CSRF testing playbook. Use when reviewing state-changing web flows, anti-CSRF defenses, SameSite behavior, JSON CSRF, login CSRF, and OAuth state handling.
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。
297 件 ・ 関連度順
概要と使いどころ
CSRF testing playbook. Use when reviewing state-changing web flows, anti-CSRF defenses, SameSite behavior, JSON CSRF, login CSRF, and OAuth state handling.
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 debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
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。
Validate at every layer data passes through to make bugs impossible
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 comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
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。
Routes any game-development request to the right specialized skill(s): it detects the engine (Godot, Unity, Unreal, Bevy, Phaser, PixiJS, three.js, LÖVE, pygame, Roblox) and the task, then reads the chosen skill before acting. Use to make a game or to decide which skill applies — for players, levels, enemies, shaders, art direction, sprites, tiles, textures, 3D assets, UI/UX, cameras, game feel, physics, input, audio, saving, multiplayer, AI, dialogue, procedural generation, or performance, for genres (platformer, roguelike, RPG, FPS, tower-defense, card game, visual novel, survival-crafting, puzzle), and for shipping (game jam, Steam, itch). Start here when unsure which gamedev skill to use.
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。
Run the pre-flight checklist before an agent drives a browser — the untrusted-web-content threat (every page is attacker-controllable), the credential and session-cookie exposure, the action-confirmation gates for purchases and posts, and the sandboxing that limits the damage. Use when asked let my agent browse safely, is it safe to give the agent computer/browser use, guardrails before the agent uses my browser, or review my browser agent's setup. Produces the sandbox decision, the content-injection defenses, the action gates, and the credential-isolation rules.
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 anticipating the objections a sophisticated American Economic Journal: Applied Economics (AEJ: Applied) referee will raise, so a manuscript pre-empts them before submission or addresses them in revision. Plans the defense; it does not draft the response letter (aeja-rebuttal) or run the submission preflight (aeja-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。
Use when choosing suggested and opposed referees for an Advanced Materials submission and pre-empting the objections materials reviewers most often raise. Plans referee selection and objection defense; does not write the manuscript or the rebuttal.
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 revising an ACM CCS paper for a precise threat model, calibrated attack/defense claims, 12-page ACM sigconf compression, double-blind wording, adaptive-evaluation honesty, and the security house style that survives an adversarial SIGSAC program committee.
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 positioning an ACM CCS submission against the security big-four and specialist literature, including arXiv preprints, prior CCS/S&P/USENIX/NDSS papers, concurrent disclosures, CVE and advisory records, and the attack-and-defense lineage that a SIGSAC program committee expects to see credited.
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 strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.
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 designing or auditing ACM CCS experiments, attack demonstrations, adaptive-attack defense evaluations, security measurements, baselines, overhead and cost reporting, ablations, and claim-to-evidence fit, with emphasis on evidence that survives an adversarial program committee rather than leaderboard wins.
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 packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable, and Results Reproduced — covering what security evaluators inspect, how to make attacks and defenses turnkey, and how to justify withheld artifacts.
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 drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.
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 somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.
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。
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
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。
Defend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.
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。
STRIDE threat modeling, DREAD risk scoring, secret detection, and secure architecture design. Use when conducting threat models, reviewing code for vulnerabilities, designing defense-in-depth, or scanning for hardcoded secrets.
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。
Audits legal AI skills, prompts, workflows, MCP/tool instructions, and agent packages for prompt injection, malicious instructions, unsafe scripts, suspicious metadata, credential exposure, exfiltration paths, persistence mechanisms, and supply-chain risk. Use before installing, importing, publishing, promoting, modifying, or trusting third-party or generated AI skills and legal workflows. Do not use as a generic code review unless skill trust, workflow safety, prompt injection, or supply-chain hygiene is in scope.
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。
Guides security professionals in implementing defense-in-depth security architectures, achieving compliance with industry frameworks (SOC2, ISO27001, GDPR, HIPAA), conducting threat modeling and risk assessments, managing security operations and incident response, and embedding security throughout the SDLC.
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。
Expert blueprint for AI pathfinding (tower defense, RTS, stealth) using NavigationAgent2D/3D, NavigationServer, avoidance, and dynamic navigation mesh generation. Use when implementing enemy AI, NPC movement, or obstacle avoidance. Keywords NavigationAgent2D, NavigationRegion2D, pathfinding, NavigationServer, avoidance, baking, NavigationObstacle.
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。
Expert patterns for managing combat waves, difficulty scaling, and automated enemy spawning in Godot 4. Use when building wave-based shooters, tower defense, or arena games.
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。
Validate at every layer data passes through to make bugs impossible
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 for 小北在读研 / XiaoBei academic paper-to-PPT workflows: generate thesis-defense or project-report decks from uploaded papers, literature, reports, technical documents, and optional PPTX visual templates. Produces a source-grounded outline, an imagegen visual scheme, one complete bitmap per slide, an imagegen provenance manifest, and an image-only PPTX. Do not use when the user needs editable slide text or native editable charts.
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。