Openclaw: >> Openclaw >> 2026.1.52 Security Vulnerabilities
OpenClaw is a personal AI assistant. Prior to 2026.2.14, browser-facing localhost mutation routes accepted cross-origin browser requests without explicit Origin/Referer validation. Loopback binding reduces remote exposure but does not prevent browser-initiated requests from malicious origins. A malicious website can trigger unauthorized state changes against a victim's local OpenClaw browser control plane (for example opening tabs, starting/stopping the browser, mutating storage/cookies) if the browser control service is reachable on loopback in the victim's browser context. Starting in version 2026.2.14, mutating HTTP methods (POST/PUT/PATCH/DELETE) are rejected when the request indicates a non-loopback Origin/Referer (or `Sec-Fetch-Site: cross-site`). Other mitigations include enabling browser control auth (token/password) and avoid running with auth disabled.
CVSS Score
7.1
EPSS Score
0.0
Published
2026-02-19
OpenClaw is a personal AI assistant. In versions 2026.1.30 and below, if channels.telegram.webhookSecret is not set when in Telegram webhook mode, OpenClaw may accept webhook HTTP requests without verifying Telegram’s secret token header. In deployments where the webhook endpoint is reachable by an attacker, this can allow forged Telegram updates (for example spoofing message.from.id). If an attacker can reach the webhook endpoint, they may be able to send forged updates that are processed as if they came from Telegram. Depending on enabled commands/tools and configuration, this could lead to unintended bot actions. Note: Telegram webhook mode is not enabled by default. It is enabled only when `channels.telegram.webhookUrl` is configured. This issue has been fixed in version 2026.2.1.
CVSS Score
7.5
EPSS Score
0.0
Published
2026-02-19
OpenClaw (formerly Clawdbot) is a personal AI assistant users run on their own devices. In versions 2026.2.2 and below, when the Slack integration is enabled, channel metadata (topic/description) can be incorporated into the model's system prompt. Prompt injection is a documented risk for LLM-driven systems. This issue increases the injection surface by allowing untrusted Slack channel metadata to be treated as higher-trust system input. This issue has been fixed in version 2026.2.3.
CVSS Score
3.7
EPSS Score
0.0
Published
2026-02-19
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