sentinel-olegRuntime security layer for OpenClaw agents. Intercepts and scans all external input (emails, API responses, web content, chat messages, calendar events) for...
Install via ClawdBot CLI:
clawdbot install oleglegegg/sentinel-olegGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
wget [^&]*&& ?(bash|shAccesses system directories or attempts privilege escalation
/proc/Calls external URL not in known-safe list
https://api.example.com/dataAI Analysis
This skill implements runtime security monitoring which is legitimate, but it requires copying and executing external shell scripts with system-level access. The patterns include broad regex matching that could cause false positives/negatives, and the canary token mechanism could be misused for tracking. However, no evidence of data exfiltration or credential harvesting was found.
Generated Mar 21, 2026
Customer service AI agents handling emails and chat messages from untrusted users are vulnerable to prompt injection attacks. Sentinel intercepts all incoming communications, scans for multi-language injection attempts, and sanitizes input before the agent processes it, preventing malicious actors from hijacking the agent's behavior.
AI agents in fintech that parse bank statements, transaction data, or API responses from external financial services need protection against data exfiltration and credential leaks. Sentinel monitors both input and output, detecting attempts to steal API keys or crypto wallet information and preventing sensitive financial data from being leaked in agent responses.
Research AI agents that scrape web content, read academic papers, or process documents from various sources encounter potentially malicious content. Sentinel scans all fetched content for hidden prompt injections and social engineering attempts, normalizing Unicode and encoded threats while allowing clean research data through to the agent.
Healthcare AI agents managing patient communications, calendar events, and appointment details must prevent data leaks of PHI (Protected Health Information). Sentinel's output monitoring detects when agents might accidentally expose private information in responses, while input scanning protects against appointment manipulation attempts via prompt injection.
Logistics AI agents processing API responses from shipping carriers, supplier emails, and inventory updates need runtime protection against supply chain attacks. Sentinel detects credential leaks in API responses and prevents malicious actors from injecting commands that could disrupt shipping schedules or inventory management through the agent.
Offer Sentinel as part of a comprehensive AI security suite for enterprises deploying multiple agents. Charge annual subscriptions based on the number of protected agents, with tiered pricing for different threat detection levels and support SLAs. Include regular pattern updates and custom rule creation for specific industry threats.
Provide fully managed Sentinel deployment with 24/7 monitoring of threat logs and automated response configuration. Clients pay monthly for security operations center (SOC) services that analyze Sentinel logs, configure custom detection patterns, and provide incident response when threats are detected in their AI agents.
Offer professional services to integrate Sentinel into existing AI agent pipelines across different industries. Provide custom pattern development for specific threat landscapes (financial, healthcare, etc.), compliance configuration for regulations like HIPAA or GDPR, and security audit services using Sentinel's logging capabilities.
💬 Integration Tip
Start by adding sentinel-input.sh to all external data pipelines and sentinel-output.sh to agent response handlers, using the --clean flag initially to understand threat patterns without disrupting operations.
Scored Jun 19, 2026
Audited Apr 16, 2026 · audit v1.0
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