Security Audit

performance-profiling

github.com/davila7/claude-code-templates

AI SkillCommit 458b11867eae

CRITICAL

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

performance-profiling received a trust score of 38/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.

SkillShield's automated analysis identified 5 findings: 1 critical, 1 high, 2 medium, and 1 low severity. Key findings include Arbitrary command execution, Dangerous call: subprocess.run(), Network egress to untrusted endpoints.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The Manifest Analysis layer scored lowest at 61/100, indicating areas for improvement.

Last analyzed on February 12, 2026 (commit 458b1186). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

61%

Static Code Analysis

78%

Dependency Graph

100%

LLM Behavioral Safety

100%

Behavioral Risk Signals

Network Access

2 findings

Shell Execution

3 findings

Dynamic Code

1 finding

Security Findings5

Severity	Finding	Layer	Location
CRITICAL	Arbitrary command execution Python shell execution (os.system, subprocess) Review all shell execution calls. Ensure commands are static (not built from user input), use absolute paths, and are strictly necessary. Prefer library APIs over shell commands.	Manifest	cli-tool/components/skills/development/performance-profiling/scripts/lighthouse_audit.py:22
HIGH	Dangerous call: subprocess.run() Call to 'subprocess.run()' detected in function 'run_lighthouse'. This can execute arbitrary code. Avoid using dangerous functions like exec/eval/os.system. Use safer alternatives.	Static	cli-tool/components/skills/development/performance-profiling/scripts/lighthouse_audit.py:22
MEDIUM	Network egress to untrusted endpoints HTTP request to raw IP address Review all outbound network calls. Remove connections to webhook collectors, paste sites, and raw IP addresses. Legitimate API calls should use well-known service domains.	Manifest	cli-tool/components/mcps/devtools/figma-dev-mode.json:4
MEDIUM	Unsanitized user input passed to external command The `lighthouse_audit.py` script takes a URL directly from `sys.argv[1]` and passes it as an argument to the `lighthouse` command via `subprocess.run`. While using a list of arguments for `subprocess.run` prevents direct shell injection, an attacker could craft the URL to include `lighthouse` command-line flags (e.g., `--version`, `--help`, or flags that alter output behavior). This argument injection could cause `lighthouse` to behave unexpectedly, potentially leading to denial of service, information disclosure (if specific flags are exploited), or other unintended side effects depending on the `lighthouse` CLI's argument parsing and the agent's execution environment. Validate and sanitize the `url` argument before passing it to `subprocess.run`. Ensure it is a well-formed URL and does not contain unexpected command-line flags or metacharacters. For example, use `urllib.parse.urlparse` to strictly validate the URL structure and reject inputs that contain `--` or other suspicious patterns if they are not part of a valid URL path or query.	Static	scripts/lighthouse_audit.py:20
LOW	Covert behavior / concealment directives Multiple zero-width characters (stealth text) Remove hidden instructions, zero-width characters, and bidirectional overrides. Skill instructions should be fully visible and transparent to users.	Manifest	cli-tool/components/mcps/devtools/jfrog.json:4

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