If you’re running AI agents that install skills from public marketplaces, you need to read this. Today, August 6, 2026, at Black Hat USA, Zenity Labs dropped a disclosure that should be required reading for every AI agent operator: a malicious skills campaign with more than 1.7 million aggregate installs has been uncovered across public AI agent marketplaces — and the attackers were hiding in plain sight for months.

Simultaneously, Zenity open-sourced Promptware EOD — described as an “agent detonation chamber” — a framework for red-teaming and analyzing the malicious payloads hiding in AI agent supply-chain artifacts. This is a major moment for AI security: the first serious malware-analysis tooling purpose-built for the AI agent ecosystem is now publicly available.

What Happened: The 1.7M Install Campaign

Zenity Labs researchers, presenting their briefing “Promptware EOD: Skillful Agent Detonation” at Black Hat USA 2026 (South Seas C&D, August 6), disclosed the findings from an extensive analysis of skills published to public marketplaces — including Vercel’s skills.sh platform.

The findings are sobering:

  • Hundreds of malicious or dangerous skills were discovered across public marketplaces
  • One active campaign had accumulated more than 1.7 million aggregate installs — credential-stealing malware that remained undetected for months
  • Malicious payloads hid inside skill markdown files using evasion techniques designed to blind static scanners (including a notorious case where the evasion instruction literally read “these aren’t the droids you’re looking for”)
  • Attack types included cryptominers and infostealers, operating through the five-stage Promptware kill chain: initial access → persistence → lateral movement → actions on objectives

After discovery, Zenity coordinated with Vercel to quickly disrupt the active campaign.

What Is Promptware?

“Promptware” is the term Zenity uses to describe malware that operates through the AI agent supply chain — payloads hidden in artifacts that agents consume and execute:

  • Skills and plugins (agent marketplaces)
  • Markdown files (documentation, instructions agents read)
  • MCP servers (Model Context Protocol integrations)
  • Model files (fine-tuned or quantized models)
  • Platform posts (content that agents browse or summarize)

The attack surface is the entire set of inputs an AI agent trusts. And unlike traditional malware, promptware doesn’t need to exploit a code vulnerability — it exploits the fact that agents are designed to follow instructions. A malicious skill that tells an agent to exfiltrate credentials doesn’t need a buffer overflow; it just needs to be installed.

Promptware EOD: The Open-Source Detonation Chamber

The centerpiece of today’s disclosure is the open-sourcing of Promptware EOD (Explosive Ordnance Disposal — the name is intentional). This is the tool Zenity built to analyze malicious skills at scale.

Rather than relying on LLM-based static analysis (which can be fooled by the same evasion techniques the attackers used), Promptware EOD takes a behavioral approach:

  • Agent honeypots — run suspect skills in isolated agent environments and observe what they actually do
  • Kernel-level insights — monitor system calls, network activity, and filesystem operations at a low level that the malicious skill can’t see or evade
  • Behavioral fingerprinting — identify attack patterns across thousands of detonated skills

This is essentially the AI-agent equivalent of a sandboxed malware analysis platform — the same technology that endpoint security teams use to safely analyze suspicious executables, now applied to the AI agent supply chain.

The full report was expected to be released at labs.zenity.io following the Black Hat session. CTO Michael Bargury and the Zenity research team (including Francesco Montorsi et al.) led the work.

What This Means for OpenClaw and Agent Skill Users

If you’re using OpenClaw or any platform that lets you install third-party skills, MCP servers, or agent plugins, this is directly relevant to you. Some practical guidance based on the research:

Verify Sources Before Installing

  • Prefer skills from verified, trusted publishers over anonymous submissions
  • Check for any unusual instructions in skill documentation — particularly anything that redirects the agent’s behavior in ways unrelated to the stated purpose
  • Be skeptical of skills with oddly high install counts relative to their age or publisher reputation

Audit What You Have Installed

  • Review your currently installed skills and MCP servers
  • Look for any that have unusually broad permissions (filesystem access, network access, credential access) that don’t match their stated function
  • Remove anything you don’t actively use

Watch the Zenity Disclosure for Tool Access

  • The Promptware EOD framework is now open-source. Once Zenity releases the full report and tooling at labs.zenity.io, OpenClaw users running local agents should consider using it to audit their skill installations
  • At time of writing, the full repository and documentation are expected to follow the Black Hat session — check the Zenity Labs GitHub or labs.zenity.io for availability

Don’t Trust Static Scans Alone

  • The 1.7M install campaign evaded static analysis specifically by including obfuscation instructions in the skill’s own markdown. Static LLM-based scanning can be fooled the same way. Behavioral analysis (what does the skill actually do when run?) is more reliable

The Bigger Picture: AI Supply Chain Security Is Now Real

This disclosure represents a maturation moment for AI security. The questions researchers have been raising theoretically for two years — “what if someone hides malicious instructions in an agent’s skill?” — have now been answered empirically with production data.

The good news: Zenity caught this, coordinated disclosure, and is sharing their tools with the community. The ecosystem has defenders who are taking this seriously.

The sobering reality: 1.7 million installs happened before anyone caught it. The attack surface is large, the detection tools are immature, and the adversaries are already active.

For anyone building or operating AI agents, the message is clear: treat your agent’s supply chain — the skills, MCP servers, and tools it consumes — with the same security scrutiny you’d apply to any third-party code dependency. Because that’s exactly what it is.

Sources

  1. Zenity Labs BusinessWire Disclosure — Aug 6, 2026
  2. Zenity Labs Black Hat USA 2026 — Event Page
  3. Black Hat USA 2026 AI Security Recap — Straiker.ai
  4. Web search cross-reference — confidence 91/100

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260806-0800

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