Security Audit

aikek-api

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

CAUTION

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

aikek-api received a trust score of 57/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 3 findings: 1 critical, 0 high, 2 medium, and 0 low severity. Key findings include Network egress to untrusted endpoints, Suspicious import: requests, Unpinned Python Dependencies.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.

Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

70%

Static Code Analysis

93%

Dependency Graph

100%

LLM Behavioral Safety

93%

Behavioral Risk Signals

Network Access

3 findings

Excessive Permissions

1 finding

Security Findings3

Severity	Finding	Layer	Location
CRITICAL	Network egress to untrusted endpoints Python requests POST/PUT to URL 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	skills/vvsotnikov/aikek/scripts/register.py:50
MEDIUM	Suspicious import: requests Import of 'requests' detected. This module provides network or low-level system access. Verify this import is necessary. Network and system modules in skill code may indicate data exfiltration.	Static	skills/vvsotnikov/aikek/scripts/register.py:18
MEDIUM	Unpinned Python Dependencies The skill specifies `solders` and `requests` as dependencies without pinning their versions. This can lead to supply chain vulnerabilities, such as dependency confusion attacks, or unexpected breakage if newer versions introduce breaking changes or security flaws. It is best practice to pin dependencies to specific, known-good versions to ensure reproducibility and security. Pin dependency versions to specific, known-good versions (e.g., `solders==X.Y.Z requests==A.B.C`) in a `requirements.txt` file or similar. Regularly audit and update these pinned versions.	LLM	scripts/register.py:10

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/a4015f02afb55c7b.svg)](https://skillshield.io/report/a4015f02afb55c7b)