hopeidsInference-based intrusion detection for AI agents. Pattern matching + LLM analysis for jailbreaks, prompt injection, credential theft, social engineering. 108 detection patterns, OpenClaw plugin, auto-scan, quarantine. Commands: hopeid scan, hopeid test, hopeid setup, hopeid stats, hopeid doctor.
Install via ClawdBot CLI:
clawdbot install emberdesire/hopeidsGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/E-x-O-Entertainment-Studios-Inc/hopeIDSAudited Apr 17, 2026 · audit v1.0
Generated Mar 20, 2026
A bank deploys this skill on its customer service AI agent to automatically block attempts to extract sensitive account details or inject malicious commands. It uses strict mode for high-risk agents handling transactions, with Telegram alerts enabling compliance officers to review and approve or reject flagged interactions in real-time.
A telehealth platform integrates the skill to scan messages between patients and AI assistants, quarantining any attempts to override instructions or exfiltrate personal health information. Per-agent config allows stricter thresholds for agents accessing medical records, ensuring HIPAA compliance through metadata-only logging and human review via alerts.
An online retailer uses the skill to protect its AI support agents from jailbreak attempts or credential theft scams. Non-strict mode on main agents warns of suspicious patterns without disrupting service, while strict mode blocks high-risk threats on backend agents, with alerts sent to security teams for manual oversight and trust-building for legitimate users.
An edtech company applies the skill to AI tutors to detect and block instruction overrides or impersonation attacks that could manipulate learning content. It configures per-agent thresholds to balance security with educational flow, using quarantine records to audit incidents and commands like /trust to whitelist verified educators.
A smart home provider deploys the skill on AI agents controlling IoT devices, scanning for command injection or discovery threats that could compromise device security. Strict mode is enabled for critical agents, with Telegram alerts allowing administrators to approve false positives and reinforce patterns based on threat categories like data exfiltration.
Offer the skill as a cloud-based service with tiered pricing based on the number of AI agents, message volume, and features like advanced threat categories or custom pattern matching. Revenue comes from monthly subscriptions, with upsells for dedicated support or compliance reporting.
Sell perpetual licenses to large organizations for on-premises deployment, including custom configuration, integration support, and training. Revenue is generated through one-time license fees plus annual maintenance contracts for updates and security patches.
Provide a free version with basic auto-scan and quarantine for small teams, monetizing through premium upgrades such as per-agent config, advanced Telegram alert customization, or priority human-in-the-loop review. Revenue streams include in-app purchases or subscription tiers.
💬 Integration Tip
Ensure proper configuration of per-agent settings to match security postures, and test commands like /scan in a staging environment before deployment to avoid false positives in production.
Scored Jun 17, 2026
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