「secure」の検索結果

Detect insecure JWT (JSON Web Token) implementations in a codebase using a two-phase approach: first map all JWT issuance and verification sites to understand the token lifecycle and signing configuration, then check each verification site for exploitable weaknesses such as algorithm confusion, missing signature verification, weak secrets, header injection, and missing claim validation. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/jwt-results.md. If no JWT usage is found in Phase 1, Phase 2 is skipped. Use when asked to find JWT, token forgery, or authentication bypass bugs.

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Detect Insecure Direct Object Reference (IDOR) vulnerabilities in a codebase using a three-phase approach: recon (find candidates), batched verify (check authorization in parallel subagents, 3 candidates each), and merge (consolidate batch results). Checks endpoints for missing ownership or authorization checks on user-supplied identifiers. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/idor-results.md. Use when asked to find IDOR or authorization bypass bugs.

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This skill helps Claude write secure web applications. Use this when working on any web application or when a user requests a scan or audit to ensure security best practices are followed.

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Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.

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Use when storing credentials securely, encrypting data, implementing passkeys, securing AI/agentic features against prompt injection, code signing, or managing certificates and provisioning profiles.

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Use Apple CryptoKit for Swift cryptographic primitives. Use when hashing with SHA-2 or SHA-3, generating HMACs, encrypting with AES-GCM or ChaChaPoly, signing with P256/P384/P521/Curve25519 or ML-DSA keys, performing ECDH, HPKE, ML-KEM, or X-Wing key exchange, using Secure Enclave CryptoKit keys, or migrating CommonCrypto code to CryptoKit.

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Guides Stripe integration decisions across development and test environment planning (separate sandboxes vs the shared test mode sandbox), API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, tax and registrations (Stripe Tax, automatic_tax, product tax codes), Treasury financial accounts, integration options (Checkout, Payment Element), migrating from deprecated Stripe APIs, and security best practices (API key management, API key permissions, webhooks, OAuth). Use when planning, building, modifying, testing, or reviewing any Stripe integration, including choosing a development environment, accepting payments, building marketplaces, integrating Stripe, processing payments, setting up subscriptions, collecting sales tax, VAT, or GST, creating connected accounts, or implementing secure key handling.

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AWS Secrets Manager for secure secret storage and rotation. Use when storing credentials, configuring automatic rotation, managing secret versions, retrieving secrets in applications, or integrating with RDS.

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Manage secrets and certificates in Azure Key Vault. Configure access policies, integrate with Azure services, and implement secure secret management. Use when managing secrets in Azure environments.

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Generate, sign, and verify SBOMs and provenance attestations to secure the software supply chain. Use when implementing SLSA controls, artifact trust policies, or compliance evidence for releases.

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Scan container images for vulnerabilities using Trivy, Grype, and cloud-native tools. Identify security issues in base images, packages, and configurations. Use when implementing container security, building secure images, or meeting compliance requirements.

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Secure secrets in Google Cloud Secret Manager. Configure IAM policies, integrate with GKE, and manage secret versions. Use when managing secrets in GCP environments.

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Conduct threat modeling using STRIDE methodology. Identify threats, assess risks, and design security controls. Use when designing secure systems or assessing application security.

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Perform static application security testing with tools like Semgrep, CodeQL, and SonarQube. Identify security vulnerabilities in source code before deployment. Use when implementing secure SDLC, code review automation, or security gates in CI/CD pipelines.

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Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.

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Secure Model Context Protocol (MCP) servers with transport encryption, tool authorization, input validation, and audit logging for safe AI agent integrations.

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Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.

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Secure the AI model supply chain with artifact signing, provenance attestation, SBOM workflows, dependency controls, and trusted model promotion.

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Apply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features. Use when hardening Linux systems for production or meeting security compliance requirements.

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Secure OpenClaw deployments with preflight hardening checks, CI/CD guardrails, container runtime restrictions, and post-deploy verification. Use when shipping OpenClaw with Docker, Kubernetes, or automated release pipelines.

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Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

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Implement Kubernetes security contexts, Pod Security Standards, and network policies. Secure cluster components and workloads. Use when hardening Kubernetes deployments or meeting security compliance.

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Design secure, multi-tenant LLM hosting platforms with tenant isolation, quotas, billing attribution, noisy-neighbor protection, and per-tenant policy controls.

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Manage and secure company devices with MDM solutions — enroll macOS, Windows, iOS, and Android devices, enforce security policies, and automate software deployment. Use when setting up device management for a growing team.

日本語の概要は準備中です。原文の説明を表示しています。