Red Team persona for Business Logic and Auth manipulation. Generates and executes stateful fuzzing scripts (Playwright/Python) to test RBAC bypasses, BOLA/IDOR, race conditions, and complex multi-step transaction flaws.
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。
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概要と使いどころ
Red Team persona for Business Logic and Auth manipulation. Generates and executes stateful fuzzing scripts (Playwright/Python) to test RBAC bypasses, BOLA/IDOR, race conditions, and complex multi-step transaction flaws.
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。
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.
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。
Use when you need to add or review fuzz testing for Java APIs with CATS — including contract-driven negative testing, malformed payload validation, boundary input exploration, CI integration, reproducible failures, and local execution guidance. This should trigger for requests such as Add fuzz testing to a Java project; Use CATS for API negative testing; Review CI quality gates for API contract robustness; Improve boundary and malformed input test coverage; Run CATS fuzz tests against an OpenAPI contract. Part of Plinth Toolkit
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。
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
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。
Generate targeted test inputs to reach specific code paths and hard-to-reach behaviors in Python code. Use when: (1) Targeting uncovered branches or specific execution paths, (2) Need coverage-guided test generation, (3) Want to leverage LLM understanding of code semantics for meaningful test inputs, (4) Testing boundary conditions and edge cases systematically, (5) Combining symbolic reasoning with fuzzing. Provides path analysis, constraint solving, coverage-guided strategies, and LLM-driven semantic generation for comprehensive test input creation.
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。
Perform dynamic security testing against running web applications and APIs to discover vulnerabilities through active probing and fuzzing. Use when the user requests dynamic application security testing or provides relevant inputs for this workflow.
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。
Think and work like an expert Cryptographer. Use when a task calls for Cryptographer judgment. Reasons from IND-CCA/EUF-CMA games and tight reductions through AES-GCM/RSA-OAEP/ECDSA, ML-KEM/ML-DSA (FIPS 203/204), ProVerif/Tamarin/EasyCrypt, dudect constant-time, CAVP/ACVP and FIPS 140-3 CMVP—not pure number theory or vuln fuzzing.
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。
安全研究元思考方法论 - 从先知社区5600+篇安全文档中提炼的漏洞挖掘方法论框架。 Use this skill when: - 进行漏洞挖掘和安全研究时,需要系统化的思考框架 - 分析特定类型漏洞(Web注入、反序列化、二进制、域渗透等)的攻击路径 - 需要了解绕过防护措施(WAF、EDR、沙箱)的思维模式 - 进行代码审计需要Source-Sink分析方法论 - 红队攻防需要完整攻击链规划 - CTF竞赛需要快速解题思路 - 逆向分析恶意软件需要方法论指导 Triggers: 漏洞挖掘、安全研究、渗透测试、代码审计、红队攻防、CTF、逆向分析、 WAF绕过、免杀、提权、横向移动、域渗透、反序列化、二进制安全、Fuzzing
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。
A strict code reviewer, pair programmer, debugger, and mentor for Python, Bash, Google Apps Script, JavaScript, and Swift/Apple platforms. Use when writing, reviewing, debugging, planning, or securing code, or for senior-level rigor, a security review, or mentoring. Mode triggers — REVIEW: (critique + refactor), EXPLAIN: (teach), MVP:/PROTOTYPE: (lean-but-safe), DEBUG: (root-cause), AUDIT: (report-first); default is pair-programming. Drives a spec→plan→TDD→verify loop with a deterministic-first, verify-before-asserting (anti-hallucination) discipline. Enforces a security floor (secrets, injection, input validation, isolation, least privilege, authn) and a backup/continuity floor on a phase-aware rigor ladder (Prototype→MVP→Production) — cheap ≠ insecure. Covers testing & fuzzing, SAST/secret-scan/type-check/supply-chain gates, multi-tenant data protection, resilience & DR, scalability, CI/CD, cloud/containers/DBs, and accessible UI — deep references read on demand.
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。
Rust fuzzing with cargo-fuzz (libFuzzer).
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。
Python fuzzing with Atheris for discovering vulnerabilities in Python code.
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。
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.
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。
fast-check patterns for JS/TS — 6 canonical property categories with worked examples targeting agent-studio utilities (path normalization, safe-json, glob-to-regex, routing logic)
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。
Use when writing KUnit tests, adding kselftest cases, fuzzing syscalls with syzkaller and kcov, running LTP, or wiring CI for a kernel patch.
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。
Use when C code is written or audited and needs a pure-C baseline: standard, undefined behavior, integer and buffer safety, sanitizers, fuzzing, build flags. Not for C++: use modern-cpp-practices.
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。
Use when a user needs to measure fuzz corpus coverage, explain a coverage plateau, or turn uncovered regions into campaign work. Not for harness creation: use fuzz-harness-writing.
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。
Use when a user needs to create or improve a deterministic, engine-agnostic fuzz harness for raw or structured target inputs. Not for coverage measurement: use fuzzing-coverage-analysis.
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。
Use when a user needs coverage-guided fuzzing for Python code or a Python native extension using Atheris. Not for remote, credential, publish, deploy, or irreversible changes.
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。
Identify, exploit, and write custom payloads for classic Stack-Based Buffer Overflows in 32-bit and 64-bit applications. Use this skill when conducting exploit development, reverse engineering custom network protocols, or preparing for advanced certifications (OSCP, OSEP). Covers fuzzing, controlling EIP/RIP, identifying bad characters, generating shellcode, finding return/JMP instructions, and gaining reverse shells.
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。
Master Burp Suite Professional for comprehensive web application security testing. Use this skill when performing manual web application assessments with Burp Suite including proxy interception, Scanner automation, Intruder attacks, Repeater analysis, and extension integration. Covers advanced techniques like match-and-replace rules, macro authentication, Collaborator for OOB testing, and Turbo Intruder for high-speed fuzzing.
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。
Bug bounty findings secretary, tracker, and workspace initializer for the bb-huge portal. Use this skill for web security research, vulnerability hunting, and hunt workspace setup. Triggers on: "log finding", "save finding", "add to bb-huge", "record vulnerability", "update finding", "show findings", "bb-huge stats", "mark as confirmed", "mark as rewarded", "setup workspace", "pull evidence", "continue working on finding", "dump attachments", "list my skills", "what skills do I have", "/bb-huge init", "init hunt workspace", "new bug bounty program", "start hunting", "mobile bug bounty", "binary analysis", "source code review", "white-box audit", "h1-brain", "hack program", "hack()", "search disclosed", "fetch rewarded". Also auto-activates whenever a vulnerability is discovered during any recon, fuzzing, or manual testing session — do not wait to be asked.
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。
AI/LLM red-team assessment using the OWASP LLM Top 10 (2025) + OWASP AI Testing Guide (AITG v1, Nov 2025) frameworks, plus OWASP MCP Top 10 runtime testing for agentic/MCP targets. Tests prompt injection, jailbreaks, system prompt leakage, sensitive data extraction, excessive agency, improper output handling, model extraction, content bias, evasion, membership inference, MCP token exposure, MCP command injection, and more. Uses four tools in combination: FuzzyAI (single-turn jailbreak fuzzing), PyRIT (multi-turn orchestrated attacks), Garak (probe-based vulnerability scanning), and promptfoo (plugin-based red-team evaluation). Each tool covers different OWASP categories; running them together gives systematic coverage. Includes a conditional MCP reconnaissance phase and a post-access AI infrastructure phase (chained from /post-exploit). Produces: OWASP LLM Top 10 + AITG + MCP coverage matrix, findings per category, architecture diagram of the AI system, PoCs for confirmed exploits. Chains into /gh-export for issue filing.
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。
Authorized exploit development and vulnerability research skill for lab environments, CTFs, owned software, crash analysis, memory corruption, exploitability assessment, fuzzing results, proof-of-concept design, and remediation. Use for defensive validation and education; avoid real-world weaponization, stealth, persistence, evasion, or unauthorized targets.
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。
API security automation skill for REST, GraphQL, gRPC, and WebSocket APIs. Covers OpenAPI/AsyncAPI ingestion, authenticated fuzzing, OWASP API Top 10 (BOLA, BFLA, mass assignment, SSRF), schema diffing, GraphQL introspection abuse, JWT and OAuth misuse, rate-limit and replay testing. Use to automate API assessments with safe, scoped, evidence-backed findings.
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。