「enforcement」の検索結果

Enforce Kubernetes admission policies using OPA Gatekeeper with ConstraintTemplates, Rego rules, and the Gatekeeper policy library.

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Sign and verify container image provenance using Sigstore Cosign with keyless OIDC-based signing, attestations, and Kubernetes admission enforcement.

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Tests API rate limiting implementations for bypass vulnerabilities by manipulating request headers, IP addresses, HTTP methods, API versions, and encoding schemes to circumvent request throttling controls. The tester identifies rate limit headers, Belirle:s enforcement mechanisms, and attempts bypasses including X-Forwarded-For spoofing, parameter pollution, case variation, and endpoint path manipulation. Maps to OWASP API4:2023 Unrestricted Resource Consumption. Activates for requests invol...

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Implements input and output validation guardrails for LLM-powered applications to prevent prompt injection, data leakage, toxic content generation, and hallucinated outputs. Builds a security validation pipeline using NVIDIA NeMo Guardrails Colang definitions, custom Python validators for PII Tespit and content policy enforcement, and the Guardrails AI framework for structured output validation. The guardrails system intercepts both user inputs (blocking injection attempts, stripping PII, ...

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Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.

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Deploying Palo Alto Networks Prisma Access for SASE-based zero trust network access using GlobalProtect agents, ZTNA Connectors, security policy enforcement, and integration with Strata Cloud Manager for unified security management.

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Simulates man-in-the-middle attacks using Ettercap, mitmproxy, and Bettercap in authorized environments to intercept, analyze, and modify network traffic for testing encryption enforcement, certificate validation, and detection capabilities.

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Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

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Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.

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Run TypeScript type checking after file edits and immediately flag type errors before moving on. Uses Cursor hooks for automatic enforcement.

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Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

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Design workflow — create design systems, DESIGN.md, and design tokens with anti-pattern enforcement and accessibility checks

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Audit the project's agent / LLM instruction files for vague rules, missing examples, drifted compliance, and mechanical-enforcement opportunities.

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Implement Adobe-specific lint rules, CI policy checks, and runtime guardrails covering credential scanning (p8_ patterns), Firefly content policy pre-screening, PDF Services quota enforcement, and OAuth scope validation. Trigger with phrases like "adobe policy", "adobe lint", "adobe guardrails", "adobe eslint", "adobe content policy".

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デザイントークンを使わずに直書きされた色・余白・フォントサイズ・角丸・シャドウを検出する。Figma Variables / Tailwind config / CSS custom properties のルールに違反する実装を指摘する。

Run the refactor workflow — mandatory architectural justification, test verification, risk-based implementation, and scope enforcement.

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Establish and enforce coding standards, best practices, and architectural patterns across the codebase using linters, formatters, and code review processes. Use when setting up ESLint/Prettier, configuring linting rules, creating code style guides, implementing pre-commit hooks, establishing naming conventions, enforcing TypeScript strict mode, maintaining consistency, conducting architecture reviews, or defining team coding standards.

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Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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Runtime security for agent skills — prevents state corruption, skill overwrite attacks, denial of service, and enforces provenance tracking and no-go repo management. Load as part of the secure-* skill sequence whenever an agent processes external content or writes to the skill store. Also load when the user asks to check for state corruption, prevent skill overwrite, manage no-go repos, check provenance, audit runtime security, detect DoS patterns, or protect the skill store. Covers Issues 6, 9, 10 from the agent security threat model: instruction hierarchy enforcement, state corruption and skill overwrite, and denial of service prevention.

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Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.

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Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.

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Agent Workforce Orchestration: Hybrid Human+AI Teams. Build agent-led workforce orchestration: capability matching, escrow-based payments for AI agents and human gig workers, unified reputation scoring, SLA enforcement, dispute resolution, and compliance reporting. Includes detailed Python code examples for every pattern.

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When the user wants to monitor brand mentions, detect trademark infringement, or set up brand monitoring. Also use when the user mentions "brand monitoring," "brand watch," "trademark watch," "brand mentions," "impersonation detection," "counterfeit detection," or "brand abuse monitoring." For enforcement, use brand-protection.

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。