T09 · Insecure Skill Coding Practices
Error
- Location
scripts/run.py:29- Finding
Unredacted Health and Identity Data Is Transmitted to an External LLM Service
- Content
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Any: data = json.dumps(payload, ensure_ascii=False).encode("utf-8") req = urllib.request.Request( url=url, data=data, method="POST", headers={"Content-Type": "application/json", **headers}, ) try: ctx = urllib.request.urlopen(req) if not timeout else urllib.request.urlopen(req, timeout=timeout) ``` ```python def run_health_record(health_info: str, llm, output_path: str = "") -> int: prompt = f"""Please extract a structured resident health record from the following resident health information. [Resident health information] {health_info.strip()} Return JSON and a summary according to the required format. Use null for information that was not provided and do not fabricate information.""" print("Extracting resident health record information...") result = llm([sys_msg(SYSTEM_PROMPT), user_msg(prompt)]) ``` ```python try: health_info = load_input(input_path, args.encoding) except Exception as e: print(f"Failed to read input file: {e}", file=sys.stderr) return 1 llm = make_llm_caller(args.appkey, args.base, args.model, args.timeout) try: return run_health_record(health_info, llm, args.output) ``` ### Technical Analysis The application loads the complete contents of the supplied health-record file and embeds them directly into an LLM request. It does not locally detect, redact, tokenize, or reject direct identifiers such as names, government identification numbers, telephone numbers, or addresses. This conflicts with the privacy statements in `SKILL.md`, which state that direct identifiers are not processed and that strict de- ...[truncated 1384 chars]- Remediation
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