Entry P1 category router for reconnaissance and methodology. Use when mapping scope, discovering assets, fingerprinting technology, building endpoint inventory, and choosing the first high-value security testing path.
中文简介正在准备中。当前显示原文说明。
Reverse shell techniques playbook. Use when establishing remote shells including language one-liners, encrypted shells (OpenSSL/socat/ncat), web shells, PTY upgrades, file transfer methods, PowerShell shells, and Windows payload generation.
中文简介正在准备中。当前显示原文说明。
Exploit validation and exploitation using Metasploit Framework. Runs in a dedicated Docker container (separate from Kali). Validates CVEs discovered by nuclei, nikto, or other scanners with actual exploit modules. Covers exploit selection, payload configuration, exploitation, and post-exploitation pivoting. Uses msfconsole, msfvenom, and the Metasploit module database. Chains from /pentester, /analyze-cve, or /post-exploit when exploitable CVEs are confirmed.
中文简介正在准备中。当前显示原文说明。
Use when testing APIs and web frameworks for mass assignment vulnerabilities where user-controlled request body fields are bound directly to model attributes without a field allowlist. Trigger on: ORM update/create endpoints, REST APIs accepting JSON body, Rails strong parameters, Django model forms, Laravel fillable/guarded, Node.js Mongoose/Sequelize, PUT/PATCH requests, registration endpoints, profile update endpoints, GraphQL mutations. Detects privilege escalation via role/admin/isAdmin fields, plan upgrades via subscription fields, and horizontal access via ownerId/userId injection.
中文简介正在准备中。当前显示原文说明。
Detects authentication and biometric bypass vulnerabilities in mobile apps (Android/iOS). Trigger on: BiometricPrompt, LocalAuthentication, LAContext, evaluatePolicy, CryptoObject, Android Keystore, Secure Enclave, kSecAccessControlBiometryCurrentSet, userAuthenticationValidityDurationSeconds, confirmCredentials, biometric fallback, PIN bypass, passive authentication, enrolled biometrics detection, Frida hook auth, jailbreak bypass, TouchID, FaceID, fingerprint. Covers MASVS-AUTH-1/2/3.
中文简介正在准备中。当前显示原文说明。
Exploit weak password reset and change flows via CSRF on reset forms, cross-user password modification by swapping username parameters, token predictability in reset links, reset displaying old password in plaintext (revealing weak storage), missing current-password verification on change forms, and session hijacker lockout via passwordless change. Test with Burp Suite, OWASP ZAP following OWASP Forgot Password Cheat Sheet.
中文简介正在准备中。当前显示原文说明。
macOS security bypass playbook. Use when targeting macOS endpoints and need to bypass TCC, Gatekeeper, SIP, sandbox, code signing, or entitlement-based protections during authorized red team or pentest engagements.
中文简介正在准备中。当前显示原文说明。
Identify and exploit logical flaws in OAuth 2.0 and OpenID Connect workflows. Use this skill when testing "Sign in with Google/Facebook/Apple" features, focusing on Authorization Code interception, Implicit flow token leakage, standard CSRF bypassing via missing `state` parameters, and redirect logic flaws.
中文简介正在准备中。当前显示原文说明。
Open redirect playbook. Use when URL parameters, form actions, or JavaScript sinks control navigation targets and may redirect users to attacker-controlled destinations.
中文简介正在准备中。当前显示原文说明。
macOS process injection playbook. Use when you need to inject code into running or launching macOS processes via dylib hijacking, DYLD environment variables, XPC exploitation, Mach port manipulation, or Electron/Chromium abuse.
中文简介正在准备中。当前显示原文说明。
Generate sophisticated initial access payloads designed to bypass email gateways and endpoint antivirus systems while executing Command and Control (C2) agents. Use this skill to craft malicious LNKs, ISOs, Weaponized Office Documents, and HTML Smuggling techniques for Red Team campaigns.
中文简介正在准备中。当前显示原文说明。
Exploit Mass Assignment vulnerabilities in APIs and web frameworks to inject unauthorized parameters. This skill details how attackers uncover hidden fields and manipulate JSON or HTTP bodies to elevate privileges or tamper with data logic.
中文简介正在准备中。当前显示原文说明。
Perform forensic analysis of the macOS Unified Logging System (ULS) to investigate system events, application crashes, kernel panics, and potential indicators of compromise (IoCs) such as persistence mechanisms or unauthorized access.
中文简介正在准备中。当前显示原文说明。
Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening assessment.
中文简介正在准备中。当前显示原文说明。
Detects code quality vulnerabilities in mobile apps (Android/iOS). Trigger on: SQL injection in SQLite, JavaScript injection in WebViews, intent injection, unsafe deserialization, NSKeyedUnarchiver, NSCoding, Java serialization, Parcelable, buffer overflow, JNI native code, PIE disabled, NX disabled, stack canary absent, RELRO, ARC disabled, third-party library CVE, vulnerable dependency, outdated SDK, targetSdkVersion, update enforcement missing, implicit Intent, URL loading in WebView, object persistence, memory corruption, OWASP dependency check. Covers MASVS-CODE-1/2/3/4.
中文简介正在准备中。当前显示原文说明。
Exploit an application's absolute trust in its underlying LLM (Overreliance). Use this skill to induce critical "hallucinations" (confident falsehoods) that cause downstream logical systems or automated agents tracking the LLM's output to make destructive actions or grant unauthorized access.
中文简介正在准备中。当前显示原文说明。
Identify Open Redirect vulnerabilities where applications route users to arbitrary external URLs based on unvalidated input. Prove maximum impact by chaining Open Redirects with OAuth token theft, SSRF, or Phishing, graduating this typically low-risk finding into a high-severity report.
中文简介正在准备中。当前显示原文说明。
Exploit AI applications using Indirect Prompt Injection. This skill focuses on hiding malicious instructions within data sources (web pages, documents, emails) that the LLM processes, causing the AI to execute unintended actions or leak data without direct user interaction.
中文简介正在准备中。当前显示原文说明。
Comprehensive LLM security testing prompts for bias detection, data leakage, alignment testing, and adversarial prompt resistance.
中文简介正在准备中。当前显示原文说明。
NTLM relay and authentication coercion playbook. Use when capturing and relaying NTLM authentication to escalate privileges via SMB, LDAP, HTTP, or MSSQL relay targets, combined with PetitPotam, PrinterBug, and other coercion methods.
中文简介正在准备中。当前显示原文说明。
Detects sensitive data stored insecurely on mobile devices (Android/iOS). Trigger on: SharedPreferences, NSUserDefaults, SQLite, Room DB, DataStore, Core Data, Keychain misconfiguration, external storage, backup exposure, plaintext files, unencrypted databases, adb backup, iCloud backup, NSFileProtection, EncryptedSharedPreferences, SQLCipher, allowBackup, FLAG_SECURE, keyboard cache, sensitive logs. Covers MASVS-STORAGE-1 (local storage) and MASVS-STORAGE-2 (exposure to unauthorized actors).
中文简介正在准备中。当前显示原文说明。
Mobile SSL pinning bypass playbook. Use when intercepting HTTPS traffic from mobile applications that implement certificate pinning, public key pinning, or SPKI hash pinning on Android and iOS, including React Native, Flutter, and Xamarin frameworks.
中文简介正在准备中。当前显示原文说明。
Identify and exploit vulnerabilities in the AI Supply Chain by injecting malicious models, datasets, or dependencies. Use this skill to simulate advanced persistent threats (APTs) compromising Hugging Face repositories, manipulating pre-trained weights (Model Poisoning), and exploiting insecure deserialization during model loading (e.g., Pickle files).
中文简介正在准备中。当前显示原文说明。
Extract sensitive training data (PII, API keys, intellectual property, or code) directly from a deployed Large Language Model (LLM). This AI Red Teaming skill focuses on forcing models to regurgitate memorized, unredacted data from their massive internet-scraped datasets through repetition attacks, prefix continuation, and context window manipulation.
中文简介正在准备中。当前显示原文说明。