External risk intelligence

Cybersecurity AI Command Injection Vulnerability in SSH Functionality

CVE advisorySeverity: CRITICAL (CVSS 9.6)

CVE-2025-67511

The vulnerability exists within a framework for AI agents intended for offensive and defensive automation. This framework is typically utilized by developers and security engineers in internal research or specialized environments rather than as a public-facing network service or internet gateway. While network-reachable in some custom configurations, public internet exposure is uncommon for this type of framework.

Command Injection

Aliasrobotics Cybersecurity Ai

0.5.9 and earlier

Halo Surface Signal: 2 out of 5 — less likely to be public-facing.

External exposure likelihood

Horizon Alert

Summary of the vulnerability and why it matters

A critical vulnerability has been identified in the Cybersecurity AI framework, an open-source tool used for developing AI-powered security automation. The issue allows for command injection, meaning an attacker could potentially run unauthorized commands on systems where the framework is deployed. This could have broad implications if the framework is integrated into sensitive operations or external-facing services.

Allows attackers to run unauthorized commands.
Critical flaw impacts AI security automation framework.
Confirm relevance and potential exposure.

Attack Path

How an attacker could exploit the issue

An attacker could target the Cybersecurity AI framework by sending specially crafted input to an AI agent. If an agent uses the vulnerable `run_ssh_command_with_credentials()` function, the attacker's input could be interpreted as a command, allowing them to execute arbitrary code on the system.

No authentication required to reach.
Triggered by agent using vulnerable function.
Allows arbitrary code execution.

Live Threat

Current exploitation, exposure, and threat context

When supported by the advisory, AI agents running Cybersecurity AI could execute arbitrary commands on systems they manage when interacting with an attacker-controlled host. This could occur if an AI agent is tricked into connecting to a malicious server or processing specially crafted input related to host, port, or username parameters.

Agent-managed system data.
Malicious host or input.
Unauthorized command execution.

Operational Fix

Recommended remediation, mitigation, and detection steps

Given that Cybersecurity AI is an open-source framework for AI agents, ownership likely resides with the teams responsible for deploying and managing AI tools, such as platform or security engineering teams. The immediate first step is to locate all instances of this framework, determine their exposure and criticality, and identify the accountable owner before planning remediation.

Identify and confirm ownership.
Verify asset reachability and criticality.
Plan remediation based on risk.

Supplementary metadata

CVSS vector

Validate whether this threat affects your internet-facing exposure.

Halo Threat Intelligence helps prioritize remediation with Halo Surface Signal and H/A/L/O context. Start exposure validation with a free external attack surface trial.

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Frequently asked questions

What is the Cybersecurity AI framework?

Cybersecurity AI is an open-source framework designed to help developers and security engineers build and deploy AI agents for offensive and defensive automation. It functions as a platform that enables AI to perform security tasks, such as managing connections or interacting with systems, rather than acting as a standalone application.

What does CWE-77 mean for CVE-2025-67511?

CWE-77 is the weakness class for command injection. In this CVE, it means the framework incorrectly handles user-supplied input when building SSH commands. Because the system fails to properly sanitize the host, port, or username fields, an attacker can insert additional malicious commands that the underlying system will execute instead of just the intended SSH operation.

How is this command injection triggered?

The vulnerability is triggered when an AI agent utilizes the run_ssh_command_with_credentials function with malicious parameters. While the function does correctly escape password and command strings, it fails to sanitize the host, port, and username values. If an agent is directed to use these specific unvalidated fields, an attacker can manipulate them to execute unauthorized code. Standard command or password inputs do not trigger this specific flaw.

Is my system at risk according to Halo Surface Signal?

Halo Surface Signal suggests that risk is generally unlikely for most users. Because this framework is typically deployed in internal research or specialized environments, it is rarely exposed as a public-facing network service. You should primarily be concerned if your specific implementation has customized the framework to make it reachable over the internet.

What should I do if I use Cybersecurity AI?

Since there is currently no official software patch, your first step is to locate all deployments of the framework within your environment. Identify which teams own these instances and evaluate whether any AI agents are currently using the run_ssh_command_with_credentials function. Once mapped, assess the criticality of those systems to prepare for risk mitigation once a fix becomes available.

References

Written by Nicholas Merritt

Nicholas Merritt is VP of Security Solutions at Halo Security. With more than 25 years across application security, vulnerability prioritization, and offensive security, he helps teams translate threat data into practical exposure validation and remediation focus. He authors Halo Threat Intelligence CVE advisories using Halo Surface Signal and H/A/L/O context to prioritize internet-facing risk.