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OpenClaw x VirusTotal: A New Line of Defense Against Malicious AI Skills on ClawHub

ByInnoVirtuoso

If your AI agent had a mind of its own, would it quietly siphon your API keys, exfiltrate your browser data, and pivot to your crypto wallets? That’s not sci‑fi anymore—that’s the new reality of malicious “skills” sneaking into AI marketplaces. In response, OpenClaw just made a move the entire agentic AI world should pay attention to: a partnership with Google’s VirusTotal to automatically scan every skill uploaded to ClawHub before it goes live—plus daily re‑scans of what’s already active.

According to The Hacker News (Feb 7, 2026), this integration arrives amid mounting evidence that threat actors are abusing AI agents’ broad permissions, persistent memory, and third‑party extensions to stage credential theft, botnet operations, and data exfiltration. Security teams are sounding the alarm, and for good reason: researchers uncovered hundreds of malicious ClawHub skills masquerading as video or crypto utilities—but dropping keyloggers and the Atomic macOS Stealer (AMOS) once installed.

Let’s unpack what OpenClaw’s VirusTotal integration means, how it works, why it matters, and what teams should be doing today to secure their agent stacks.

What’s New: Automated Malware Screening for AI Skills

OpenClaw, the fast‑growing open‑source agent platform behind the ClawHub skills marketplace, is integrating VirusTotal into its submission and maintenance workflow:

  • All newly uploaded skills are scanned by VirusTotal before approval.
  • Malicious submissions are blocked; suspicious ones are flagged for human review.
  • Active skills undergo daily re‑scans to catch late‑breaking detections.

This is classic defense‑in‑depth applied to the agent ecosystem. It creates a baseline gate that repels known malware families, re‑packages, and commodity payloads that piggyback on seemingly harmless skills. It’s the same logic that package registries and mobile app stores have leaned on for years—now pointed squarely at the emerging supply chain for AI agents.

What makes this move stand out is timing. The agent era has arrived fast, and marketplace moderation hasn’t kept pace with the speed and creativity of attackers. OpenClaw’s step to automate malware triage with VirusTotal puts a scalable tripwire where it’s needed most: the first mile of software supply into agents.

Why This Matters Now

Several developments have collided to raise the stakes:

  • Security researchers found malicious skills on ClawHub marketed for botnet operations on underground forums like Exploit.in.
  • Koi Security documented a “ClawHavoc” campaign with 341 malicious skills disguised as YouTube tools and crypto helpers—but backdoored to deploy keyloggers and AMOS, harvesting wallets, browser data, and credentials.
  • Trend Micro reported actors leveraging OpenClaw skills for illicit activity, reinforcing that marketplaces are a practical distribution vector, not a theoretical one.
  • Censys identified more than 21,000 exposed OpenClaw instances, widening the blast radius of any compromise due to misconfigurations and shadow deployments.
  • Gartner reportedly labeled the current risk profile an “unacceptable cybersecurity liability,” citing shadow agent deployments and unvetted skill use that expose API keys and sensitive data.

The larger context: autonomous agents blur boundaries. They read mail, move money, query knowledge bases, call APIs, run code, and remember. That power makes them productive—and an attacker’s dream. A weaponized skill installed in the right place isn’t just a malicious package; it’s a foothold with permissions and memory, stitched into automated workflows, and often overlooked by traditional security controls.

How the VirusTotal Integration Helps (and What It Doesn’t)

VirusTotal aggregates detections from dozens of antivirus engines and sandboxes, providing a multi‑perspective verdict on files and URLs. For AI skills—often bundles of code, dependencies, and config—VT can:

  • Flag known malware families, droppers, and commodity loaders quickly.
  • Catch re‑packed or slightly modified versions of known threats.
  • Surface suspicious behaviors observed in dynamic analysis/sandboxing.

By wiring VT into ClawHub’s approval pipeline, OpenClaw reduces the odds that obvious malware or repurposed stealers will ever reach users. The daily re‑scan helps backfill coverage as new signatures roll out and as threat intel matures over time.

However, there are clear boundaries:

  • Prompt injection and jailbreaks: A skill with “clean” code can still smuggle malicious instructions via prompts or data, tricking an agent into unsafe actions. Scanners won’t catch that.
  • Logic bombs and feature misuse: A tool that exfiltrates data under certain conditions might not look malicious in static analysis.
  • Novel or targeted malware: Very new families may initially evade detections across engines.
  • Supply‑chain pivots: Dependencies fetched at runtime (e.g., a later‑resolved package) can bypass initial scans if not tightly constrained.
  • Environment‑specific payloads: Malware that activates only under specific OS/arch/permissions may not fully detonate in sandboxes.

Translation: VirusTotal dramatically improves the baseline, but it’s not a silver bullet. The agent ecosystem still needs policy, provenance, sandboxing, and least‑privilege controls to close the gaps.

Inside the “ClawHavoc” Campaign: What Went Wrong

Per reporting summarized by The Hacker News, the “ClawHavoc” cluster relied on classic disguise‑and‑drop tactics tailored to AI marketplaces:

  • Cover stories: YouTube download/conversion tools, crypto utilities, and “productivity enhancers.”
  • Inside the box: Keyloggers and stealer malware, notably AMOS (Atomic macOS Stealer), to vacuum wallets, browser data, saved passwords, and system info.
  • Underground distribution: Discussions and marketing to other actors via forums like Exploit.in, highlighting ease of use and reach within agent ecosystems.
  • Operational impact: Compromised keys and browser data equate to durable, monetizable access—ideal for account takeover, lateral movement, and fraud.

Why this works so well in agent worlds:

  • Users expect skills to act broadly: “Download this,” “Summarize that,” “Check my account,” etc. That normalizes risky scopes.
  • Skills chain together: A malicious skill can piggyback on otherwise benign actions by other tools.
  • Trusted paths are informal: If it’s on a marketplace and has ratings, many users will install—visibility and social proof trump scrutiny.

A VT gate won’t stop everything, but it will kneecap the lowest‑effort copies and derivative payloads that were getting a free pass.

The Unique Risk Profile of Autonomous AI Agents

Here’s why agents are different—and why defenders need to adjust:

  • Persistent memory: Agents “remember” context, credentials, and preferences, turning ephemeral sessions into durable targets.
  • Broad permissions: Agents often hold OAuth tokens, API keys, SSH access, or file system privileges to “get things done.”
  • Tool arbitrage: Skills wrap powerful OS and network capabilities. A compromised skill can transform that power into RCE, data exfiltration, or lateral movement.
  • Prompt injection and data poisoning: Instructions hidden in content (emails, web pages, PDFs, knowledge bases) can redirect agent behavior without altering code.
  • Marketplace trust assumptions: If a skill appears in an app store‑like environment, users treat it as safe—even if curation is thin.
  • Shadow deployments: Teams spin up agents without central oversight, fragmenting visibility and control.

Understanding these patterns is the first step to building agent‑aware defenses that go beyond traditional EDR and perimeter controls.

Defense‑in‑Depth for AI Skill Marketplaces

OpenClaw’s VT integration is a strong baseline. To raise the bar across the ecosystem, marketplaces and platform maintainers should layer the following:

  • Provenance and signing
  • Require skill signing and verify signatures on install and update.
  • Publish and enforce a chain of custody for builds (e.g., SLSA-style attestations; see slsa.dev).
  • SBOMs and dependency policy
  • Mandate SBOMs for each skill and pin dependencies by hash.
  • Block known-bad packages and enforce minimum versions for patched CVEs.
  • Permissioned capabilities
  • Fine‑grained permission prompts (“network egress to these domains,” “read-only filesystem,” “access to calendar scope X”).
  • Deny-by-default posture; progressive disclosure of sensitive scopes.
  • Runtime sandboxing
  • Containerized or VM‑isolated execution with read‑only filesystems, seccomp/AppArmor profiles, and no default outbound network.
  • Per‑skill identity to isolate credentials and telemetry.
  • Network egress controls
  • Marketplace‑side and client‑side domain allowlists; block common C2 patterns by default.
  • TLS inspection with DLP for enterprise deployments where policy allows.
  • Behavioral monitoring
  • Telemetry for file access, network calls, and data volumes. Alert on anomalous patterns (e.g., mass credential scraping).
  • Optional community‑shared IOCs where privacy permits.
  • Human review with context
  • Prioritize “suspicious” VT results, high‑permission requests, and brand‑impersonation skills for manual analysis.
  • Developer vetting
  • Verified publisher badges, mandatory MFA, and post‑compromise recovery procedures.
  • Responsible disclosure and transparency
  • Publish removal reasons, maintain an advisories feed, and support bug bounty submissions for malicious skill discovery.

For prompt‑centric risks:

  • Prompt and RAG governance
  • Treat prompts as code; review and version them.
  • Use retrieval allowlists and content sanitization.
  • Apply LLM safety patterns from OWASP’s LLM Top 10 (owasp.org) and threat model with MITRE ATLAS (atlas.mitre.org).

What OpenClaw Users Should Do Today

If you run OpenClaw or rely on ClawHub skills, take these steps now:

  • Update and audit
  • Upgrade to the latest OpenClaw runtime and marketplace client to benefit from VT checks as they roll out.
  • Inventory all installed skills; remove anything you don’t actively use.
  • Rotate secrets
  • Assume exposure if you installed unvetted skills in recent months. Rotate API keys, OAuth tokens, cloud creds, and refresh client secrets.
  • Move secrets to a managed vault and scope them minimally.
  • Lock down egress
  • Enforce domain allowlists for your agent host (e.g., only your SaaS APIs, CDNs, and update endpoints).
  • Block TOR exits, paste sites, and known malware C2 domains at the network layer.
  • Sandbox agents
  • Run agents with non‑privileged users in containers/VMs. Use read‑only filesystems and ephemeral workspaces that reset between sessions.
  • Isolate skills into separate sandboxes where possible.
  • Harden the host
  • Apply OS hardening baselines (CIS/SecureHost), enable disk encryption, and keep EDR/AV active and tuned for developer workflows.
  • Monitor aggressively
  • Log skill installs/updates, file writes, and outbound requests. Alert on unusual destinations or data volumes.
  • Subscribe to OpenClaw and ClawHub advisories; auto‑remove deprecated or delisted skills.
  • Pin and verify
  • Pin skills to specific versions and verify checksums/signatures. Review diffs before upgrading.
  • Validate publishers
  • Prefer verified publishers. Be wary of brand lookalikes, sudden spikes in ratings, and vague descriptions.

These measures aren’t just “nice to have.” They determine whether a marketplace hiccup becomes an enterprise incident.

Enterprise Playbook: SecOps + MLOps Collaboration

Agent security spans teams. Here’s a condensed playbook for enterprises deploying OpenClaw:

  • Governance
  • Create an Agent Security Standard: allowed models, allowed skills, data boundaries, and prohibited actions.
  • Establish a formal exception process for high‑risk permissions.
  • Platform controls
  • Route all agent traffic through secure egress with DLP and threat intel.
  • Require signed skills and attestation; deny unsigned installs.
  • Identity and secrets
  • Use dedicated service accounts with least privilege. Rotate tokens automatically. Enforce short‑lived credentials.
  • Data protection
  • Label and restrict sensitive corpora. Add guardrails for retrieval‑augmented generation (RAG) to prevent over‑broad queries.
  • Testing and staging
  • Stage new skills in a quarantined environment. Run dynamic analysis and DAST‑style tests for prompt injection and unsafe tool use.
  • Incident response
  • Pre‑build playbooks for “malicious skill discovered” events: isolate agent hosts, revoke tokens, pull network logs, and scan endpoints.
  • Education
  • Train developers and analysts on agent‑specific threats: prompt injection, tool abuse, and marketplace hygiene.

The Privacy Angle: What About Scanning My Code?

VirusTotal shares samples with participating security vendors and (depending on submission path) with the broader community of analysts. That’s a feature for threat hunting—but a risk if proprietary code or secrets are inadvertently uploaded.

Key considerations:

  • Don’t bundle secrets into skills. Use environment variables or vault references, not hardcoded keys.
  • Understand OpenClaw’s submission path: marketplace‑submitted builds should be scrubbed of sensitive environment artifacts.
  • For private, proprietary skills you cannot share widely, consider running an internal multi‑scanner stack and local sandboxes instead of uploading source or artifacts to public services.

Balancing safety with privacy is part of mature marketplace design. Expect OpenClaw to document how they handle sample submission scopes across public and private contexts.

How This Changes the Ecosystem

  • Raising the floor: A first‑mile scanner significantly reduces commodity malware throughput. This alone will cut incident volume.
  • Signaling maturity: Integrations with established security infrastructure (like VT) build enterprise confidence in AI marketplaces.
  • Forcing attacker evolution: Expect a pivot from crude stealers to more subtle prompt‑ and logic‑layer abuses, dependency hijacking, and brand impersonation.
  • Regulatory alignment: As regulators tilt toward “duty of care” for AI distributors, visible controls like multi‑engine scanning and transparency reports will become table stakes.
  • Competitive pressure: Other agent hubs and plugin stores will likely follow suit, adding signing, attestations, and runtime isolation to stay credible.

What We’ll Be Watching

  • Block rate and dwell time
  • How many submissions are blocked at upload? How quickly are live malicious skills detected and removed?
  • False positives
  • Are benign tools being flagged? How responsive is the review pipeline?
  • Re‑scan coverage
  • Are all live skills re‑scanned daily? How are updates prioritized?
  • Publisher verification
  • Does ClawHub expand identity checks and MFA enforcement for maintainers?
  • Prompt injection mitigations
  • We expect stronger content governance, retrieval allowlists, and model‑side policies to catch non‑code attacks.
  • Dependency pinning
  • Are marketplace policies adopting SBOMs, hash pinning, and dependency firewalling?

Practical Checklist for Skill Authors

Help the platform help you—and your users:

  • No secrets in code. Ever.
  • Provide a complete SBOM and pin dependencies by hash.
  • Scope permissions narrowly and document why you need them.
  • Add a SECURITY.md with reporting channels and hardening tips.
  • Sign releases and use reproducible builds where possible.
  • Test for prompt injection and unsafe tool use; document limitations.
  • Respond quickly to abuse reports and maintain a changelog for transparency.

Key Takeaways

OpenClaw’s partnership with VirusTotal is a smart, timely move that will measurably reduce the flow of malicious skills into ClawHub. Automated pre‑approval scans and daily re‑checks create a powerful gate against known malware and commodity threats. But scanning alone won’t stop prompt injection, logic‑layer abuse, or clever supply‑chain pivots.

If you rely on agents, treat this announcement as your cue to harden everything around the marketplace: enforce least privilege, sandbox skills, pin dependencies, control egress, and monitor for unusual behavior. The agent era is here. With sensible layers of defense, it doesn’t have to be an unacceptable liability.

Frequently Asked Questions

Q: What exactly did OpenClaw announce?
A: OpenClaw is integrating Google’s VirusTotal into the ClawHub skills marketplace. All new skill submissions are scanned before approval; malicious ones are blocked, suspicious ones are flagged for review. Active skills are re‑scanned daily to catch late detections. Source: The Hacker News.

Q: Will VirusTotal scanning stop prompt injection attacks?
A: No. VT focuses on malware and suspicious behavior in files/URLs. Prompt injection is a content‑layer attack that manipulates model behavior without necessarily containing malware. Mitigations include retrieval allowlists, content sanitization, and policies aligned with the OWASP LLM Top 10.

Q: What is “ClawHavoc”?
A: A campaign documented by researchers in which 341 malicious ClawHub skills posed as crypto and YouTube utilities but installed keyloggers and the Atomic macOS Stealer (AMOS), stealing wallets, browser data, and credentials. It underscores why marketplace screening is essential.

Q: Are my API keys at risk if I installed questionable skills?
A: Potentially. If you used unvetted skills recently, rotate API keys, OAuth tokens, and any credentials those agents could access. Move secrets to a vault, enforce least privilege, and review logs for unusual access.

Q: Does this affect self‑hosted OpenClaw instances?
A: The VirusTotal integration targets the ClawHub marketplace workflow, but self‑hosters should still adopt local multi‑scanner checks, sandbox execution, dependency pinning, and strict egress controls. Consider integrating your CI/CD with multiple scanners and enabling read‑only filesystems for agent runtimes.

Q: How does this compare to app stores and package registries?
A: It’s similar in spirit to mobile app stores and registries like npm that run automated scans and enforce policy. The difference: AI agents also face prompt‑ and data‑layer threats that code scanners won’t catch, so additional controls (memory boundaries, permission prompts, retrieval allowlists) are essential.

Q: Will my proprietary code be uploaded to VirusTotal?
A: Marketplace submission flows vary. VirusTotal shares samples with its security community under certain conditions, which is great for detection but risky for proprietary IP. Authors should avoid embedding secrets in code and review platform documentation on submission privacy. Enterprises with sensitive code should consider local scanning alternatives.

Q: Where can I learn more about agent‑focused threat modeling?
A: Start with OWASP’s LLM Top 10 and MITRE ATLAS for adversary behaviors in AI systems: – OWASP LLM Top 10: https://owasp.org/www-project-top-10-for-large-language-model-applications/ – MITRE ATLAS: https://atlas.mitre.org

Q: Who else is reporting on these threats?
A: The initial context comes from The Hacker News. Broader trend analysis and threat intel appear regularly on vendor blogs such as Trend Micro Research and internet‑wide exposure studies from Censys.

Final takeaway: Malware scanning is necessary but not sufficient. OpenClaw’s VirusTotal integration raises the floor for everyone—but your posture, from permissioning to sandboxing and monitoring, decides whether a malicious skill becomes a headline or a nonevent.

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InnoVirtuoso

Hello there! I'm passionate content writer navigating the digital landscape. With a deep love for words and an insatiable curiosity about technology.

With 10 years of experience in IT field, I write mostly about emerging tech, sharing news, informational articles and covering other topics I find interesting.

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