Results for “wit-ai”

Guides AI system compliance with the EU AI Act through six article-cited questions covering prohibited practices, risk classification, conformity assessment, role obligations, transparency, and GPAI systemic risk.

Use to design and audit how customers are told they are interacting with AI, or that AI was involved in a decision about them, and to evidence that it happened. Trigger for "do we tell customers it's a bot", "AI disclosure requirements", "should the bot say it's not human", "customer asked if they were talking to a person", AI transparency obligations, or evidencing that an AI-assisted decision was explained.

Execute email operations with platform-specific optimizations and security protocols.

Crl reference tool. Use when working with crl in security contexts.

Web application security scanner with proxy and active/passive scanning

Tls reference tool. Use when working with tls in security contexts.

Add governance, safety, and trust controls to AI agent systems with policy enforcement, intent classification, and audit trails.

Analyze text and images for harmful content using Azure AI Content Safety, with customizable blocklists and severity thresholds.

Captures WPA/WPA2 handshakes and performs offline password cracking using aircrack-ng, hashcat, and dictionary attacks during authorized wireless security assessments to evaluate passphrase strength and wireless network security posture.

中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.

Documents AI-built apps with architecture, permissions, secrets, and test coverage maps to make them reviewable before shipping.

Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness, providing detailed improvement recommendations with frameworks, testing methodologies, and educational content.

Provides regulatory compliance assessments across data privacy, AI ethics, and localization laws, producing structured outputs with risk scores and remediation status.

Security vulnerability assessment identifying OWASP risks, injection vectors, authentication issues, and data exposure with severity classification.

Analyze text and images for harmful content using Azure AI Content Safety SDK for Java. Supports hate, violence, sexual content, and self-harm detection with blocklist management.

Guides authorized Wi-Fi security assessments including handshake capture, PMKID collection, rogue AP detection, and offline password policy evaluation using aircrack-ng, hashcat, and Wireshark.

Assess AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, and agent tool abuse, with MITRE ATLAS mapping and guardrail recommendations.

Audit a codebase, UI, or copy for machine-generated tells across prose, visual/UI, code, and structure/IA, then produce a phased de-slop burndown. Use when the user says "feels AI-generated", "looks like AI slop", "reads like ChatGPT", "feels generic/soulless", or wants an authenticity/voice pass before launch.

Implements AI safety guardrails including input validation, output filtering, robustness testing, human oversight, and monitoring to prevent harmful outputs and ensure system reliability.

Authenticate AI agents with services using ERC-8004 onchain identity via Sign-In With Agent (SIWA).

Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

Safety guardrails for autonomous agents. Intercepts destructive actions and vets skills, requires structured approval before irreversible operations, with CLI-backed cryptographic audit trails and policy enforcement.

Automate multi-turn adversarial conversations against LLM agents using Microsoft PyRIT, including Crescendo and Tree-of-Attacks-with-Pruning (TAP) attack chains with scorer feedback loops.

Manages and analyzes Clerk authentication resources, including users, organizations, and sessions, with commands for user growth, auth health, and membership review.

Analyze AWS GuardDuty findings, detectors, suppression rules, and member accounts with parallel execution and anti-hallucination guardrails.

Modern authentication and security patterns for web applications. Expert in JWT tokens, OAuth2 flows, session management, RBAC, MFA, API security, and zero-trust architectures. Framework-agnostic patterns that work with any tech stack.

Scan and audit AI agent skills for security risks before installation, producing a PASS/WARN/FAIL verdict with findings and remediation guidance.

Pressure-tests any compliance program with six forcing questions before adopting a new framework, planning an audit cycle, or signing off on certification readiness.

Create agent user identities in Microsoft Entra ID to enable AI agents to act as digital workers with user capabilities in Microsoft 365.

Reads and audits Auth0 tenant configuration, applications, connections, rules, actions, users, and logs using the Management API with a discovery-first, read-only approach.