail to verify ownership, allows users to access and manipulate notes of unauthorized patients.

CWE-639
CVE-2026-334250 UNKNOWN

Discourse is an open-source discussion platform.

CWE-203CWE-639CWE-862
CVE-2026-330538.8 HIGH

Langflow is a tool for building and deploying AI-powered agents and workflows.

CWE-639
CVE-2026-321140 UNKNOWN

Discourse is an open-source discussion platform.

CWE-639

Is your system affected?

Precogs AI detects CVE-2026-33304 in compiled binaries, LLMs, and application layers — even without source code access.