Loading the registry…
AI-powered QC for fiber trench construction documentation (APG Hackathon 2026)
Cursor Rules are .cursorrules / .cursor/rules files that steer Cursor's AI; scanned with the same pipeline.
We found this by crawling public sources and nobody has attested to it. That is how most of the registry gets here, and it is not a mark against the artifact — it only means no authenticated act of publication is on record. An artifact can be the vendor's own and still appear here.
8 critical findings reported by cisco-skill-scanner. The composite score alone does not reflect this — read the per-scanner reports below.
Cursor Rules are .cursorrules / .cursor/rules files that steer Cursor's AI. Review the scanned source before copying them into your own project.
nerlo install -- oepentrench
4 of 11 scanners examined this package. The rest do not apply to it — language, ecosystem and packaging decide which analyzers can say anything, and a scanner that cannot examine an artifact reports nothing rather than passing it.
v2.0.11
40 findings · 13.2s
v0.3.74
20 findings · 16.2s
v0.1.0
0 findings · 4.0s
v0.1.0
2 findings · 4.0s
v1.4.0
None of the entry points this scanner reads were found in this artifact. What each scanner covers
0 findings · 0.2s
vv0.3.2
No Go packages were found in this artifact. What each scanner covers
0 findings · 0.1s
v0.1.0
This scanner found nothing in this artifact that it assesses. What each scanner covers
0 findings · 1.7s
No report in this scan: govulncheck, osv-scanner, trivy, trivy_image.
1 scan on record. Every scan's full results are retained immutably for 24 months.
| Completed | Composite | Change | Scanners | Status |
|---|---|---|---|---|
| Aug 21, 2026 | Scan Halted | — | agentshield ·n/a: not applicablecisco-skill-scanner: completeagent-audit-kit: completenerlo-behavioral: completenerlo-install-instruction: completecapslock ·n/a: not applicablenerlo-multi-source ·n/a: not applicable | rejected |
Findings in files this artifact installs stand as reported; a model re-read the rest and said which ones it believes are false positives. This is a second opinion published beside the evidence, not a correction to it: the per-scanner reports above are unchanged, every dismissed finding is still listed there at its original severity, and the score and the Flagged badge are computed from those raw severities alone. Nothing below moved them.
Out of 62 findings across every scanner that examined this package. None of the 8 findings rated critical by their scanner were dismissed.
Two keys had to turn. The model had to name a reason from a fixed list of six, and a deterministic check of ours — over which files this artifact actually installs — had to independently agree. Anything it could not corroborate is in “not reviewed” above, at full severity.
11 Documentation or example — The match is in documentation or sample code, confirmed by our own check to be outside the installed artifact.
Rules: opt.nerlo-rules.nerlo-install-pipe-to-shell, AAK-HEALTHCARE-AI-004, SOCIAL_ENG_VAGUE_DESCRIPTION and 2 more · Files: /repo/docs/labelling-harness.md, docs/labelling-harness.md, /repo/docs/SKILL.md and 4 more · reported by nerlo-install-instruction, agent-audit-kit, cisco-skill-scanner
2 Agent instruction file — The match is in a file that instructs an AI coding agent — a CLAUDE.md or similar. It is documentation of intent, and our own check confirmed it is not part of what gets installed.
Rules: AAK-AGENT-002, TOOL_ABUSE_UNDECLARED_NETWORK · Files: CLAUDE.md, /repo/repo/CLAUDE.md · reported by agent-audit-kit, cisco-skill-scanner
These findings are in files this artifact installs and are not placeholder values. No false-positive basis can be corroborated for such a finding, so this review never dismisses one; they were not sent to the model and stand at their scanner's severity.
17 AAK-MCP-OPENAPI-LAZY-DESCRIPTION-001
Files: openapi/openapi.json · reported by agent-audit-kit
8 COMMAND_INJECTION_EVAL
Files: /repo/scripts/train_trench_classifier.py, /repo/src/api/helpers/face_detection.py, /repo/src/classifier/trench_classifier.py and 2 more · reported by cisco-skill-scanner
5 BINARY_FILE_DETECTED
Files: /repo/data/cache/phashes.parquet, /repo/artifacts/trench_classifier_base/head.joblib, /repo/artifacts/trench_classifier_tuned/head.joblib and 2 more · reported by cisco-skill-scanner
5 UNANALYZABLE_BINARY
Files: /repo/artifacts/trench_classifier_base/head.joblib, /repo/data/cache/phashes.parquet, /repo/artifacts/trench_classifier/head.joblib and 2 more · reported by cisco-skill-scanner
4 MANIFEST_MISSING_LICENSE
Files: /repo/SKILL.md, /repo/frontend/SKILL.md, /repo/scripts/SKILL.md and 1 more · reported by cisco-skill-scanner
Critical command injection vulnerabilities detected.
The artifact contains critical command injection vulnerabilities, allowing shell execution in multiple Python files. Specifically, eight instances of `COMMAND_INJECTION_EVAL` were found in `/repo/scripts/train_trench_classifier.py`, `/repo/src/api/helpers/face_detection.py`, `/repo/src/classifier/trench_classifier.py`, `/repo/vm-server/server/adapters/grounding_dino.py`, and `/repo/vm-server/server/adapters/owlv2.py`. Additionally, the artifact exhibits low analyzability, which may obscure further risks. These findings warrant immediate attention.
Concern level assessed by the review: Critical. This is the review's scale, not the registry badge.
Reviewed by gemini-2.5-flash. The model sees the findings, not your code, and cannot change a score.
4 SOCIAL_ENG_VAGUE_DESCRIPTION
Files: /repo/SKILL.md, /repo/frontend/SKILL.md, /repo/scripts/SKILL.md and 1 more · reported by cisco-skill-scanner
2 EXCESSIVE_FILE_COUNT
Files: /repo/., /repo/frontend/. · reported by cisco-skill-scanner
2 LOW_ANALYZABILITY
Files: /repo, /repo/frontend · reported by cisco-skill-scanner
1 AAK-LEGAL-002
Files: frontend/package.json · reported by agent-audit-kit
1 OVERSIZED_FILE
Files: /repo/weights/yolo11l-aug.pt · reported by cisco-skill-scanner