torchdrug
4 findings (4 high), mainly command injection. Most recent scan 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
- Package
- 10 files, 76 KB
- SKILL.md
- 1314 words, 12+ sections
- Code
- None. Instructions only.
- Allowed tools
ReadWriteEditBash- License
- Apache-2.0 license
- Compatibility
- Requires Python 3.7-3.10, PyTorch 1.8-2.0, compatible torch-scatter/torch-cluster, RDKit, and fair-esm. Apple Silicon is CPU-only and requires native builds; MPS is unsupported. Network access is needed for uncached datasets and weights.
SKILL.md covers: TorchDrug · Start with the version guard · Installation · Canonical property-prediction workflow · Choose the official workflow · Molecular property prediction · Self-supervised molecular pretraining · Molecule generation · Retrosynthesis · Knowledge graph reasoning · Protein modeling · Rules for reliable TorchDrug code
Findings
HIGH Python code block uses eval/exec Command Injectionbehavioral
Code block in references/molecular_generation.md at line 74 contains potentially dangerous Python code.
references/molecular_generation.md:74
task.eval()HIGH Python code block uses eval/exec Command Injectionbehavioral
Code block in references/molecular_generation.md at line 201 contains potentially dangerous Python code.
references/molecular_generation.md:201
task.eval()HIGH Python code block uses eval/exec Command Injectionbehavioral
Code block in references/molecular_property_prediction.md at line 118 contains potentially dangerous Python code.
references/molecular_property_prediction.md:118
task.eval()HIGH Python code block uses eval/exec Command Injectionbehavioral
Code block in references/retrosynthesis.md at line 193 contains potentially dangerous Python code.
references/retrosynthesis.md:193
task.eval()What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 12 KB |
references/core_concepts.md | doc | 7.3 KB |
references/datasets.md | doc | 8.9 KB |
references/knowledge_graphs.md | doc | 5.8 KB |
references/models_architectures.md | doc | 5.6 KB |
references/molecular_generation.md | doc | 6.2 KB |
references/molecular_property_prediction.md | doc | 7.3 KB |
references/protein_modeling.md | doc | 8.2 KB |
references/retrosynthesis.md | doc | 7.4 KB |
references/review.md | doc | 7.1 KB |
External hosts referenced
torchdrug.ai github.com arxiv.org data.pyg.org deepchemdata.s3-us-west-1.amazonaws.com docs.astral.sh doi.org export.arxiv.org pypi.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-torchdrug-scan.json
- Badge for your README:
 - Request a re-scan