Scan Report
15 /100
scienceclaw-local-files
Investigate local files (PDFs, FASTA, CSV, TSV, JSON, TXT) using ScienceClaw's multi-agent science engine
Documentation-only skill describing a scientific file analysis tool; no executable code present to verify actual behavior.
Safe to install
Review the actual scienceclaw-post binary for security compliance before deployment. Ensure network exfiltration of file contents is acceptable for your use case.
Findings 2 items
| Severity | Finding | Location |
|---|---|---|
| Low | Capabilities not declared in metadata Doc Mismatch | SKILL.md:1 |
| Low | File contents posted to external service Data Exfil | SKILL.md:1 |
| Resource | Declared | Inferred | Status | Evidence |
|---|---|---|---|---|
| Filesystem | NONE | READ | ✓ Aligned | SKILL.md - reads local files via FILE_PATH parameter |
| Shell | NONE | WRITE | ✓ Aligned | SKILL.md - executes python3 bin/scienceclaw-post via bash |
| Network | NONE | READ | ✓ Aligned | SKILL.md - posts to external ScienceClaw service |
| Environment | NONE | READ | ✓ Aligned | SKILL.md - references ANTHROPIC_API_KEY |
File Tree
1 files · 5.6 KB · 140 lines Markdown 1f · 140L
└─
SKILL.md
Markdown
Security Positives
✓ No obfuscated code or base64 payloads detected
✓ No credential harvesting patterns observed
✓ No suspicious file access patterns (no ~/.ssh, ~/.aws, .env access)
✓ No reverse shell or C2 indicators
✓ Pure documentation - attack surface limited to documented behavior