Security Audit

antigravity-image-gen

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

CAUTION

Scanned about 1 month ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

antigravity-image-gen received a trust score of 70/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 2 findings: 0 critical, 2 high, 0 medium, and 0 low severity. Key findings include Sensitive path access: AI agent config, Arbitrary File Write via Unsanitized Output Path.

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

100%

Static Code Analysis

85%

Dependency Graph

100%

LLM Behavioral Safety

85%

Behavioral Risk Signals

Filesystem Write

2 findings

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Sensitive path access: AI agent config Access to AI agent config path detected: '~/.clawdbot/'. This may indicate credential theft. Verify that access to this sensitive path is justified and declared.	Static	skills/ipedrax/antigravity-image-gen/SKILL.md:8
HIGH	Arbitrary File Write via Unsanitized Output Path The `scripts/generate.js` skill takes an `--output` argument which is directly used as the file path for `fs.writeFileSync` without proper sanitization or validation. This allows an attacker to specify an arbitrary file path, potentially outside the intended output directory, leading to arbitrary file write. An attacker could use path traversal sequences (e.g., `../../`) to write files to sensitive locations on the filesystem, potentially overwriting system files, creating malicious scripts, or causing denial of service. Implement strict path validation for the `--output` argument. Ensure the provided path is normalized and resolved to be strictly within a designated, secure output directory (e.g., `/tmp/generated-images/` or a user-specific sandbox directory). Reject any paths that attempt to traverse outside this directory. Alternatively, only allow the user to specify a filename and construct the full path internally within a secure, predefined directory.	LLM	scripts/generate.js:30

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