ClawHub

Guardian Shield

v1.1.1

Locally scans untrusted text and documents to detect and block prompt injection threats, jailbreaks, exfiltration, and social engineering attacks.

⭐ 0· 344·1 current·1 all-time
byJosh@jtil4201
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
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Benign
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OpenClawOpenClaw
Benign
high confidence
✓
Purpose & Capability
Name/description (local prompt injection scanner) align with the included files: regex patterns, scanner, text extraction, and an optional ML model. No unrelated credentials, binaries, or network dependencies are requested.
✓
Instruction Scope
SKILL.md and README instruct only local scanning (CLI and Python API) and call the provided scripts. The instructions do reference scanning web_fetch outputs, group messages, and file contents — which matches the scanner's capabilities. The example text includes malicious phrases (e.g., 'ignore previous instructions') which triggered the pre-scan pattern detector; this is expected for a demonstration of detections, not an instruction to exfiltrate data.
ℹ
Install Mechanism
No install spec (instruction-only) which minimizes installer risk. Optional Python dependencies are listed (onnxruntime, PyPDF2, beautifulsoup4). One small inconsistency: the package includes models/ward_vocab.json (vocab) but the ONNX model file ward.onnx is not present in the provided manifest — ML inference will be unavailable unless the model file is obtained separately.
✓
Credentials
The skill does not request environment variables, credentials, or config paths. Config.json flags (e.g., scan_web_fetches, scan_file_reads) are local configuration toggles and do not imply secret access. No disproportionate credential requests were found.
✓
Persistence & Privilege
Skill is not always-enabled and does not modify other skills or global agent settings. It is a library/CLI the agent can call; it does not request elevated persistence or special privileges.
Scan Findings in Context
[ignore-previous-instructions] expected: SKILL.md and README intentionally include example attack phrases (e.g., 'ignore previous instructions') to demonstrate detection. The pre-scan flag is therefore expected and does not by itself indicate malicious intent.
Assessment
This package appears coherent and implements a local prompt-injection scanner as advertised. Before installing, consider: 1) The ML model (ward.onnx) is not included in the manifest — ML scoring will be disabled unless you provide a trusted ONNX model and install onnxruntime. 2) Optional dependencies (PyPDF2, beautifulsoup4, onnxruntime) are required only for extra features; install them from PyPI if you need those capabilities. 3) The skill's examples deliberately contain malicious phrases (used to test detection) — this is normal for this tool. 4) If you enable automatic scanning of agent outputs (web_fetch results, group messages, file reads), confirm your agent's integration respects privacy and you trust the skill source; it will examine untrusted content but does not exfiltrate it. 5) Check the license terms (source-available, non-commercial free tier) before using in commercial contexts. If you want higher assurance, ask the author for the missing model file checksum or supply your own vetted model.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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