Hunt JSON Web Token (JWT) vulnerabilities — alg=none bypass, RS256→HS256 key confusion, weak HMAC secret cracking, kid path traversal, JWKS injection, jku/x5u header attacks, embedded JWK confusion, expired-token acceptance, claim mutability, and token replay. Use when an app uses JWT for authentication or stateless sessions.
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。
0xGhostCAT/claude-ai-cyber-security-skills☆ 422026年6月3日 更新
Hunt web cache poisoning, CDN cache poisoning, and cache deception attacks. Use when target uses a CDN (Cloudflare, Akamai, Fastly, AWS CloudFront) or has Varnish/nginx caches and you want to identify cache key flaws that let attackers serve malicious content to other users.
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。
0xGhostCAT/claude-ai-cyber-security-skills☆ 422026年6月3日 更新
Use when the user asks about supply-chain attacks, third-party / vendor compromise (SolarWinds, Kaseya, 3CX, MOVEit, XZ-utils-style), software-bill-of-materials risks, or library / dependency-injection attacks. Self-updating knowledge cell.
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。
Liberty91LTD/cti-skills☆ 272026年9月30日 更新
MITRE ATT&CK local dataset reference. Query techniques, groups, software, and mitigations from the local enterprise-attack.json.
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。
Liberty91LTD/cti-skills☆ 272026年9月30日 更新
Use when you need to answer "which attacker techniques do our controls actually stop, and how well?", "what controls should I have for this threat?", or "what telemetry should I collect to detect it?" — joining a customer's or your own security control baseline to ATT&CK techniques using a public, versioned evidence base of 9,545 control-to-technique mappings from six sources. Produces four ranked lists (addressed strongly, addressed weakly, real gaps, and techniques no control anywhere addresses). Use for control gap analysis, security programme prioritisation, board reporting on coverage, or the Resistance Strength side of a FAIR risk assessment. Invoke after /threat-actor-profiling or /lookup-liberty91 has produced a technique list.
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。
Liberty91LTD/cti-skills☆ 272026年9月30日 更新
SAML SSO assertion attack playbook. Use when testing signature validation, assertion wrapping, audience restrictions, ACS handling, XML trust boundaries, and enterprise SSO 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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference attacks.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Deploy an Evil Twin (Rogue Access Point) to clone a legitimate Wi-Fi network's SSID and MAC address. By combining this with targeted deauthentication attacks, an attacker aggressively forces nearby victims to silently connect to the malicious AP, enabling pervasive Man-in-the-Middle (MitM), captive portal phishing, and credentials interception.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
RSA attack playbook for CTF and real-world cryptanalysis. Use when given RSA parameters (n, e, c) and need to recover plaintext by exploiting weak keys, small exponents, shared factors, or padding oracles.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Exploit JSON Web Tokens (JWT) by implementing the 'None' algorithm attack. This skill details how to bypass authentication mechanisms when a server improperly accepts JWTs with the `alg` header set to `none`, allowing attackers to forge tokens without a valid signature.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
JWT and OAuth token attack playbook. Use when validating token trust, signing algorithms, key handling, claim abuse, bearer flows, and OAuth account-binding weaknesses.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
HTTP/2 protocol-specific attack playbook. Use when the target supports HTTP/2 and you need to exploit binary framing, HPACK compression, h2c upgrade smuggling, pseudo-header injection, stream multiplexing abuse, or H2→H1 downgrade translation 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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Execute a Kerberoasting attack to extract Service Principal Name (SPN) ticket hashes from Active Directory and crack them offline. This allows an attacker with any valid domain credentials to escalate privileges by obtaining the plaintext password of highly-privileged service accounts.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Lattice-based cryptanalysis playbook. Use when attacking RSA via Coppersmith small roots, recovering DSA/ECDSA nonces from bias, solving knapsack problems, or applying LLL/BKZ reduction to cryptographic constructions.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Exploit GraphQL API architectural features to execute highly efficient brute-force, Credential Stuffing, and Denial of Service (DoS) attacks. Utilize Query Batching and Alias injection to bypass rate limits by packing thousands of requests into a single HTTP POST request.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Use when hunting GitHub Actions cache poisoning vulnerabilities where an attacker can inject malicious content into the CI/CD cache and have it restored by a privileged downstream workflow. Trigger on: "cache poisoning", "actions/cache", "actions/setup-node", "node_modules cache", "GitHub Actions cache", "pnpm cache", "LRU eviction", "10GB limit", "Cacheract", "poisoned cache", "workflow cache attack", supply chain via CI cache, "ng-renovate", "cache stuffing", scheduled workflow cache restore, shared cache key, "hashFiles package.json", cross-workflow cache, PR workflow release workflow same key, "npm install prefer-offline", Cacheract, Gato-X, supply chain npm token.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
CORS misconfiguration allows attacker-controlled origins to read sensitive cross-origin responses when servers echo the `Origin` header in `Access-Control-Allow-Origin` or set it to `*` with `Access-Control-Allow-Credentials: true`. Detect via `Origin: https://attacker.com` reflection in `Access-Control-Allow-Origin` response header, wildcard `*` on credentialed endpoints, and null origin acceptance. Tools: OWASP ZAP, Burp Suite, manual `fetch()` with `credentials: include`.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Container and Kubernetes security assessment. Tests container escape vectors, Docker/containerd socket exposure, K8s RBAC misconfigurations, pod security violations, exposed API servers, etcd access, service account token abuse, image layer secrets, private registry attacks, SSRF to metadata services, cross-namespace network bypass, CIS benchmarks, crypto miner detection, resource exhaustion, and admission controller gaps. Both external and internal (compromised pod) perspectives. Uses trivy, kube-bench, kubectl, nuclei, dive, amicontained, and docker-bench-security. Covers OWASP Kubernetes Top 10 and all 22 Kubernetes Goat attack scenarios.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Audit and attack session cookies via missing Secure/HttpOnly/SameSite attributes, overly broad Domain/Path scope, non-expiring persistent cookies, absent __Host- and __Secure- prefixes, browser cache leakage (Cache-Control: no-store missing), session token predictability via Burp Sequencer analysis, server-side session not invalidated on logout, and SSO single-logout bypass. Tools: Burp Suite Repeater/Sequencer, OWASP ZAP, EditThisCookie, Tamper Data, Cookiebro.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Execute AS-REP Roasting to extract and crack the NTLM hashes of Active Directory user accounts that have the "Do not require Kerberos preauthentication" flag explicitly enabled. This attack generates a recoverable Ticket Granting Ticket (TGT) without requiring the attacker to authenticate first.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新
Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.
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。
ShulkwiSEC/bb-huge☆ 242026年7月11日 更新