CVE-2026-32895

OpenClaw versions prior to 2026.

Verified by Precogs Threat Research
Last Updated: Mar 21, 2026
Base Score
5.4MEDIUM

Executive Summary

CVE-2026-32895 is a medium severity vulnerability affecting ai-code, appsec. It is classified as Incorrect Authorization. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.

Precogs AI Insight

"The defect is inherently caused by within OpenClaw versions prior, allowing insufficient sanitization protocols during data parsing. Exploitation typically involves an attacker attempting to compromise the entire application stack, rendering traditional defenses ineffective. Precogs combines static analysis with threat intelligence to prevent unauthorized logical exploitation."

Exploit Probability (EPSS)
Low (0.0%)
Public POC
Undisclosed
Exploit Probability
Low (<10%)
Public POC
Available
Affected Assets
ai codeappsecCWE-863

What is this vulnerability?

CVE-2026-32895 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.

OpenClaw versions prior to 2026.2.26 fail to enforce sender authorization in member and message subtype system event handlers, allowing unauthorized events...

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 Score5.4 (MEDIUM)
Vector StringCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N
PublishedMarch 21, 2026
Last ModifiedMarch 21, 2026
Related CWEsCWE-863

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-863

Is your system affected?

Precogs AI detects CVE-2026-32895 in compiled binaries, LLMs, and application layers — even without source code access.