Threats Tagged 'openclaw'

Between February and May 2026, researchers identified five malicious skills on ClawHub, OpenClaw's AI agent marketplace, that evaded detection by VirusTotal and ClawScan. The threats included two macOS infostealers communicating with command-and-control infrastructure, one skill using file padding to bypass scanner thresholds, and two novel agentic threats exploiting the AI supply chain for financial gain. The infostealers delivered payloads including AMOS malware through Base64-encoded droppers and paste-site redirects. One skill implemented runtime affiliate injection by forcing agents to recommend products through malicious referral links, while another orchestrated a front-running scheme using coordinated AI agents to manipulate cryptocurrency token launches. These attacks demonstrate how malicious actors exploit semantic instruction hijacking and the lack of isolation between skill logic and agent authority to compromise AI agent ecosystems.

Threat actors are actively exploiting AI distribution platforms like Hugging Face and ClawHub to deliver malware by embedding malicious code within models, datasets, and agent extensions. Over 575 malicious skills across 13 developer accounts were identified in the OpenClaw ecosystem, targeting Windows and macOS with trojans, cryptominers, and AMOS stealer. Attackers abuse trust relationships between users and AI platforms through indirect prompt injection, where hidden instructions cause AI agents to execute malicious actions on behalf of users. Trojanized skills masquerade as legitimate tools while instructing users to execute encoded commands or install hidden malicious dependencies. On Hugging Face, repositories host payloads within multistep infection chains disguised as legitimate applications. These campaigns employ social engineering, obfuscation, encryption, in-memory execution, process injection, and persistence techniques to evade detection while establishing covert command-and-control communica...

In March 2026, threat actors weaponized the OpenClaw AI agent framework by publishing a deceptive "DeepSeek-Claw" skill. This skill embedded malicious installation instructions designed to trick AI agents and developers into executing hidden payloads. On Windows systems, a PowerShell command downloads an MSI package containing a legitimate signed GoToMeeting executable that sideloads a malicious DLL. This loader patches ETW and AMSI for evasion, then decrypts and executes Remcos RAT using TEA encryption, enabling remote access and data theft including keylogging and cookie stealing. An alternate execution path for macOS and Linux delivers GhostLoader through obfuscated Node.js scripts, harvesting credentials via fake sudo prompts and exfiltrating SSH keys, cryptocurrency wallets, and cloud API tokens. This campaign represents an emerging threat vector exploiting autonomous AI workflows and developer trust in open-source frameworks.

Threat actors are exploiting AI agent skill formats as a novel attack vector, using convincingly packaged OpenClaw skills to distribute malicious payloads. The latest campaign employs pure social engineering, with skills containing no malicious code themselves but instead tricking users into downloading Windows binaries. The attack leverages a fake GitHub infrastructure hosting GachiLoader, which delivers Rhadamanthys infostealer through fileless injection. The operation uses two delivery mechanisms: Node.js Single Executable Applications and an Electron dropper, both converging on the same payload. GachiLoader employs sophisticated evasion techniques including anti-VM checks, sandbox detection, and privilege escalation, while using a Polygon blockchain smart contract as its C2 resolver for enhanced persistence and obfuscation.

A new campaign exploits OpenClaw skills to distribute the Atomic MacOS Stealer (AMOS). This evolution in supply chain attacks manipulates AI agentic workflows to install malware. The campaign spans multiple repositories with hundreds of malicious skills uploaded to ClawHub and SkillsMP. The infection chain begins with a seemingly harmless SKILL.md file that installs a prerequisite, leading to the download of a Mach-O universal binary. This AMOS variant steals extensive data, including credentials, browser data, cryptocurrency wallets, and various user documents. It lacks system persistence but expands its reach by exfiltrating Apple and KeePass keychains. The malware uses sophisticated encryption schemes and targets multiple browsers and cryptocurrency wallets.

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A massive malware campaign dubbed ClawHavoc has been uncovered in the ClawHub marketplace, targeting OpenClaw bots and their users. An AI bot named Alex, working with security researcher Oren Yomtov, discovered 341 malicious skills, including 335 from a single campaign. The malware, identified as Atomic Stealer (AMOS), uses sophisticated techniques to evade detection and steal sensitive data. The attack exploits users' trust in AI assistants, potentially compromising personal and financial information. In response, a new tool called Clawdex has been developed to help bots and users scan for malicious skills before installation.

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Almost 400 fake crypto trading add-ons in the Moltbot/OpenClaw AI assistant project have been discovered, potentially leading users to install information-stealing malware. These add-ons, known as skills, masquerade as cryptocurrency trading automation tools and target various platforms. The malicious skills share the same command-and-control infrastructure and use social engineering to convince users to execute commands that steal crypto assets. The supply chain attack relies on social engineering and lacks security review in the skills publication process. Security experts warn about the inherent risks of endpoint-native AI agents and emphasize the need for proper security controls and architectural design considerations.

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