OpenClaw

Zhou Hongyi Warns AI Tools Are Industrializing Vulnerability Discovery

At the Fourth Cyberspace Security Forum in Tianjin, 360 founder Zhou Hongyi stated that vulnerability mining is shifting from artisanal workshops to automated production lines, compressing discovery cycles from months or years down to hours. AI tools such as Mythos are standardizing and automating the process, enabling attackers to replicate elite hacker expertise at scale through distilled models and agent swarms. 360's own Tulongfeng platform has already discovered over 10,000 vulnerabilities since its June release, including long-hidden high-risk flaws in Windows, Office, OpenClaw, Flowise, and Codex. The emergence of multi-agent systems introduces new attack surfaces because compromised agents can autonomously collaborate and move laterally faster than human operators. Zhou described this as the "second one-way transparency," where offensive tradecraft becomes copy-pasteable via prompts and toolchains. Defenders are advised to adopt "model-versus-model" strategies, automate vulnerability intelligence workflows with SOAR, enforce strict agent permission audits, and integrate AI into their own code review and detection engineering processes.

Hermes Emerges as Modular Harness for Practical AI Security Testing

The article details the development of Hermes, a lightweight modular harness designed to turn raw language models into reliable AI security agents. Unlike heavy frameworks such as OpenClaw, Hermes uses dynamic skill loading, strict runbooks stored in Git, and a file-system source of truth to eliminate hallucinations and context bloat. It continuously scans dozens of sources including NVD, CISA KEV, arXiv and research blogs, then applies the custom TIPS scoring metric to rank threats before attempting reproduction. A dedicated Paper-to-PoC skill converts academic attack descriptions into executable code that is validated inside an isolated Ollama and Docker sandbox. Eight mandatory validation gates must pass before any finding is accepted, ensuring reproducibility and freshness of data. The system already supports tools such as Garak, PyRIT, promptfoo, fickling, modelscan and presidio, and evolves autonomously by committing successful attack scenarios back to its repository.

Cybercriminals Weaponize OpenClaw AI Agent in ClawHavoc Campaign to Distribute Infostealers

Threat actors have repurposed the OpenClaw AI agent to deliver infostealers by uploading hundreds of malicious skills to ClawHub. The campaign, named ClawHavoc, tricks users into executing encoded commands or installing required tools under the guise of helpful AI recommendations. Researchers at Trellix identified 341 malicious skills, with 335 targeting installation of Atomic macOS Stealer on macOS systems. On Windows, victims receive password-protected archives and fake verification utilities that mirror classic ClickFix tactics. Analysis of repository history uncovered 1,184 suspicious packages linked to 12 authors, enabling theft of passwords, browser data, crypto wallets, API keys, SSH keys, and source code. Users are advised to update OpenClaw, audit installed skills, remove suspicious packages, and rotate potentially compromised credentials while running the agent in a restricted environment.

Israeli Firm Reveals First Known AI-Led Breach of Taiwanese Government Systems

An Israeli cybersecurity company named Dream discovered an open 160 MB archive containing 1,395 files that documented a fully autonomous AI operation against Asian government infrastructure later identified as Taiwan. Between July 1 and July 4 2026 the system ran 12 sequential waves using up to eight sub-agents simultaneously, each handling reconnaissance, exploitation, lateral movement and persistence without further human input after initial setup. The agents mapped 21 interconnected government systems, exploited unauthenticated debug endpoints and single-sign-on weaknesses, and ultimately compromised 85 employee accounts while exfiltrating more than 2,500 personnel records. The framework relied exclusively on two publicly available open-source AI assistants, Hermes and OpenClaw, and bypassed model safety filters by framing the task as an authorized penetration test. The same agents later expanded into government IT suppliers, the national email system, seven energy companies and the nuclear safety agency while performing internal validation that rejected seven false-positive findings. No zero-day exploits were used; all successful access paths involved exposed endpoints, disabled signature checks and missing authentication controls.

Securing OpenClaw and Hermes AI Agents on One VPS: Hardening Lessons from Docker, SSH, and Prompt Injection Risks

A detailed case study examines the challenges of running OpenClaw and Hermes AI agents together on a single VPS, connected via an SSH channel with forced commands. The author deployed OpenClaw as an orchestrator handling Telegram messages and Hermes as an executor for heavy tasks inside its own Docker sandbox. Multiple security misconfigurations were discovered, including Docker publishing ports directly to 0.0.0.0, ufw being removed during iptables-persistent installation, and repeated resets of gateway.bind to lan. The built-in security audit revealed a critical issue where Telegram groups allowed arbitrary command execution without an allowlist. Additional risks included context file injection that could propagate through the ACP bridge and UID conflicts caused by cloud image defaults. The experience highlights that AI agents require strict least-privilege controls because they interpret arbitrary text as potential instructions.

OpenClaw AI Assistant Compromised via WhatsApp: Three Critical Vulnerabilities Allowed Credential Theft, Sandbox Escape, and Arbitrary Code Execution on Host

Security researchers discovered three high-severity vulnerabilities in OpenClaw that could let attackers steal credentials, escalate privileges, and execute arbitrary code on the host system running the AI assistant. Two flaws rated 8.8 on the CVSS scale stemmed from incomplete command filtering that failed to block dangerous inputs, while a third issue rated 8.4 enabled sandbox bypass by mounting parent directories such as /home or /var. The weaknesses potentially exposed sensitive data in ~/.ssh, ~/.aws, and ~/.gnupg, and even allowed attackers to reach the Docker socket for full host escape. Notably, the attack could be triggered remotely through an external WhatsApp message without any prior system access, according to researcher Chinmohan Nayak. All issues were patched in OpenClaw version 2026.6.6, and users are urged to update immediately while tightening sandbox and tool permissions.