Skill UI

This technique abuses the Active Directory's `msDS-KeyCredentialLink` attribute to inject attacker-controlled public keys (Shadow Credentials). After gaining write access (e.g., via BloodHound), the attacker uses tools like pyWhisker or Certipy to append their key. They then authenticate via PKINIT to recover the target's NT hash, achieving complete account takeover without the disruptive step of a password reset. Ideal for stealthy red-teaming engagements.

A guide to designing friction-free developer onboarding experiences. Learn best practices for implementing GitHub OAuth, generating immediate API keys, and utilizing progressive profiling to maximize signup conversion rates while respecting the developer's time. Focuses on moving users from zero to coding as fast as possible.

This utility detects and redacts sensitive personally identifiable information (PII) from screenshots and images. It can mask various data types, including IDs, credit card numbers, API keys, phone numbers, and emails. Crucially, all processing is conducted locally and offline, ensuring that sensitive data never leaves the user's machine. It is essential for secure debugging, data sharing, and analysis workflows.

A comprehensive tool for detecting and flagging Personally Identifiable Information (PII) within text, code, and configuration files. It is essential to use this before committing code, logging data, or generating model responses to prevent the accidental leakage of sensitive data such as emails, passwords, SSNs, or API keys.

This skill reviews prediction market, basket, oracle, and trading-agent workflows to ensure compliance, safety, data quality, and privacy. It must be run before any workflow handles user portfolio data, venue authentication, API keys, or trade planning to mitigate execution and regulatory risks across multiple domains.

This utility diagnoses and automatically repairs common issues within the Ruflo installation environment. It performs comprehensive health checks on core dependencies like Node.js, npm, and git, while also validating configurations, daemon status, memory databases, and API keys. It provides targeted commands to resolve issues related to memory initialization, daemon startup, and configuration resets, ensuring a stable operational environment.

This utility switches the active operational credential profile to manage different brands within a multi-client agency environment. It performs mandatory, deep validation of API keys, OAuth tokens, and environment variables before switching, ensuring that all subsequent platform operations (e.g., ad spending, reporting) are correctly routed to the target brand's account. It is crucial for preventing cross-client data leakage and maintaining audit integrity.

A specialized downstream skill for complex CTF challenges, focusing on cryptographic analysis, steganography, and mobile system forensics. It guides the user through recovering complex data chains, such as decoding blobs, tracing cryptographic transforms (keys, IVs, nonces), inspecting hidden media payloads, and analyzing mobile trust boundaries (e.g., APK/IPA signing logic, local storage, SSL pinning). This skill is designed to be used only after a main sandbox orchestrator has established the operational context.

This specialized skill is designed for in-depth security and forensic analysis of Windows secrets protected by DPAPI. It maps the entire lifecycle of encrypted credentials, tracing the flow from the initial protected blob or masterkey through the context unwrapping (e.g., user logon, machine context, domain backup keys) to the specific service that finally accepts the plaintext secret. Use this to prove the decisive access edge in a complex compromise scenario.

This specialized skill is designed for deep forensic analysis of compromised Linux environments, specifically tracing the sequence of credential usage (tokens, keys, service accounts) that leads to lateral movement or privilege escalation. It helps map the decisive path from a recovered artifact to an accepted replay mechanism, identifying the exact trust edge or capability abuse responsible for the host-to-host pivot.

This skill manages the loading and efficient caching of OpenMed clinical/biomedical Named Entity Recognition (NER) models. Models are downloaded once from the Hugging Face Hub, enabling full offline operation afterward. It supports model reuse across multiple calls, configuring cache directories, specifying devices (CPU/GPU), and handling various model identifiers (registry keys, full HF IDs, or local paths).