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「attacks」の検索結果

450 件 ・ 関連度順

概要と使いどころ

Exploit insecure handling of the HTTP Host header to poison password resets, generate cache poisoning vectors, or bypass internal routing restrictions. Use this skill when web applications dynamically generate URLs, links, or redirects based on the arbitrary Host header value supplied by the client rather than relying on a static, trusted server configuration.

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-huge242026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-huge242026年7月11日 更新

Exploit implementations of JSON Web Tokens (JWT) through algorithmic confusion (e.g., RS256 to HS256), "none" algorithm attacks, and signature stripping. Use this skill to forge administration tokens and achieve unauthenticated Account Takeover (ATO) on REST APIs and modern web applications.

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-huge242026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-huge242026年7月11日 更新

HTTP request smuggling exploits disagreements between a front-end proxy and back-end server on where one HTTP request ends and the next begins, using conflicting `Content-Length` and `Transfer-Encoding: chunked` headers (CL.TE, TE.CL, TE.TE variants). Enables bypassing access controls, cache poisoning, session hijacking, and capturing other users' requests. Detect via timing attacks, differential responses, and tools like Burp's HTTP Request Smuggler extension.

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-huge242026年7月11日 更新

Systematically bypass LLM safety filters and content moderation systems using advanced jailbreaking techniques. Use this skill when testing AI systems for safety alignment robustness, evaluating content moderation effectiveness, or conducting authorized AI red team assessments. Covers role-play attacks, few-shot manipulation, encoding bypass, multi-modal exploitation, and automated jailbreak discovery methods.

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-huge242026年7月11日 更新

Authentication and credential security assessment. Tests password brute-force, credential stuffing, password spraying, default credential testing, credential harvesting, lockout analysis, MFA bypass, OAuth/OIDC abuse, session token entropy, Kerberos attacks, and intelligent wordlist generation. Uses hydra, john, ncrack, medusa, cewl, crunch, netexec, impacket, kerbrute, and nuclei default-login templates. Covers OWASP A07:2021 Identification and Authentication Failures.

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-huge242026年7月11日 更新

Identify and exploit Cross-Site Request Forgery (CSRF) vulnerabilities by bypassing weak or flawed anti-CSRF token implementations, SameSite cookie attributes, and Origin/Referer headers. Use this skill when testing state-changing web application endpoints for session riding attacks. Covers token removal, token fixation, multipart manipulation, and chaining with XSS for complete bypass.

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-huge242026年7月11日 更新

Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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-huge242026年7月11日 更新

Analyze and detect synthetic media, including deepfake videos, AI-generated images, and cloned voice audio. Use this skill when investigating potential disinformation campaigns, verifying the authenticity of digital evidence, or assessing social engineering attacks leveraging synthetic media (e.g., vishing with voice clones, spear-phishing with deepfake video calls). Covers artifact analysis, frequency detection, metadata tracing, and automated detection tools.

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-huge242026年7月11日 更新

Execute sophisticated Data Extraction and Privacy Leakage attacks explicitly against Large Language Models (LLMs) to natively force the neural network entirely into organically regurgitating exact, verbatim strings of Highly Confidential Personally Identifiable Information (PII), proprietary source code, or copyrighted material categorically memorized intrinsically during its foundational pre-training phase.

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-huge242026年7月11日 更新

DNS rebinding attack playbook. Use when testing applications that trust DNS resolution for origin checks, interact with internal services from browser context, or when SSRF is not possible server-side but the target has client-side fetch/XHR to attacker-controlled domains.

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-huge242026年7月11日 更新

Clickjacking playbook. Use when testing whether target pages can be framed, whether X-Frame-Options or CSP frame-ancestors are properly configured, and whether UI redress attacks can trigger sensitive actions.

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-huge242026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-huge242026年7月11日 更新

Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), 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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Entry P1 category router for business logic testing. Use when workflow abuse, race conditions, pricing flaws, or multi-step state attacks matter more than parser-level input injection.

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-huge242026年7月11日 更新

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。

ShulkwiSEC/bb-huge242026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-huge242026年7月11日 更新

Identify and exploit flaws in API rate limiting enforcement. Use this skill when encountering HTTP 429 Too Many Requests errors during password brute-forcing, OTP validation, credential stuffing, or enumeration attacks. These bypasses leverage IP spoofing, parameter manipulation, and edge-case application 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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Active Directory security audit using the MITRE ATT&CK framework. Full domain enumeration, trust mapping, GPO analysis, ACL abuse paths, ADCS attacks (ESC1-ESC8), delegation abuse (constrained/unconstrained/RBCD), fine-grained password policies, LAPS deployment, service account security, and Kerberos configuration. Uses enum4linux-ng, netexec, impacket, ldapsearch, certipy-ad, bloodhound-python, and rpcclient. Produces attack path diagrams, prioritized risk register, and PoCs. 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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Execute advanced SQL Injection attacks to bypass WAFs and extract data from complex architectures. Use this skill for Boolean-Based Blind, Time-Based Blind, Second-Order SQLi, and Out-of-Band (OOB) SQLi across MySQL, PostgreSQL, MSSQL, and Oracle.

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-huge242026年7月11日 更新

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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Execute a complete Active Directory penetration test from initial enumeration to domain dominance. Use this skill for AD security assessments including LDAP enumeration, Kerberos attacks (Kerberoasting, AS-REP roasting), BloodHound attack path analysis, credential dumping with Mimikatz, lateral movement via PsExec/WMI/DCOM, DCSync for NTDS extraction, and Golden/Silver ticket forging. Covers the full kill chain from domain user to domain admin.

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-huge242026年7月11日 更新

Identify and simulate Data Poisoning attacks aimed at degrading or skewing an AI model's accuracy. This skill focuses on Adversarial Machine Learning concepts where attackers inject malicious or mislabelled data points into training or fine-tuning datasets (e.g., feedback loops) to bias the AI.

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-huge242026年7月11日 更新