Skill UI

The Founder-Mode Executive Team simulates a complete C-suite of 13 specialized agents (CFO, CMO, CPO, etc.) and provides 21 structured slash commands. It is designed for founders and executives who need multi-perspective analysis, deep strategic reviews (e.g., unit economics, threat modeling), consensus building, and structured decision logging. Use it when orchestrating complex, multi-phase business decisions.

A risk-paranoid, mandatory review process designed to interrogate any plan that touches sensitive customer data, regulatory compliance, or production access. It forces consideration of critical security pillars including STRIDE threat modeling, blast radius quantification, detection mechanisms (MTTD), incident response runbooks, regulatory notification windows, and third-party vendor security posture. Essential before deploying features handling PII, PHI, or before compliance audits (SOC 2, HIPAA, GDPR).

This skill provides deep security review for GitHub Actions workflow files. It focuses on the unique Actions threat model—identifying vulnerabilities like script injection via ${{ }} interpolation, privilege escalation from triggers (e.g., pull_request_target), and ensuring least-privilege permissions for CI/CD pipelines. Use it to audit, secure, or harden existing workflows, preventing attacks from untrusted inputs and supply chain risks.

This skill generates a comprehensive, structured threat model for any given service or feature using the STRIDE framework. It guides users through identifying critical assets, defining trust boundaries, enumerating specific threats (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege), assessing risk, and proposing concrete mitigation controls. Ideal for security design reviews and documentation.

Automate security regression testing for Large Language Model (LLM) applications by integrating Promptfoo and DeepTeam into CI/CD pipelines. This skill enforces a critical security gate, automatically testing endpoints against OWASP LLM Top 10, OWASP Agentic threats, and common jailbreaks/prompt injections. It ensures that security patches do not regress over time due to prompt or model changes, providing continuous risk monitoring.

This guide demonstrates how to use the pycti Python client to model complex cyber threat intelligence within the OpenCTI platform. It structures threat actors, intrusion sets, campaigns, and TTPs into a unified STIX 2.1 knowledge graph. The skill is essential for correlating fragmented data from multiple sources (IOCs, reports) into a comprehensive, queryable adversary picture, supporting advanced threat hunting and detection engineering.

A comprehensive audit worker that integrates Open Infrastructure Architecture (OIA) manifest analysis, threat modeling, and MCP security scanning. It computes a composite worst-case severity score and persists time-stamped audit records in a memory namespace. Primarily designed for scheduled CI/CD pipelines to detect architectural drift and security regressions over time.

This skill generates an enterprise-grade threat model report using the `harness threat-model` command. It categorizes threats across the MCP surface, providing a detailed report including the overall worst severity (clean, low, medium, high) and specific findings. Ideal for pre-launch security reviews and periodic audits when sharing findings with an InfoSec team.

This tool performs comprehensive safety scanning on untrusted inputs, such as user submissions, API payloads, or webhook data. It detects sophisticated threats like prompt injection, jailbreak attempts, and adversarial attacks using advanced AI defense mechanisms, ensuring data integrity and security before model processing or execution.

A comprehensive tool for authors targeting the ACM Asia Conference on Computer and Communications Security (ASIACCS). It provides expert guidance on assessing whether a computer and communications security manuscript is a strong fit for this specific, high-impact venue. Topics covered include conference fit assessment, evidence bar establishment, manuscript re-framing strategies, threat modeling, and proper community positioning for maximum review impact.

This comprehensive guide helps authors strategically position their computer security manuscripts for the ACM Conference on Computer and Communications Security (CCS). It details topic fit, required threat modeling, evidence presentation, and critical comparisons with sister venues (e.g., S&P, USENIX Security). It serves as a high-level 'fit/framing' tool for maximizing submission success in core areas like privacy, cryptography, and systems security.

This comprehensive guide assists authors in evaluating the suitability, framing, and structural requirements for submitting research on wireless, mobile, IoT, sensing, and network security/privacy to the ACM WiSec conference. It provides critical expertise on aligning the paper's contribution type, threat model, and evidence standards with top-tier academic conference expectations, ensuring the work emphasizes the physical or network context.