「verification」の検索結果

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.

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。

Exploit PHP type juggling vulnerabilities caused by loose comparison operators to bypass authentication, circumvent hash verification, and manipulate application logic through type coercion attacks.

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。

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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。

Configuring Google Cloud Identity-Aware Proxy (IAP) to enforce per-request identity verification for Compute Engine, App Engine, Cloud Run, and GKE services using access levels, context-aware policies, and programmatic access with service accounts.

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。

Optimize performance of the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration for AEMaaCS cloud workflows only, with cloud-specific baseline and runtime verification.

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。

Provide advisory guidance for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEMaaCS cloud workflows only, with public-doc citations and cloud-specific MCP verification plans. Use for conceptual questions such as `statfileslevel`, filter rules, URL decomposition, cache invalidation behavior, rewrite behavior, and security headers.

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。

Perform security audits for the Adobe Dispatcher Apache HTTP Server module and Apache HTTPD in AEMaaCS cloud workflows only, with cloud-specific hardening verification.

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。

Resolve one exact official/current documentation gap when the user requests source verification or a version-sensitive API/SDK/provider/framework question can materially change the current decision; do not trigger for every implementation decision, ordinary framework code, local business logic, or broad research.

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。

Perform direct, bounded browser inspection through the `browser.qa` capability when the user requests runtime UI evidence or one browser-specific claim needs DOM/accessibility/console/network/visual verification; do not trigger for every UI change, backend work, delegated QA, or durable E2E artifact routing.

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。

Implements API contract testing to ensure provider-consumer compatibility using Pact or similar tools. Prevents breaking changes with contract specifications and bi-directional verification. Use for "contract testing", "API contracts", "Pact", or "consumer-driven contracts".

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。

Systematically improves Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS) with prioritized fixes and verification. Use for "Core Web Vitals", "performance", "LCP", "INP", or "CLS".

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。

Use when a running Spark or DSH web service needs real-browser verification — page load, client-plugin boot errors, console errors, failed requests, or onboarding/dialog rendering — with the repository's own Playwright chromium.

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。

Use when a researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.

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。

Comprehensive methodology for auditing and exploiting TLS/SSL implementations and misconfigurations across network services and mobile applications. Covers protocol downgrade attacks including POODLE (CVE-2014-3566) against SSLv3 CBC padding, DROWN (CVE-2016-0800) cross-protocol attack leveraging SSLv2 export ciphers to decrypt TLS sessions, and FREAK (CVE-2015-0204) forcing RSA export-grade key exchange. Addresses BEAST (CVE-2011-3389) exploiting CBC IV predictability in TLS 1.0, CRIME (CVE-2012-4929) and BREACH targeting TLS-level and HTTP-level compression oracles respectively, and Heartbleed (CVE-2014-0160) for OpenSSL memory disclosure. Covers certificate validation bypass techniques for applications with improper hostname verification or chain validation, certificate pinning bypass using Frida and Objection for mobile application interception, HSTS bypass via NTP manipulation and subdomain exploitation, TLS 1.3 0-RTT replay attacks against non-idempotent endpoints, mutual TLS (mTLS) authentication a...

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。

Systematic false positive elimination for security findings. 6-gate verification, 13-item checklist, devil's advocate questioning. MANDATORY before any CVE submission.

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。

Production-grade AI trading agent for cryptocurrency markets with advanced mathematical modeling, multi-layer validation, probabilistic analysis, and zero-hallucination tolerance. Implements Bayesian inference, Monte Carlo simulations, advanced risk metrics (VaR, CVaR, Sharpe), chart pattern recognition, and comprehensive cross-verification for real-world trading application.

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。

Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.

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。

Store, verify, and manage AI data on the Ethereum blockchain (Base network) using the ERCData standard. Use when an agent needs to store data fingerprints on-chain, verify data integrity, create audit trails, manage access control for private data, or interact with the ERCData smart contract. Supports public and private storage, EIP-712 verification, snapshots, and batch operations.

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。

Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

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。

Build face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).

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。

Cloudflare Pages and Workers deployment checklist for wrangler deploys, secret audits, D1 migrations, Worker-compatible SDK checks, and browser-auth verification. Use when shipping Cloudflare changes to production. NOT for general CI/CD architecture, non-Cloudflare deployments, or post-launch UX QA.

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。

Practical incident-response runbook for a suspected or confirmed ComfyUI / GPU-daemon compromise. Triage, scope, contain, forensic collection, weight-integrity verification, rebuild from clean snapshot, postmortem. NOT for hygiene scans on a healthy box (use supply-chain-defense-for-ml-extensions), and NOT for runtime hardening of a fresh deployment (use gpu-hosted-asset-hardening).

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。

Produces a narrow-interval quality signal for a WinDAGs skill that a third party can verify without inspecting model weights or method internals. The mechanism is attribution-kNN over a tamper-evident outcome log (task→skills→accept/reject store), combined with a conformal-prediction calibration certificate that provides a formal coverage guarantee. Thompson/Beta sampling is explicitly rejected as a category error: it produces a selection signal for stationary i.i.d. rewards, not an attestation signal for context-dependent LLM output quality. The resulting bundle — outcome-log Merkle root + conformal threshold + optional TEE guardrail signature — constitutes a "narrow-interval trust" credential: verifiable, bounded, and internals-opaque.

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。

Design a normalized, machine-readable "work receipt" that answers what changed, why, by whom, and with what validation, for any AI-coding-agent task regardless of backend (Claude Code, Codex, Cursor, Aider, CI, or homegrown). Use when defining a receipt schema, normalizing heterogeneous agent logs into one evidence shape, gating PR merges on artifact-backed proof, or designing an OSS maintainer's fast-reject/fast-merge workflow. NOT for validating a DAG node's output against its own schema (use output-contract-enforcer), continuous runtime monitoring of a live coordination daemon (use runtime-verification-for-agents), or general Port Daddy claims/notes/salvage mechanics (use port-daddy-agent-skill).

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。