SecureClaw: Dual Stack Open-Source Security Plugin and Skill for OpenClaw

Post Views: 21

SecureClaw: A Security Plugin and Skill for OpenClaw Agent Environments

As artificial intelligence (AI) agent frameworks increasingly automate tasks involving tools, files, and external services, security concerns arise around agent access, modification capabilities, and risk detection. To address these concerns, Adversa AI has developed SecureClaw, an open-source security plugin and skill designed for OpenClaw agent environments.

SecureClaw’s Architecture

SecureClaw’s architecture is unique in that it consists of two components: a plugin and a skill. The plugin integrates into OpenClaw’s plugin system, providing automated security auditing and hardening functions. The skill, on the other hand, includes a set of rule definitions and scripts that run alongside the agent, covering configuration-level checks and operational controls.

According to Alex Polyakov, co-founder of Adversa AI, most existing OpenClaw security tools only address specific threats in isolation. “They’re point solutions that solve one piece of the problem,” he said. In contrast, SecureClaw’s two-part structure is designed to provide a layered defense model, with a code-level plugin enforcing hardening at the gateway and configuration level, combined with a behavioral skill that gives the agent real-time awareness.

Key Features

SecureClaw includes 55 audit checks that evaluate an OpenClaw installation for security conditions, as well as hardening modules that apply changes based on audit findings. The project also includes scripts for running audits and applying hardening actions through a command-line workflow. Polyakov emphasized that SecureClaw was built to systematically address the full attack surface, mapped to the OWASP Agentic Security Initiative (ASI) Top 10 threat classes.

In addition to its auditing and hardening capabilities, SecureClaw includes 15 behavioral rules packaged in the skill component. These rules influence how the agent behaves when interacting with prompts, tools, and outputs, and are supported by nine scripts and four JSON pattern databases. Polyakov noted that performance constraints played a significant role in SecureClaw’s design, particularly around prompt length. To address this, the skill was optimized to approximately 1,150 tokens, which directly impacts the effectiveness of security instructions, user costs, and agent functionality.

Future Development

As enterprise adoption of OpenClaw is expected to grow, SecureClaw is being positioned to meet those requirements. Polyakov stated that the latest update added formal mappings to MITRE ATLAS agentic AI attack techniques (CoSAI) guidance, along with threat modeling documentation, to support enterprise security teams in compliance and risk assessment. Future work will focus on infrastructure-level hardening and rigorous Red Teaming.

Availability

SecureClaw is available for free on GitHub, providing a valuable resource for organizations looking to enhance the security of their OpenClaw environments.