'metadata' 검색 결과

Detects typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Identifying and exploiting SSRF vulnerabilities to access internal services, cloud metadata, and restricted network resources during authorized penetration tests.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill outlines methodologies for performing authorized penetration testing against AWS, Azure, and GCP cloud environments. It covers understanding the shared responsibility model for testing scope, leveraging cloud-specific attack tools like Pacu and ScoutSuite, exploiting IAM misconfigurations, testing for SSRF to cloud metadata services, and reporting findings aligned to MITRE ATT&CK Cloud matrix.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze the NTFS Master File Table ($MFT) to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space using MFTECmd, analyzeMFT, and X-Ways Forensics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze Microsoft Outlook PST and OST files for email forensic evidence including message content, headers, attachments, deleted items, and metadata using libpff, pst-utils, and forensic email analysis tools for legal investigations and incident response.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Start AEM Workflows on AEM as a Cloud Service using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, or passing initial metadata and payload to a workflow instance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate JSON-LD structured data for AEM Edge Delivery Services pages. Analyzes page content and metadata to determine the appropriate schema.org types, extracts relevant properties, and produces validated JSON-LD snippets ready for implementation in head.html or scripts.js. Use when adding rich results support, improving search appearance, or auditing existing structured data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate structured HTML from authoring analysis for AEM Edge Delivery Services. Creates section structure, applies block tables, handles metadata, and manages images folder.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reference for producing Adobe Document Authoring (DA, da.live) and Edge Delivery Services (EDS, aka aem.live/Helix) compatible content. Use whenever generating HTML for DA upload, uploading media binaries to DA, publishing to aem.live, or driving the DA admin API (auth, source PUT, preview/publish). Covers block HTML format (canonical div-class form and accepted table alternate), section structure, page/section metadata, icons, links, images, default content, document skeleton constraints, block cell content normalization, the DA Source API contract, IMS auth, media storage, supported formats, Media Bus vs Content Bus delivery, and silent-failure rules that corrupt content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Compare two versions of an AEM Edge Delivery Services page to identify what changed. Fetches preview vs live, or two different URLs, and produces a detailed content diff showing added, removed, and modified content, metadata, and blocks. Use when reviewing changes before publishing, auditing content modifications, or tracking content evolution.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Edits an existing blog post's content or metadata in local MD files. Use when the user wants to modify, update, or improve a blog post.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run a non-destructive open-source, npm, or public release readiness checklist covering package metadata, provenance, license, internal artifact exposure, and dry-run evidence; complements security, shipping, and sanitizer reviews, and must not publish, delete, rewrite history, or mutate release state.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Converts documents into clean, chunked datasets suitable for embeddings and vector search. Produces chunked JSONL files with metadata, deduplication logic, and quality checks. Use when preparing "training data", "vector datasets", "document processing", or "embedding data".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Produces build artifacts with Software Bill of Materials (SBOM) and supply chain metadata for security and compliance. Use for "artifact publishing", "SBOM generation", "supply chain security", or "build provenance".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a study's materials, data, code, or preprint need an open-science release: license choice, a persistent DOI (Zenodo/OSF), README and metadata, and an access-and-embargo decision that respects ethics constraints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hunt Host Header Injection — password reset poisoning → ATO, web cache poisoning via unkeyed Host/X-Forwarded-Host, routing-based SSRF (Host picks upstream → cloud metadata/internal services), path-override SSRF/ACL-bypass (X-Original-URL/X-Rewrite-URL), OAuth redirect_uri/issuer poisoning, and absolute-URL link poisoning in emails. High to Critical when it reaches ATO or mass cache poisoning. Built on public Host-header research (PortSwigger 'Practical web cache poisoning' + James Kettle, and the classic password-reset-poisoning class). Use on any forgot-password flow, CDN/reverse-proxy-fronted app, OAuth/OIDC endpoint, or absolute-URL-in-email feature.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Server-Side Request Forgery testing checklist: SSRF discovery, blind SSRF with out-of-band, cloud metadata endpoints (AWS/GCP/Azure), SSRF filter bypass techniques (IP encoding, DNS rebinding, redirect chains), and SSRF to RCE escalation. Use for web app SSRF testing and bug bounty.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Hunt gRPC vulnerabilities — server reflection enabled (enumerate all services/methods), missing authentication / metadata-stripping on internal endpoints, plaintext gRPC over HTTP/2, internal endpoint disclosure, proto file leakage, gRPC-Web/grpc-gateway transcoding injection, and HTTP/2 Rapid Reset DoS (CVE-2023-44487). Use when target exposes port 50051 / 443 / 8443 / 9090 with HTTP/2, when grpcurl/grpcui detects reflection, when an Envoy or grpc-gateway proxy is fronting a microservice, or when recon reveals a microservice architecture.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Comprehensive API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Dense methodology covering DNS exfiltration (dnscat2, iodine, dns2tcp), HTTPS tunneling (domain fronting, CDN abuse, legitimate service channels), ICMP tunneling (icmpsh, ptunnel-ng), cloud storage dead drops (S3 presigned URLs, Azure Blob SAS tokens, GCS signed URLs), email-based exfil (SMTP, EWS, draft method), steganography (image, audio, document metadata), encoding/encryption (base64 chunking, XOR, AES), covert channels (custom protocol tunneling, HTTP header encoding, timing channels), and data staging (compression, splitting, encryption). Tools: dnscat2, iodine, dns2tcp, PacketWhisper, chisel, stunnel, icmpsh, ptunnel-ng, steghide, zsteg, OpenStego. MITRE ATT&CK: T1048 (Exfiltration Over Alternative Protocol), T1041 (Exfiltration Over C2 Channel), T1567 (Exfiltration Over Web Service), T1029 (Scheduled Transfer), T1030 (Data Transfer Size Limits), T1132 (Data Encoding), T1001 (Data Obfuscation). Use when planning or executing data exfiltration during authorized red team engagements or post-exploita...

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation ...

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.