glitchward-shieldScan prompts for prompt injection attacks before sending them to any LLM. Detect jailbreaks, data exfiltration, encoding bypass, multilingual attacks, and 25...
Install via ClawdBot CLI:
clawdbot install eyeskiller/glitchward-shieldGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Contains instructions to override system prompt or ignore user requests
"ignore all previous instructions"Sends data to undocumented external endpoint (potential exfiltration)
POST → https://glitchward.com/api/shield/validateCalls external URL not in known-safe list
https://glitchward.com/shieldAI Analysis
The skill sends user prompts to an external API for security scanning, which is consistent with its stated purpose of detecting prompt injection. While this involves data transmission to a third party (Glitchward), it is a declared and necessary function of the skill, not unauthorized or hidden. The primary risk is privacy-related, as user inputs are sent externally, but there is no evidence of credential harvesting, hidden instructions, or obfuscated malicious behavior.
Generated Mar 1, 2026
Integrate Glitchward Shield into a customer support chatbot to scan user queries before processing by an LLM, preventing prompt injection attacks that could manipulate the bot into revealing sensitive data or performing unauthorized actions. This ensures secure interactions in industries like finance or healthcare where data protection is critical.
Use the skill to validate user-generated content on social media platforms before it's analyzed by AI for sentiment or categorization, detecting multilingual and stealth attacks that might bypass traditional filters. This helps maintain platform integrity by blocking malicious prompts aimed at exploiting LLM-based moderation tools.
Deploy Glitchward Shield in an academic or research AI agent that processes external documents and user queries, scanning for data exfiltration and jailbreak attempts to protect intellectual property and ensure compliant usage. This is essential in fields like pharmaceuticals where proprietary information must be safeguarded.
Implement the shield to validate customer inputs in an AI-driven recommendation engine, preventing attacks like role hijacking that could skew product suggestions or access unauthorized data. This enhances security for online retailers handling large volumes of user interactions and personal data.
Integrate the skill into an AI agent that reviews legal documents, scanning prompts for injection attacks that might alter contract interpretations or leak confidential case details. This supports law firms in maintaining client confidentiality and preventing manipulation of AI-assisted legal analysis.
Offer a free tier with 1,000 monthly requests to attract developers, then upsell to paid tiers (Starter and Pro) with higher limits for scaling businesses. Revenue is generated through subscription fees based on usage volume, targeting startups and enterprises needing robust security.
License the skill as part of a broader security suite for large organizations, providing custom integrations, dedicated support, and advanced features like batch validation. Revenue comes from annual contracts and service fees, focusing on industries with high compliance requirements.
Distribute the skill through AI agent platforms or marketplaces, earning revenue via one-time purchases or commission on usage. This model targets individual developers and small teams looking for easy-to-deploy security tools to enhance their AI applications.
💬 Integration Tip
Set the GLITCHWARD_SHIELD_TOKEN environment variable first, then use the validate endpoint before each LLM call to block attacks based on the is_blocked response.
Scored Apr 19, 2026
Audited Apr 17, 2026 · audit v1.0
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