CVE-2025-69246

Raytha CMS does not have any brute force protection mechanism implemented.

Verified by Precogs Threat Research
Last Updated: Mar 16, 2026
Base Score
9.8CRITICAL

Executive Summary

CVE-2025-69246 is a critical severity vulnerability affecting appsec. It is classified as CWE-307. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.

Precogs AI Insight

"This exposure is a direct consequence of within Raytha CMS, allowing insufficient sanitization protocols during data parsing. Adversaries commonly weaponize this defect by gain unauthorized read or write access, effectively hijacking underlying configurations. Precogs AI Analysis Engine utilizes semantic code analysis to alert security teams to imminent boundary violations."

Exploit Probability (EPSS)
Low (0.1%)
Public POC
Available
Exploit Probability
High (84%)
Public POC
Available
Affected Assets
appsecCWE-307

What is this vulnerability?

CVE-2025-69246 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.

Raytha CMS does not have any brute force protection mechanism implemented. It allows an attacker to send multiple automated logon requests without triggeri...

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 Score9.8 (CRITICAL)
Vector StringCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
PublishedMarch 16, 2026
Last ModifiedMarch 16, 2026
Related CWEsCWE-307

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-307

Is your system affected?

Precogs AI detects CVE-2025-69246 in compiled binaries, LLMs, and application layers — even without source code access.