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Security audit

Weibo TrendNote AI PC

Security checks for vulnerabilities and agentic risk

Overview

This skill appears to do what it says: fetch Weibo trends, summarize them locally, and write them to Obsidian, with scheduled runs only as an explicit option.

Install only if you want a Windows-specific Weibo-to-Obsidian automation that writes under C:\Users\Intel and appends to your Obsidian vault. Review env.ps1 and any SUMMARIZE_BIN, NOTESMD_BIN, or OPENCLAW_BIN values before running, because those settings control local programs the skill executes. Enable install-crons only if you want recurring background runs every 5 and 10 minutes.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
  • Behavioral ASTexec() Call, eval() Call, Dynamic Import
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
  • MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Findings (13)

Tainted flow: 'headers' from os.environ.get (line 76, credential/environment) → requests.get (network output)

Critical
Category
Data Flow
Confidence
90% confidence
Finding

Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.

Content

Scanner excerpt · scripts/fetch_weibo_hot.py (reported line 83)May include surrounding context.

python
last_err = None
    for attempt in range(MAX_RETRIES):
        try:
            response = requests.get(API_URL, headers=headers, timeout=10)
            response.raise_for_status()

            data = response.json()

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

The skill description claims behavior such as local summarization, Obsidian note updates, and optional recurring automation, but the analysis indicates those behaviors are absent while other fixed local state handling exists. This kind of mismatch is security-relevant because users and reviewers may approve the skill based on inaccurate expectations, allowing hidden or undocumented behavior to evade scrutiny.

Content

No source excerpt is available for this finding.

Env Variable Harvesting

High
Category
Data Exfiltration
Confidence
60% confidence
Finding

Code enumerates, copies, or searches environment variables for secrets. Bulk environment access can collect credentials unrelated to the skill's stated purpose.

Content

Scanner excerpt · scripts/flush_queue_to_obsidian.py (reported line 104)May include surrounding context.

python
if VAULT_NAME: cmd.extend(["--vault", VAULT_NAME])

    # Build env with APPDATA set for notesmd-cli
    env = os.environ.copy()
    env["APPDATA"] = r"C:\Users\Intel\AppData\Roaming"
    env["USERPROFILE"] = r"C:\Users\Intel"
    env["HOME"] = r"C:\Users\Intel"

Undeclared Tool Scope

Medium
Category
MCP Least Privilege
Confidence
94% confidence
Finding

The skill declares no explicit tool scope even though its documented behavior includes shell execution, network access, environment loading, and local file writes. This weakens least-privilege controls and makes it harder for a caller or platform to constrain the skill if the runner script is modified, compromised, or behaves unexpectedly.

Content

No source excerpt is available for this finding.

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/flush_queue_to_obsidian.py (reported line 110)May include surrounding context.

python
env["HOME"] = r"C:\Users\Intel"

    try:
        r = subprocess.run(cmd, capture_output=True, text=True, timeout=30,
                           encoding="utf-8", errors="replace", env=env)
        if r.returncode != 0:
            print(f"[notesmd] CLI error (code {r.returncode}): {(r.stderr or '')[:500]}", file=sys.stderr)

Tainted flow: 'cmd' from os.environ.get (line 100, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
88% confidence
Finding

The executable path comes from NOTESMD_BIN, which is sourced from environment variables and then executed via subprocess.run. If an attacker can influence the environment in which this skill runs, they can point NOTESMD_BIN to an arbitrary binary and gain code execution under the agent's privileges.

Content

Scanner excerpt · scripts/flush_queue_to_obsidian.py (reported line 110)May include surrounding context.

python
env["HOME"] = r"C:\Users\Intel"

    try:
        r = subprocess.run(cmd, capture_output=True, text=True, timeout=30,
                           encoding="utf-8", errors="replace", env=env)
        if r.returncode != 0:
            print(f"[notesmd] CLI error (code {r.returncode}): {(r.stderr or '')[:500]}", file=sys.stderr)

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/skill_runner.py (reported line 82)May include surrounding context.

python
script_path = Path(__file__).resolve().parent / script_name
    cmd = [python_executable(), str(script_path), *args]
    print(f"[runner] exec: {' '.join(cmd)}")
    completed = subprocess.run(cmd)
    return completed.returncode

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/skill_runner.py (reported line 151)May include surrounding context.

python
def openclaw_run(*args: str) -> subprocess.CompletedProcess:
    cmd = [resolve_openclaw_bin(), *args]
    print(f"[runner] exec: {' '.join(cmd)}")
    return subprocess.run(cmd)


def install_crons() -> int:

Context-Inappropriate Capability

Medium
Category
Not specified by scanner
Confidence
83% confidence
Finding

The skill can install persistent scheduled tasks that repeatedly execute local scripts, which expands its capability from a one-time utility into ongoing autonomous execution. Even if intended for convenience, persistence increases risk because a user may not fully understand that the skill will continue running and can repeatedly process or write data after the initial invocation.

Content

No source excerpt is available for this finding.

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/skill_runner.py (reported line 171)May include surrounding context.

python
"weibo-trendnote-aipc-obsidian-flush-10m",
    ]
    for name in stale_names:
        subprocess.run([oc, "cron", "remove", "--name", name], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)

    result1 = openclaw_run(
        "cron", "add",

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The subprocess command hard-codes --lang zh, which imposes a specific language on the generated summary. The file does not offer a user-selectable language option or explain a justified region-specific constraint, so this appears to violate the language/locale policy criteria.

Content

No source excerpt is available for this finding.

subprocess module call

Medium
Category
Dangerous Code Execution
Confidence
70% confidence
Finding

subprocess module calls execute external commands. Without careful input validation, this enables command injection.

Content

Scanner excerpt · scripts/summarize_weibo_hot.py (reported line 59)May include surrounding context.

python
print(f"[summarize] Running: {' '.join(cmd)}")
    print(f"[summarize] SUMMARIZE_BIN = {SUMMARIZE_BIN}")
    try:
        r = subprocess.run(cmd, capture_output=True, text=True,
                           timeout=SUMMARIZE_TIMEOUT, encoding="utf-8", errors="replace")
        if r.returncode == 0 and r.stdout.strip():
            return r.stdout.strip()

Tainted flow: 'cmd' from os.environ.get (line 53, credential/environment) → subprocess.run (code execution)

Medium
Category
Data Flow
Confidence
97% confidence
Finding

The executable path comes from the SUMMARIZE_BIN environment variable and is passed directly to subprocess.run. Any attacker who can influence the environment or the env.ps1 loaded by the runner can replace the summarizer with an arbitrary program, leading to code execution under the privileges of this skill.

Content

Scanner excerpt · scripts/summarize_weibo_hot.py (reported line 59)May include surrounding context.

python
print(f"[summarize] Running: {' '.join(cmd)}")
    print(f"[summarize] SUMMARIZE_BIN = {SUMMARIZE_BIN}")
    try:
        r = subprocess.run(cmd, capture_output=True, text=True,
                           timeout=SUMMARIZE_TIMEOUT, encoding="utf-8", errors="replace")
        if r.returncode == 0 and r.stdout.strip():
            return r.stdout.strip()

Static analysis

No suspicious patterns detected.