CVE-2026-25130 — Argument Injection Leading to Remote Code Execution

Vulnerability Summary

• CVE ID: CVE-2026-25130
• Affected Product: Cybersecurity AI (CAI)
• Affected Versions: All versions up to and including 0.5.10
• Vulnerability Class: Argument Injection / OS Command Injection
• CWE: CWE-78 – Improper Neutralization of Special Elements used in an OS Command
• CVSS v3.1 Score: 9.7 (Critical)
• Severity: Critical
• Attack Vector: Network
• Privileges Required: None
• User Interaction: Required (indirect, via AI input or ingested content)
• Impact: Full compromise of confidentiality, integrity, and availability
• Exploitability: High
• Exploit Availability: Exploitation techniques and proof-of-concept behavior are publicly discussed for educational and defensive purposes only; no weaponized exploit kit is required due to the simplicity of the flaw.

Official Patch / Upgrade

The vulnerability is officially fixed by the CAI maintainers.
All affected installations must be upgraded or patched immediately.

Official patch commit:
https://github.com/aliasrobotics/cai/commit/e22a1220f764e2d7cf9da6d6144926f53ca01cde

Technical Description

In vulnerable versions of Cybersecurity AI (CAI), a helper function named find_file() is used as part of the reconnaissance tooling. This function dynamically builds a system command using user-controlled input and executes it via Python’s subprocess.Popen() with shell=True.

Because the shell is explicitly invoked, all shell metacharacters and command operators embedded in the input are interpreted, rather than treated as literal data. Input validation or sanitization is not enforced before execution. As a result, arguments intended to represent file search patterns may instead be interpreted as additional shell instructions.

This design flaw results in argument injection, which directly escalates into remote code execution when crafted input is supplied. The executed commands run with the same privileges as the CAI process itself.

Root Cause Analysis

The vulnerability exists due to a combination of the following conditions:

• User-controlled or externally sourced input is accepted by the CAI agent
• Input is concatenated into a shell command string
• shell=True is used, allowing shell parsing and expansion
• Certain internal CAI tools are treated as “safe” and bypass manual approval
• No allow-listing or strict argument validation is applied

This results in a classic but highly impactful command injection scenario.

Exploitation Overview (Educational Context Only)

Exploitation is possible when an attacker is able to influence the input that reaches the find_file() function. This may occur through:

• Malicious prompts supplied to the AI agent
• Content fetched or parsed from untrusted external sources
• Data indirectly passed through AI reasoning chains into tool arguments

By embedding shell control operators or command-executing flags into the input, the shell interprets the injected components as valid commands. The operating system then executes them immediately.

No authentication or elevated privileges are required. The attack is carried out entirely within the normal execution flow of the CAI agent.

MITRE ATT&CK Technique Mapping

This vulnerability enables attacker behavior consistent with the following ATT&CK techniques:

These mappings are provided to support threat modeling, detection engineering, and incident response planning.

Detection Strategy

Primary Detection Goal

Detection should focus on identifying unexpected shell execution originating from the CAI process, especially when command arguments contain suspicious operators.

Relevant Log Sources

The following log sources are critical for effective detection:

• Process creation logs
  (Linux auditd, Windows Sysmon, EDR telemetry)
• Command-line argument logging
• CAI application and tool invocation logs
• Container runtime logs (if CAI is containerized)
• System call auditing (execve)

Suspicious Indicators to Monitor

• CAI Python process spawning a shell (sh, bash, cmd.exe)
• Use of find with unexpected execution flags
• Presence of shell metacharacters in command arguments:
  • ;
  • &&
  • |
  • `
  • $()
• Child processes whose parent is the CAI agent but are unrelated to normal CAI operations

Detection Rules

Sigma Rule

title: CAI Command Injection Behavior
id: cve-2026-25130-detection
description: Detects shell execution spawned by CAI with suspicious arguments
logsource:
  product: linux
  service: auditd
detection:
  selection:
    syscall: execve
    parent_process|contains: python
    process_name:
      - sh
      - bash
    command_line|contains:
      - "-exec"
      - "&&"
      - ";"
      - "|"
  condition: selection
level: critical

Auditd Detection Logic

• Monitor execve calls
• Filter where parent process is CAI’s Python runtime
• Alert when executed binary is a shell or system utility
• Correlate with command lines containing control operators

Indicators of Compromise (IOC Guidance)

While no static IOCs are guaranteed, the following patterns should be investigated:

• Shell processes executed shortly after CAI tool usage
• Unexpected outbound network connections from CAI hosts
• Files created or modified by CAI outside expected directories
• Logs showing abnormal arguments passed to CAI tools

Incident Response Guidance

If exploitation is suspected:

1. The affected system should be isolated immediately
2. Full process execution history should be preserved
3. All CAI tool invocation logs should be reviewed
4. Any credentials accessible to CAI should be rotated
5. The official patch or upgrade must be applied before redeployment

Why This Vulnerability Is High Risk

• Remote code execution is achieved without authentication
• Exploitation complexity is low
• AI agents often process untrusted external content
• Command execution occurs under trusted automation contexts
• Compromise may remain unnoticed without process-level logging

Preventive and Hardening Recommendations

• Avoid use of shell=True in all automation code paths
• Use argument lists instead of shell strings
• Enforce strict allow-lists for system tools and flags
• Require human approval for any OS-level command execution
• Run CAI with least privilege and strong isolation controls
• Enable detailed logging of all tool executions

Final Takeaway

CVE-2026-25130 highlights the risks introduced when AI-driven automation interacts directly with operating system commands. While the functionality was designed for convenience, unsafe shell execution transformed it into a critical security flaw. Prompt patching, strong monitoring, and secure coding practices are essential to prevent similar issues in AI-assisted security tooling.