Tests and exploits deep link (URL scheme and App Link) vulnerabilities in Android and iOS mobile applications to identify unauthorized access, data injection, intent hijacking, and redirect manipulation. Use when assessing mobile app attack surface through custom URI schemes, Android App Links, iOS Universal Links, or intent-based navigation. Activates for requests involving deep link security testing, URL scheme exploitation, mobile intent abuse, or link hijacking.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Identifying and exploiting insecure deserialization vulnerabilities in Java, PHP, Python, and .NET applications to achieve remote code execution during authorized penetration tests.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Identifies and exploits SQL injection vulnerabilities in web applications during authorized penetration tests using manual techniques and automated tools like sqlmap. The tester detects injection points through error-based, union-based, blind boolean, and time-based blind techniques across all major database engines (MySQL, PostgreSQL, MSSQL, Oracle) to demonstrate data extraction, authentication bypass, and potential remote code execution. Activates for requests involving SQL injection testing, SQLi exploitation, database security assessment, or injection vulnerability verification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Detect and exploit race condition vulnerabilities in web applications using Turbo Intruder's single-packet attack technique to bypass rate limits, duplicate transactions, and exploit time-of-check-to-time-of-use flaws.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Identifies and exploits insecure local data storage vulnerabilities in Android and iOS mobile applications including unencrypted databases, world-readable files, insecure SharedPreferences, plaintext credential storage, and improper keychain/keystore usage. Use when performing mobile penetration testing focused on OWASP M9 (Insecure Data Storage) or assessing compliance with MASVS-STORAGE requirements. Activates for requests involving mobile data storage security, local storage exploitation, SharedPreferences analysis, or mobile data leakage assessment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Detect and exploit JavaScript prototype pollution vulnerabilities on both client-side and server-side applications to achieve XSS, RCE, and authentication bypass through property injection.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Deploy Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points. This skill covers Duo integration methods, adaptive authentication policies, device trust
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Deploying Cloudflare Access with Cloudflare Tunnel to provide zero trust access to self-hosted and private applications, configuring identity-aware access policies, device posture checks, and WARP client enrollment for VPN replacement.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Conducts penetration testing of iOS and Android mobile applications following the OWASP Mobile Application Security Testing Guide (MASTG) to identify vulnerabilities in data storage, network communication, authentication, cryptography, and platform-specific security controls. The tester performs static analysis of application binaries, dynamic analysis at runtime, and API security testing to evaluate the complete mobile attack surface. Activates for requests involving mobile app pentest, iOS security assessment, Android security testing, or OWASP MASTG assessment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Configure AWS Verified Access to provide VPN-less zero trust network access to internal applications using identity and device posture verification with Cedar policy language.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Establish SAML 2.0 identity federation between on-premises Active Directory and Azure AD (Microsoft Entra ID) for seamless cross-domain authentication and SSO to cloud applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Performs runtime mobile security exploration of iOS applications using Objection, a Frida-powered toolkit that enables security testers to interact with app internals without jailbreaking. Use when assessing iOS app security posture, bypassing client-side protections, dumping keychain items, inspecting filesystem storage, and evaluating runtime behavior. Activates for requests involving iOS security testing, Objection runtime analysis, Frida-based iOS assessment, or mobile runtime exploration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
aniket2348823/Vul-Agent☆ 22026년 6월 9일 업데이트
Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
sathishssj3/Stereix-Engine☆ 22026년 10월 4일 업데이트
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
sathishssj3/Stereix-Engine☆ 22026년 10월 4일 업데이트
HTTP parameter pollution (HPP) checklist: duplicate parameter injection, backend vs frontend parsing differences, WAF bypass via HPP, server-side vs client-side HPP, and practical exploitation patterns. Use when testing web applications for parameter handling flaws.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ajtazer/heckit☆ 22026년 10월 7일 업데이트
Insecure deserialization exploitation across Java, PHP, .NET, Python, Node.js, and Ruby. Covers gadget chain construction with ysoserial/phpggc/ysoserial.net, ObjectInputStream and BinaryFormatter sink identification, pickle __reduce__ RCE, phar:// wrapper abuse, Jackson polymorphic typing, Json.NET TypeNameHandling, ViewState tampering, node-serialize IIFE injection, Ruby Marshal.load and YAML.load gadgets, framework-specific chains for Spring/Hibernate/Laravel/Symfony, modern attack surfaces including Kubernetes admission webhooks and message queue consumers, WAF bypass through encoding layers and content-type manipulation, and serialVersionUID/JMX/RMI vectors. Activate when the engagement involves deserialization sinks, serialized data in cookies or request bodies, gadget chain development, magic method abuse, ysoserial payload generation, or any review of marshalling and unmarshalling logic in target applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ajtazer/heckit☆ 22026년 10월 7일 업데이트
Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building c...
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ajtazer/heckit☆ 22026년 10월 7일 업데이트
This skill should be used when the user asks to "test for HTML injection", "inject HTML into web pages", "perform HTML injection attacks", "deface web applications", or "test content injection vulnerabilities". It provides comprehensive HTML injection attack techniques and testing methodologies.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
danstrem2/clawdbot-skill-master-pack☆ 22026년 2월 1일 업데이트
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
danstrem2/clawdbot-skill-master-pack☆ 22026년 2월 1일 업데이트
This skill should be used when the user asks to "test for insecure direct object references," "find IDOR vulnerabilities," "exploit broken access control," "enumerate user IDs or object references," or "bypass authorization to access other users' data." It provides comprehensive guidance for detecting, exploiting, and remediating IDOR vulnerabilities in web applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
danstrem2/clawdbot-skill-master-pack☆ 22026년 2월 1일 업데이트
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
danstrem2/clawdbot-skill-master-pack☆ 22026년 2월 1일 업데이트
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
danstrem2/clawdbot-skill-master-pack☆ 22026년 2월 1일 업데이트