Skill UI

Provides Wycheproof test vectors for validating cryptographic implementations against known attacks and edge cases, making it ideal for CI regression sweeps and third-party crypto audits.

A rigorous, security-focused code review process designed for Pull Requests (PRs), commits, and diffs. It moves beyond general reviews by focusing intensely on high-risk areas such as authentication, cryptography, external calls, and value transfer. The methodology is evidence-based, requiring detailed attack scenario modeling and generating comprehensive, auditable markdown reports to identify overlooked vulnerabilities and regressions.

Master the creation of a two-tier Public Key Infrastructure (PKI) Certificate Authority hierarchy—including an offline Root CA and an operational Intermediate CA. This skill guides you through using OpenSSL and Python cryptography to manage X.509 certificate issuance, configure Certificate Revocation Lists (CRLs), set up OCSP responders, and enforce strict certificate policies. Essential for deploying robust trust anchors for TLS, code signing, or client authentication.

This guide details the configuration and implementation of mutual TLS (mTLS) authentication between microservices. It utilizes Python's cryptography library for robust certificate generation, validation, and secure service-to-service authentication, essential for adopting zero-trust security models.

Automates the static security analysis of Android APK/AAB files using the Mobile Security Framework (MobSF). This skill identifies critical vulnerabilities such as hardcoded secrets, insecure permissions, weak cryptography, and structural flaws (mapping to OWASP Mobile Top 10) without requiring application execution. It is essential for integrating security gates into CI/CD pipelines, performing pre-release quality assurance, and enhancing penetration testing coverage.

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.

A comprehensive strategy guide for authors preparing manuscripts for the ACM Symposium on Theory of Computing (STOC). It helps researchers determine the ideal fit, required evidence bar, and narrative framing for major theoretical contributions in algorithms, complexity, cryptography, and theoretical computer science.

This guide helps authors assess whether their computer security manuscript is suitable for the European Symposium on Research in Computer Security (ESORICS). It covers conference positioning, necessary evidence standards (e.g., threat models, empirical validation), and scope definition across privacy, systems, and cryptography, ensuring the paper meets the high academic bar of the venue.

This comprehensive guide helps authors determine if their manuscript is suitable for the Financial Cryptography and Data Security (FC) conference. It covers the specific scope fit, required evidence standards (including threat models and economic context), and best practices for re-framing general CS research into a finance/security-focused narrative, ensuring the paper meets the expectations of the specialized review community.

This comprehensive guide helps authors strategically position their theoretical computer science manuscript for the IEEE Symposium on Foundations of Computer Science (FOCS). It analyzes the paper's core contribution type, required technical depth (algorithms, complexity, cryptography), necessary evidence, and structural framing to meet the high academic standards of the venue. Ideal for venue selection and manuscript refinement.

This skill performs security-focused code reviews for pull requests, commits, and diffs. It prioritizes high-risk areas like authentication, cryptography, and external calls. The process is evidence-based, requiring specific line numbers and attack scenarios. It adapts to codebase size and always generates a comprehensive markdown report.