mageck

SAFE max severity MEDIUMSkillSpector Caution 20 registry K-Dense-AI last scanned 2026-10-21 1 scan

Verdict safe, but 3 findings (2 medium, 1 low), mainly command injection, supply chain attack. Most recent scan 2026-10-21.

Findings3

Critical0

High0

Medium2

Low1

Analyzersstatic bytecode pipeline correlation behavioral trigger

Scanner version2.3.1

Second scanner: NVIDIA SkillSpector

VerdictCaution 20

Score20 / 100

Issues3

CategoriesDangerous Code Execution MCP Least Privilege

Version2.12.0 (static)

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

Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.

Package: 4 files, 29 KB
SKILL.md: 1009 words, 7 sections
Code: Python (1)
License: MIT
Compatibility: Requires Python 3.10+ for the helper and MAGeCK 0.5.9.5 with its compiled RRA executable for analysis. Tested runtime uses Python 3.11, NumPy 1.26.4 and SciPy 1.13.1. Source installation needs a C++ compiler; network is needed only for installation. No credentials.

SKILL.md covers: MAGeCK pooled-screen analysis · When to use · Runtime · Workflow · Commands · Single-end guide reads; trim and orientation must match the user's library preparation. · Primary references

Findings

MEDIUM Remote fetch followed by execution Command Injectionpipeline

Content is downloaded from the network and subsequently executed. This is a classic remote code execution attack pattern. (found in documentation — may be instructional)

references/runtime.md:14

uv venv --python 3.11 mageck-env
uv pip install --python mageck-env/bin/python numpy==1.26.4 scipy==1.13.1 setuptools==69.5.1
curl -fL 'https://sourceforge.net/projects/mageck/files/0.5/mageck-0.5.9.5.tar.gz/download' -o mageck.tar.gz
tar -xzf mageck.tar.gz
# This archive contains liulab-mageck-c491

Remediation: Review the command sequence for potential multi-step attacks. Ensure all steps are necessary and safe.

MEDIUM Glob or find pattern targeting hidden (dot) files, which may expose sensitive configurations Command Injectionstatic

Pattern detected: glob("screen.*

scripts/screen_analysis.py:214

for artifact in work.glob("screen.*"):

Remediation: Avoid targeting hidden files with glob patterns. Be explicit about which files to access

LOW Archive extraction followed by execution Supply Chain Attackpipeline

An archive is extracted and its contents are then executed. This pattern can deliver and run malicious payloads hidden in archives. (found in documentation — may be instructional)

references/runtime.md:15

uv venv --python 3.11 mageck-env
uv pip install --python mageck-env/bin/python numpy==1.26.4 scipy==1.13.1 setuptools==69.5.1
curl -fL 'https://sourceforge.net/projects/mageck/files/0.5/mageck-0.5.9.5.tar.gz/download' -o mageck.tar.gz
tar -xzf mageck.tar.gz
# This archive contains liulab-mageck-c491

Remediation: Review the command sequence for potential multi-step attacks. Ensure all steps are necessary and safe.

What is in the package

File	Kind	Size
`SKILL.md`	doc	8.4 KB
`references/design.md`	doc	2.9 KB
`references/runtime.md`	doc	3.4 KB
`scripts/screen_analysis.py`	script	14 KB

External hosts referenced

sourceforge.net github.com

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-mageck-scan.json
Badge for your README: ![skillscan.io](https://skillscan.io/badge/k-dense-ai-mageck.svg)
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