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cross-disciplinary-bridge-finder
Identifies collaboration opportunities across fields, finds experts in complementary disciplines, translates methodologies between scientific domains, and builds interdisciplinary research teams.
Legitimate cross-disciplinary research tool with no malicious behavior; minor doc-code mismatch on declared permissions but no security impact.
可以安装
This skill is safe to use. Consider updating SKILL.md to accurately reflect that only standard Python libraries are used (no shell access or file I/O tools required).
安全发现 2 项
| 严重性 | 安全发现 | 位置 |
|---|---|---|
| 低危 | Permission declaration mismatch 文档欺骗 | SKILL.md:4 |
| 低危 | Dependencies not version-pinned 供应链 | scripts/requirements.txt:1 |
| 资源类型 | 声明权限 | 推断权限 | 状态 | 证据 |
|---|---|---|---|---|
| 文件系统 | WRITE | NONE | ✓ 一致 | SKILL.md:4 declares 'Write' but main.py only uses pathlib.Path for DATA_DIR crea… |
| 命令执行 | WRITE | NONE | ✓ 一致 | SKILL.md:4 declares 'Bash' but main.py contains no subprocess, os.system, or any… |
| 网络访问 | NONE | NONE | — | No network requests found in code |
| 环境变量 | NONE | NONE | — | No os.environ access or credential harvesting |
目录结构
5 文件 · 44.3 KB · 1201 行 Python 1f · 1078L
Markdown 1f · 102L
Text 2f · 11L
JSON 1f · 10L
├─
▾
scripts
│ ├─
main.py
Python
│ └─
requirements.txt
Text
├─
requirements.txt
Text
├─
SKILL.md
Markdown
└─
tile.json
JSON
依赖分析 7 项
| 包名 | 版本 | 来源 | 已知漏洞 | 备注 |
|---|---|---|---|---|
networkx | >=2.8 | pip | 否 | Version not pinned with upper bound |
numpy | >=1.21 | pip | 否 | Version not pinned with upper bound |
pandas | >=1.3 | pip | 否 | Version not pinned with upper bound |
scikit-learn | >=1.0 | pip | 否 | Version not pinned with upper bound |
matplotlib | >=3.5 | pip | 否 | Version not pinned with upper bound |
seaborn | >=0.11 | pip | 否 | Version not pinned with upper bound |
openai | >=1.0 | pip | 否 | Imported but not actually used in code; version not pinned |
安全亮点
✓ No shell execution (no subprocess, os.system, or command injection)
✓ No network requests or data exfiltration
✓ No credential harvesting or sensitive file access (~/.ssh, ~/.aws, .env)
✓ No obfuscation techniques (no base64, eval, or anti-analysis)
✓ No reverse shell or C2 communication patterns
✓ Legitimate academic research tool with clear, understandable logic
✓ Uses well-established libraries (networkx, numpy, scikit-learn) with no custom dangerous code