open-source
Fail
Audited by Gen Agent Trust Hub on Oct 23, 2026
Risk Level: HIGHREMOTE_CODE_EXECUTIONEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONDYNAMIC_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [REMOTE_CODE_EXECUTION]: Documentation in
references/quickstart.mdsuggests executing a remote shell script viacurl -fsSL https://browser-use.com/profile.sh | shto synchronize browser profiles with cloud infrastructure, which constitutes remote code execution from a non-whitelisted domain. - [EXTERNAL_DOWNLOADS]: The skill instructs users and agents to download and install multiple external Python packages, including
browser-use,lmnr, andopenlitfrom public registries, as seen inreferences/quickstart.mdandreferences/monitoring.md. - [COMMAND_EXECUTION]: The documentation provides examples of shell command execution, including the use of
subprocess.Popento launch browser instances with remote debugging enabled inreferences/examples.mdand the use ofuvxfor tool installation. - [DYNAMIC_EXECUTION]: The
browser-uselibrary documentation describes anevaluatemethod that allows for the execution of arbitrary JavaScript code within a browser page context, which is highlighted as a capability inreferences/actor.mdandreferences/tools.md. - [INDIRECT_PROMPT_INJECTION]: The skill describes a library designed to process untrusted web content (ingestion point) and provides it with extensive capabilities, creating a significant attack surface for indirect prompt injection.
- Ingestion points:
agent.run()andbrowser_navigateingest data from arbitrary, potentially attacker-controlled URLs (documented inreferences/agent.mdandreferences/integrations.md). - Boundary markers: The documentation does not specify the use of delimiters or 'ignore' instructions to separate untrusted web content from system prompts.
- Capability inventory: The documented capabilities include file system operations (
write_file,read_file), network interactions (browser navigation), and arbitrary JavaScript execution (evaluate). - Sanitization: While the documentation mentions a
sensitive_datadictionary for redacting credentials, it lacks comprehensive guidance on sanitizing or escaping untrusted content before it is processed by the LLM.
Recommendations
- AI detected serious security threats
Audit Metadata