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Security audit

AI通识课资深专家V8.2BNBU

Security checks for vulnerabilities and agentic risk

Overview

The skill is a mostly coherent AI teaching workflow, but installation and cloud-privacy controls need review before use.

Review this skill before installing in environments with sensitive student or institutional data. Use skip-ffmpeg or preinstall a trusted FFmpeg build where possible, avoid placing PII in intent or context fields, and only configure cloud endpoints/API keys you trust. Treat the zero-upload claims as aspirational until final-payload redaction and executable integrity checks are fixed.

Vulnerability Patterns
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
  • 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
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
Findings (2)

T03 · Remote Payload Retrieval and Execution

Error
Location
scripts/setup_resources.py:55
Finding

Unverified Third-Party FFmpeg Executable Is Downloaded and Executed During Bootstrap

Content
View full analysis
bool: """Run the executable with the supplied arguments and report success.""" for flag in flags: try: result = subprocess.run( [str(exe_path), flag], capture_output=True, timeout=15, ) if result.returncode == 0: return True except Exception: continue return False ``` ```python def _download_with_progress(url: str, dest: Path, timeout: int = DOWNLOAD_TIMEOUT) -> None: """Download URL to dest.""" log.info(f" Downloading: {url}") log.warn(f" Destination: {dest} (timeout {timeout}s)") old_timeout = socket.getdefaulttimeout() socket.setdefaulttimeout(timeout) try: urllib.request.urlretrieve(url, str(dest)) finally: socket.setdefaulttimeout(old_timeout) ``` ```python for url in FFMPEG_ZIP_URLS: try: _download_with_progress(url, zip_path) if zip_path.stat().st_size == 0: continue with zipfile.ZipFile(zip_path, "r") as zf: if _find_in_zip(zf, "ffmpeg.exe") and _find_in_zip(zf, "ffprobe.exe"): downloaded_ok = True break except Exception as e: log.warn(f"[ffmpeg] Current source failed: {e}") continue ``` ```python with zf.open(ffmpeg_zip_path) as src, open(ffmpeg_dest, "wb") as dst: shutil.copyfileobj(src, dst) with zf.open(ffprobe_zip_path) as src, open(ffprobe_dest, "wb") as dst: shutil ...[truncated 3421 chars]
Remediation
View remediation

T09 · Insecure Skill Coding Practices

Error
Location
scripts/edge_cloud_dispatch.py:427
Finding

Cloud Privacy Redaction Omits User-Controlled Intent and Context Fields

Content
View full analysis
tuple[dict, bool]: """Apply recursive PII redaction to abstract_data.""" abstract = request.get("abstract") or {} data = abstract.get("abstract_data") try: from pii_redactor import redact_abstract_data redacted, detected = redact_abstract_data(data) abstract["abstract_data"] = redacted abstract["pii_detected"] = detected request["abstract"] = abstract return request, detected except ImportError: return request, abstract.get("pii_detected", False) ``` ```python request, pii_detected = self._apply_pii_redaction(request) if pii_detected: request["abstract"]["pii_detected"] = False ``` The unredacted `intent` and `context` fields are then added directly to the external provider request: ```python def _v7_to_openai_request(request: dict) -> dict: """Convert the V7 request to OpenAI /chat/completions format.""" abstract = request.get("abstract") or {} intent = request.get("intent", "") context = abstract.get("context", "") system_msg = ( "You are an AI literacy teaching expert. V7 edge-cloud protocol v1.0.\n" f"Primary task: {abstract.get('task_type', '')}\n" "Return teaching recommendations based on abstract_data." ) user_msg = f"Intent: {intent}\nContext: {context}\nMetadata: {json.dumps(abstract.get('abstract_data', {}), ensure_ascii=False)[:8000]}" return { "model": os.environ.get("EDGE_CLOUD_MODEL", "gpt-4o-mini"), "messages": [ {"role": "system", "content": system_msg}, {"role": "user", "content": user_msg}, ], ...[truncated 4093 chars]
Remediation
View remediation
Vulnerability Patterns
  • Taint TrackingDirect Taint Flow, Variable-Mediated Taint Flow, Credential Exfiltration Chain
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (345)

Tainted flow: 'connect_timeout' from os.environ.get (line 743, credential/environment) → urllib.request.urlopen (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/edge_cloud_dispatch.py (reported line 782)May include surrounding context.

python
req = urllib.request.Request(url, data=payload, headers=headers, method="POST")

    try:
        with urllib.request.urlopen(req, timeout=connect_timeout) as resp:
            body = resp.read().decode("utf-8")
            provider_resp = json.loads(body)
    except socket.timeout as exc:

Tp4

High
Category
MCP Tool Poisoning
Confidence
98% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
93% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
92% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
97% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
95% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
98% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
97% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
97% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
96% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
97% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
97% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
99% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Tp4

High
Category
MCP Tool Poisoning
Confidence
94% confidence
Finding

Automatic environment setup, dependency installation, process re-execution, and manifest generation materially exceed what many users would infer from an 'AI literacy teaching expert' description. This can lead to unreviewed local changes and increased attack surface under misleadingly low-risk expectations.

Content

No source excerpt is available for this finding.

Static analysis

Detected: suspicious.destructive_delete_command, suspicious.dynamic_code_execution, suspicious.exposed_secret_literal

Documentation contains a destructive delete command without an explicit confirmation gate.

Warn
Code
suspicious.destructive_delete_command
Location
references/deployment-guide.md:1619

Dynamic code execution detected.

Critical
Code
suspicious.dynamic_code_execution
Location
support/p5.min.js:1

Dynamic code execution detected.

Critical
Code
suspicious.dynamic_code_execution
Location
support/p5.sound.min.js:2

File appears to expose a hardcoded API secret or token.

Critical
Code
suspicious.exposed_secret_literal
Location
references/deployment-guide.md:592