Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
DLT大乐透预测 v4.0
v4.0.0基于2853期历史数据，结合五池加权采样与博弈论遗传算法，生成符合多重约束的DLT复式及单式投注号码预测。
⭐ 0· 49·0 current·0 all-time
by@lovensr
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
The name/description (DLT lottery prediction) matches the provided files and runtime instructions. The codebase contains sampler, fusion, constraint, and optimizer modules appropriate for generating and backtesting lottery combinations. No unrelated credentials, system paths, or external services are requested in the manifest or SKILL.md.
Instruction Scope
SKILL.md instructs local import and running of the DLTFusionComplete API (predict and backtest). The instructions reference inserting a path to the skill workspace (typical for local skill usage). The visible code snippets operate on local historical draws and perform CPU-bound computations (sampling, GA, scoring). However multiple files were truncated in the provided package listing — those omitted files should be reviewed for any instructions that read unrelated user files, access environment variables, or make network requests.
Install Mechanism
No install spec is present (instruction-only install), and the package ships source files that will run under the agent's Python environment. There are no downloads from external URLs, no brew/npm installs, and no extract operations declared.
Credentials
The skill declares no required environment variables, credentials, or config paths. The shown code operates on in-repo/local historical data and algorithmic logic; there is no apparent need for secrets or external service credentials.
Persistence & Privilege
The skill does not request always:true and uses default invocation semantics. There are no instructions in SKILL.md to modify other skills or system-wide agent settings. The package manipulates sys.path inside its code to ensure local imports, which is common for in-repo Python packages.
Assessment
This package appears coherent for its stated purpose and does not request secrets or external installs. Before running it: (1) review the remaining truncated files for any network calls (requests, urllib, sockets), subprocess usage (os.system, subprocess), or reading of arbitrary filesystem paths; (2) run the code in a sandbox or isolated environment if you are unsure of origin; (3) inspect any included data files (dlt_skill_config.json or historical draws) to confirm they are benign; (4) be aware this is a prediction/gambling tool — it may have legal or ethical considerations in your jurisdiction. If you want, I can scan the omitted files for network I/O, subprocess invocation, or credential access.Like a lobster shell, security has layers — review code before you run it.
chinese-lotteryvk975ne4gaw1f4wq8wvjd3qj2t584am6qdltvk975ne4gaw1f4wq8wvjd3qj2t584am6qgame-theoryvk975ne4gaw1f4wq8wvjd3qj2t584am6qgenetic-algorithmvk975ne4gaw1f4wq8wvjd3qj2t584am6qlatestvk975ne4gaw1f4wq8wvjd3qj2t584am6qlotteryvk975ne4gaw1f4wq8wvjd3qj2t584am6qpredictionvk975ne4gaw1f4wq8wvjd3qj2t584am6q
License
MIT-0
Free to use, modify, and redistribute. No attribution required.