clawsec-feedSecurity advisory feed package for OpenClaw-related threats and vulnerabilities. The upstream feed is updated daily; local automation is handled by clawsec-s...
Install via ClawdBot CLI:
clawdbot install davida-ps/clawsec-feedGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://clawsec.prompt.securityUses known external API (expected, informational)
api.github.comAudited Apr 17, 2026 · audit v1.0
Generated Mar 1, 2026
Security teams can integrate clawsec-feed into their AI SOC to automatically monitor for vulnerabilities in OpenClaw-related tools. The daily NVD CVE updates provide real-time threat intelligence, allowing analysts to prioritize patching and mitigation efforts for critical vulnerabilities affecting their AI infrastructure.
Development teams building AI applications with OpenClaw can incorporate clawsec-feed into their CI/CD pipelines. The automated vulnerability feed helps identify security issues early in the development lifecycle, enabling proactive remediation before deployment to production environments.
MSSPs can use clawsec-feed to enhance their AI security monitoring services for clients using OpenClaw platforms. The standardized feed provides consistent vulnerability data that can be integrated into client dashboards and automated alerting systems for comprehensive threat management.
Organizations subject to regulatory requirements can leverage clawsec-feed to maintain continuous monitoring of AI system vulnerabilities. The automated NVD polling helps demonstrate due diligence in vulnerability management programs and supports compliance reporting for frameworks like NIST CSF or ISO 27001.
Research institutions and AI labs using OpenClaw for experimental projects can deploy clawsec-feed to maintain security awareness without dedicated security staff. The lightweight standalone installation allows researchers to stay informed about vulnerabilities while focusing on their core development work.
Offer clawsec-feed as a free community tool to build user adoption, then provide premium features like advanced analytics, custom alerting, or integration with commercial SIEM platforms. The open source foundation establishes trust while premium features generate recurring revenue from enterprise users.
Position clawsec-feed as a foundational component within a broader AI security platform. Offer additional paid modules for vulnerability assessment, patch management, and compliance reporting that integrate seamlessly with the free feed, creating upsell opportunities for comprehensive security solutions.
Provide the feed as open source software while generating revenue through enterprise support contracts, custom integration services, and security consulting. Organizations with critical AI deployments will pay for guaranteed response times, custom configurations, and dedicated security expertise.
💬 Integration Tip
Start with standalone installation for testing, then integrate into existing monitoring workflows using the checksum verification and structured JSON outputs for automated processing.
Scored Jun 19, 2026
Manage and operate ClawSec Monitor v3.0, a MITM HTTP/HTTPS proxy that logs AI agent traffic, detects exfiltration and injection threats in real time.
Command-line security analyzer for ClawHub skills. Run analyze-skill.sh to scan SKILL.md files for malicious patterns, credential leaks, and C2 infrastructure before installation. Includes threat intelligence database with 20+ detection patterns.
Scan Clawdbot and MCP skills for malware, spyware, crypto-miners, and malicious code patterns before you install them. Security audit tool that detects data exfiltration, system modification attempts, backdoors, and obfuscation techniques.
577+ pattern prompt injection defense. Now with typo-tolerant bypass detection. TieredPatternLoader fully operational. Drop-in defense for any LLM application.
Security scanner for ClawHub skills. Vet third-party skills before installation — detect dangerous patterns, suspicious code, and risky dependencies.
Security audit and hardening for AI agents — credential hygiene, secret scanning, prompt injection defense, data leakage prevention, and privacy zones.