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Is browser-use/browser-use safe?

What browser-use/browser-use does

Browser Use lets AI agents control a web browser to complete tasks, and is offered as an open-source Python library, a CLI and a hosted cloud service. It is published in the browser-use/browser-use repository. The library drives a local browser, can reuse a Chrome profile through Browser.from_system_chrome(), and calls an LLM provider with your API key, for example OPENAI_API_KEY, or BROWSER_USE_API_KEY for Browser Use's own services. Before installing, run agents in a separate browser profile rather than your everyday one, because a reused profile carries your cookies and signed-in sessions.

Some risk - review before installing
Notable — review in context (a capability is not a malicious indicator):
  • Remote pipe-to-shell execution
  • Agent instructions download code and run it
  • Python shell/command execution

What to do: Read the findings below before installing: each one opens the exact line of code it was found on.

browser-use/browser-use is a GitHub repository analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators, though 2 risky constructs are reported for review. It can: dynamic code execution, filesystem read, filesystem write, mcp tools detected, network egress and shell execution — capabilities are what the code can do, not a verdict on intent. Risk score 30/100 (medium).

browser-use 1.0.4

GitHub repository, read as a PyPI package · https://github.com/browser-use/browser-use
MEDIUM
30
/ 100 risk score
Snapshot · scanned Nov 13, 2026 · browser-use@1.0.4 · engine 1.1.0 / ruleset 100

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Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of browser-use/browser-use's authors. Report a false positive.

Capabilities — what this component can do (not a risk score):
dynamic code executionfilesystem readfilesystem writemcp tools detectednetwork egressshell execution

Behavioral traits

How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.

Tool surface
Tool Usage
Execution authority
Tool Access Control / Direct Tool Access
Filesystem reach
Tool Execution Context
Network egress
Interaction & Communication / Direct Communication
Supply-chain provenance risk
General Protections / Supply Chain

Findings (9)

CapabilityPython dynamic code executionnot scored · severity highST-DYN-PY

The code turns strings into live code at runtime (eval / new Function / exec).

exec(_NAMESPACE_IMPORTS, ns)
exec('from browser_harness.helpers import *', ns)
tree = compile(code, f'<cell {n}>', 'exec', flags=ast.PyCF_ONLY_AST | flags)
return compile(tree, f'<cell {n}>', 'exec', flags=flags)
return loop.run_until_complete(eval(code_obj, ns))
return exec(code_obj, ns)
obj = compile(msg['code'], '<finish>', 'eval', flags=ast.PyCF_ALLOW_TOP_LEVEL_AWAIT)
value = _run(obj, ns, loop) if obj.co_flags & inspect.CO_COROUTINE else eval(obj, ns)

Why it matters: If those strings aren't fixed and trusted, they become a way to run arbitrary code.

Fix: Avoid evaluating dynamically constructed code; if unavoidable, ensure the input is a trusted constant and never derived from external data.

CapabilityDangerous MCP tool capabilitynot scored · severity highST-MCP-DANGEROUS-TOOL

An MCP tool exposes a powerful capability (files, shell, network, browser, or credentials).

types.Tool(
			name='browser_exec',
types.Tool(
				name='browser_exec',
types.Tool(
				name='browser_screenshot',
types.Tool(
				name='browser_login',

Why it matters: Wired into an agent, these grant it real access to your machine — confirm each is required.

Fix: Confirm each powerful tool is required and constrained; broad MCP tools (shell/filesystem/network) grant an agent significant host access.

HIGHRemote pipe-to-shell executionST-SHELL-PIPE-EXEC

A remotely fetched payload is piped straight into a shell (e.g. `curl ... | bash`). The component runs code downloaded at runtime, which is unreviewable and a common second-stage delivery vector.

curl -LsSf https://astral.sh/uv/install.sh | sh

Fix: Download to a file, inspect it, and run a pinned/verified copy instead of piping a network response directly into a shell.

CapabilityPython shell/command executionnot scored · severity highST-SHELL-PY

The component can run operating-system commands or spawn processes.

self.proc = subprocess.Popen(
					[binary, *args],
					stdin=subprocess.DEVNULL,
					stdout=subprocess.DEVNULL,
					stderr=err,
					start_new_session=sys.platform != 'win32',  # its own process group: _kill reaches every helper
					cr …
return subprocess.Popen(
			[sys.executable, '-P', '-c', WATCHDOG, *args],
			env={**os.environ, 'BU_CLEANUP_BROWSER_ID': cloud_id},
			stdin=subprocess.PIPE,
			stdout=subprocess.DEVNULL,
			stderr=subprocess.DEVNULL,
			start_new_session= …
result = subprocess.run(cmd)
r = subprocess.run(
				cmd,
				stdin=subprocess.DEVNULL,
				capture_output=True,
				text=True,
				errors='replace',
				env=env,
				timeout=INSTALL_TIMEOUT_S,
			)
subprocess.Popen(command, stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
subprocess.Popen(
					args,
					env=env,
					stdin=subprocess.PIPE,
					stdout=subprocess.DEVNULL,
					stderr=subprocess.DEVNULL,
					**detach,
				)
subprocess.run(['taskkill', '/F', '/T', '/PID', str(pid)], capture_output=True)
self.proc = subprocess.Popen(  # noqa: ASYNC220 - asyncio forks synchronously too; see self.proc
				# -P: the workspace is not sys.path[0]: a json.py there must not shadow the stdlib (worker.py appends it)
				[sys.executable, '-P', '-m', …
probe = subprocess.run([uv, 'tool', 'dir'], capture_output=True, text=True)
result = subprocess.run([uv, *args])
subprocess.Popen([sys.executable, '-I', '-c', EXIT_SENDER, f'{POSTHOG_HOST}/batch/', *files], **kw)

Why it matters: Powerful and often legitimate — confirm the commands aren't built from untrusted input.

Fix: Confirm the command and its arguments are fully controlled and not derived from untrusted input; avoid shell=True.

CapabilityPython filesystem readnot scored · severity mediumST-FS-PY-READ

The component reads files from disk.

value = json.loads((self.repl.state / 'partial.json').read_text(encoding='utf-8'))['value']
log = download_records(log.read_text(encoding='utf-8').splitlines())
self._agent_tabs.update(Path(self._tabs_file).read_text().split())
self._agent_tabs.update(Path(tabs_file).read_text().split())  # a follow-up run's sweep still knows them
lines = log.read_text(encoding='utf-8').split('\n')[:-1]
port, path = (base / 'DevToolsActivePort').read_text(encoding='utf-8', errors='replace').split()[:2]
port = (base / 'DevToolsActivePort').read_text(errors='replace').split()[0]
with open(real, 'rb') as f:
cache = json.loads((root / 'Local State').read_text(encoding='utf-8', errors='replace'))['profile']['info_cache']
lines = (user_data_dir / 'DevToolsActivePort').read_text(encoding='utf-8', errors='replace').splitlines()
if m := re.search(rb'DevTools listening on (ws://\S+)', log.read_bytes()):
tail = log.read_bytes()[-600:].decode(errors='replace').strip()
profiles = list((json.loads(path.read_text(encoding='utf-8')).get('browser_profile') or {}).values())
or 'docker' in Path('/proc/1/cgroup').read_text(encoding='utf-8', errors='replace').lower()
return _marker(name).read_text().strip()
return open(file, mode, buffering, encoding, *args, **kwargs)
with open(path, 'rb') as f:
files = [Path(p).read_bytes() for p in paths]
saved = json.loads(self.path.read_text(encoding='utf-8'))
with open(path, encoding='utf-8', errors='replace') as f:
for line in (STATE / 'downloads.jsonl').read_text(encoding='utf-8').splitlines():
return _add_image(p.read_bytes(), f'image/{ext}')
with open(path, mode, encoding='utf-8', newline='') as out:  # Windows: the cell already wrote \r\n; no \r\r\n
with open(out_path, encoding='utf-8', errors='replace') as f:
return skill_path.read_text(encoding='utf-8')

Why it matters: Usually legitimate, but worth confirming it can't be steered into reading sensitive files.

Fix: Confirm which files are read and that paths cannot be influenced by untrusted input to reach sensitive locations.

CapabilityPython filesystem write/deletenot scored · severity mediumST-FS-PY-WRITE

The component writes or deletes files on disk.

path.write_text(json.dumps(redact(archive, s.repl.secrets), ensure_ascii=False), encoding='utf-8')
f = open(path, 'xb')  # - exclusive create: two sessions never write the same file
shutil.copy2(root / 'Local State', dest / 'Local State')
shutil.copytree(root / directory, dest / directory, ignore=SKIP_COPY, symlinks=True, dirs_exist_ok=True)
with open(d / OWNER, 'r+b') as f:
shutil.rmtree(d, ignore_errors=True)
self._owner = open(self.tmp / OWNER, 'wb')  # locked while this process lives: sweep_stale_dirs skips the dir
with open(log, 'wb') as err:
shutil.rmtree(self.tmp, ignore_errors=True)
shutil.rmtree(udd, ignore_errors=True)
shutil.rmtree(_own_chromium_dir(), ignore_errors=True)
tmp.write_text(json.dumps(data), encoding='utf-8')
log = open(self.state / 'worker.log', 'ab')  # noqa: ASYNC230 - handed to the child process
with contextlib.suppress(OSError), open(STATE / 'downloads.jsonl', 'a', encoding='utf-8') as f:
with contextlib.suppress(OSError), open(tabs_file, 'a') as f:
path.write_bytes(base64.b64decode(r['data']))
tmp.write_text(text, encoding='utf-8')
output_path.write_text(text, encoding='utf-8')
tmp.write_text(new_device_id, encoding='utf-8')
tmp.write_text(json.dumps({**marker, 'props': props()}, default=str), encoding='utf-8')
cache.write_text(json.dumps({'latest': latest, 'checked_at': time.time()}), encoding='utf-8')
output_path.write_text(expected, encoding='utf-8')

Why it matters: Usually legitimate, but worth confirming the paths can't be controlled by untrusted input.

Fix: Confirm which files are written/deleted and that paths cannot be influenced by untrusted input.

CapabilityPython network egressnot scored · severity mediumST-NET-PY

The component makes outbound network requests.

req = urllib.request.Request(
		f'{CLOUD_API}{path}',
		method=method,
		data=json.dumps(body).encode() if body is not None else None,
		headers={'X-Browser-Use-API-Key': browser_use_api_key(), 'Content-Type': 'application/json'},
	)
with urllib.request.urlopen(url, timeout=min(30.0, left), context=tls_context()) as r:  # the timeout bounds each read
return urllib.parse.urlsplit(url)._replace(query='', fragment='').geturl()
items = _cloud(f'/profiles?pageSize=100&query={urllib.parse.quote(profile)}').get('items', [])
u = urllib.parse.urlsplit(cdp_url)  # a token in the query stays after /json/version
with urllib.request.urlopen(
		u._replace(path=u.path.rstrip('/') + '/json/version').geturl(), timeout=30, context=tls_context()
	) as r:
u = urllib.parse.urlsplit(cdp_url)
local = urllib.request.build_opener(urllib.request.ProxyHandler({}))  # 127.0.0.1 itself, never an HTTP proxy
return urllib.parse.urlsplit(ws).path == path
import urllib.request
request = urllib.request.Request(f'{auth.auth_base()}/api/v4/browsers?pageSize=1', headers={'X-Browser-Use-API-Key': key})
import urllib.request
opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))  # an HTTP_PROXY never sees localhost
u = urllib.parse.urlsplit(url)
if urllib.request.getproxies().get(u.scheme) and not _loopback(host) and not urllib.request.proxy_bypass(host):
request = urllib.request.Request(url, headers={'Authorization': f'Bearer {key}'})
with urlopen_keyed(urllib.request.Request(url, headers=headers), PREFLIGHT_TIMEOUT_S):
self.json_pages.add(urllib.parse.urlsplit(params['frame'].get('url') or '')._replace(query='').geturl())
return urllib.request.build_opener(CheckedRedirects, TLSHandler)

Why it matters: Usually legitimate, but confirm the destinations are expected and no sensitive data leaves.

Fix: Confirm the destination hosts are expected and that no sensitive data is sent off-host.

MEDIUMAgent instructions download code and run itST-SKILL-FETCH-EXEC

An instruction file the agent follows (a skill, subagent, command or project instructions) tells it to download a script and run it, for example `curl ... | bash`. The agent runs whatever that host serves when it follows the instruction, which this scan cannot see; an allowed-tools list that admits the shell lets it run without asking. (2 occurrence(s) shown as evidence).

allowed-tools: Bash, Read, Task
command -v uv || curl -LsSf https://astral.sh/uv/install.sh | sh   # the uv installer, only if missing

Fix: Read what the URL serves before letting an agent follow this instruction, or replace it with a pinned package install.

CapabilityMCP tool surface detectednot scored · severity lowST-MCP-DETECTED

An MCP tool surface (manifest or tool definitions) was found.

server.add_request_handler('tools/list', types.PaginatedRequestParams, list_tools)
server.add_request_handler('tools/call', types.CallToolRequestParams, call_tool)
self.server.add_request_handler('tools/list', types.PaginatedRequestParams, handle_list_tools)
self.server.add_request_handler('tools/call', types.CallToolRequestParams, handle_call_tool)
types.Tool(
			name='browser_exec',
types.Tool(
				name='browser_exec',

Why it matters: Just context — review which tools it offers and their permissions.

Fix: Review the declared MCP tools and their permissions.

How attackers abuse these capabilities

Interactive labs on the attack class behind the rules above. They show the technique, not anything found in browser-use/browser-use.

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