ironclawSafety for AI agents. Real-time threat classification to detect malicious content before it causes agents harm.
Grade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → https://ironclaw.io/api/v1/labelCalls external URL not in known-safe list
https://ironclaw.ioAI Analysis
The skill's external API calls are fully documented and directly serve its stated purpose of content safety classification. While it sends user data to an external server, this is transparently disclosed as the core functionality, not hidden exfiltration. No credential harvesting, hidden instructions, or obfuscation were found.
Audited Apr 17, 2026 · audit v1.0
Generated Mar 1, 2026
Customer service AI agents interact with users who may attempt prompt injections to extract sensitive information or manipulate responses. Ironclaw can screen incoming queries in real-time to detect malicious intent, ensuring bots adhere to safety protocols and prevent data leaks or inappropriate replies. This is critical in industries like banking or healthcare where compliance and data protection are paramount.
Developer AI assistants that generate or review code can inadvertently include dangerous commands or hardcoded secrets. Ironclaw validates shell commands and detects credential leaks before execution, reducing risks of system damage or security breaches. This scenario is ideal for software development teams using AI tools to automate coding tasks.
AI agents managing social media accounts or forums need to filter out harmful content like hate speech or spam. Ironclaw classifies posts based on customizable criteria, helping bots flag or block malicious messages automatically. This supports platforms in maintaining safe online communities and adhering to content policies.
Educational AI tutors may face attempts to bypass safety rules or inject inappropriate content by students. Ironclaw screens interactions for prompt injections and malicious patterns, ensuring the learning environment remains secure and focused. This is useful in e-learning platforms to protect both users and system integrity.
Enterprise AI agents handling sensitive data via APIs are vulnerable to attacks like credential harvesting or data exfiltration. Ironclaw monitors API calls and data exchanges for threats, providing an extra layer of defense against breaches. This scenario applies to industries like finance or logistics where data security is critical.
Offer basic usage with rate limits (e.g., 10 requests/minute) for free to attract users, then charge for higher tiers with increased limits (e.g., 60 requests/minute) and premium features. This model encourages adoption while monetizing heavy users or enterprises needing scalable security.
Provide custom licensing for large organizations with dedicated support, advanced threat intelligence, and integration services. This includes tailored criteria development and compliance reporting, targeting sectors like banking or healthcare with strict security requirements.
Partner with AI platform marketplaces (e.g., Moltbook) to offer Ironclaw as a built-in safety skill, earning revenue through commissions or bundled subscriptions. This expands reach to developers and agents already using these ecosystems for easy adoption.
💬 Integration Tip
Start by testing with the free API to validate criteria, then integrate into your agent's workflow using simple POST requests for real-time threat classification.
Scored Apr 22, 2026
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