“sam”的搜索结果

Hunting skill for auth bypass vulnerabilities. Built from 12 public bug bounty reports across SAML XSW / parser-differential (GitHub Enterprise CVE-2025-25291/25292), SAML signature stripping (Uber, Rocket.Chat, samlify CVE-2025-47949), SAML domain enforcement bypass via control characters (HackerOne 2024), partner-portal cross-IdP assertion reuse (Slack), WordPress XMLRPC bypassing SSO (Uber), JWT alg-confusion HS256/RS256 (Jitsi), JWT signature-validation skip (Linktree, Newspack), and token-audience confusion (Argo CD CVE-2023-22482). For standalone JWT signature/crypto forging (alg:none, key confusion, kid/jku) see hunt-jwt-crypto; this skill covers JWT only inside SSO/SAML/token-trust bypass chains. SAML assertion-layer attacks (XSW, comment injection, signature stripping, XXE-in-assertion) are owned by hunt-saml; this skill owns the broader cross-protocol auth-bypass taxonomy. Use when hunting auth bypass — see the Legacy-Protocol Matrix for branded-UI vs legacy-endpoint patterns.

中文简介正在准备中。当前显示原文说明。

Work with Waypoint models to analyze microbiome samples, the communities of microbes in a sample. Convert taxonomic abundance tables, generate numerical sample representations, configure further training for prediction tasks, and evaluate models on the Compass benchmark.

中文简介正在准备中。当前显示英语简介。

• Convert microbiome abundance tables into Waypoint inputs
• Generate sample vectors for clustering and visualization
• Configure further training with sample labels

Read, query, filter, and write genomic files with pysam in Python. Extract regions, summarize variants, and count aligned bases while handling coordinate conventions, file indexes, headers, and the reference sequences needed to decode CRAM files.

中文简介正在准备中。当前显示英语简介。

• Inspect genomic file formats, headers, and indexes
• Filter alignment records by quality and flags
• Summarize variants and genotypes in a genomic region

Prepare and launch nf-core/pacsomatic workflows for matched tumor and normal PacBio HiFi samples. Generate sample sheets and launch files from unaligned BAM inputs, run local checks, submit cluster launchers, and troubleshoot startup failures.

中文简介正在准备中。当前显示英语简介。

• Prepare sample sheets for matched tumor and normal samples
• Review generated launch files with a dry run
• Submit a Nextflow launcher to a computing cluster

Assess Microsoft Entra ID with AADInternals during authorized security testing. Examine publicly exposed tenant information, API access, and federation weaknesses, including Golden SAML, a token forgery technique, then document evidence and recommendations for stronger identity protection.

中文简介正在准备中。当前显示英语简介。

• Mapping publicly exposed Entra ID tenant information
• Checking API access available through acquired tokens
• Validating AD FS signing certificate protection

Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.

中文简介正在准备中。当前显示原文说明。

In-memory caching in Golang using samber/hot — eviction algorithms (LRU, LFU, TinyLFU, W-TinyLFU, S3FIFO, ARC, TwoQueue, SIEVE, FIFO), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Apply when using or adopting samber/hot, when the codebase imports github.com/samber/hot, or when the project repeatedly loads the same medium-to-low cardinality resources at high frequency and needs to reduce latency or backend pressure.

中文简介正在准备中。当前显示原文说明。

Structured logging extensions for Golang using samber/slog-**** packages — multi-handler pipelines (slog-multi), log sampling (slog-sampling), attribute formatting (slog-formatter), HTTP middleware (slog-fiber, slog-gin, slog-chi, slog-echo), and backend routing (slog-datadog, slog-sentry, slog-loki, slog-syslog, slog-logstash, slog-graylog...). Apply when using or adopting slog, or when the codebase already imports any github.com/samber/slog-* package.

中文简介正在准备中。当前显示原文说明。

Dependency injection in Golang using samber/do — service containers, lifecycle management, scopes, health checks, graceful shutdown, and module organization. Apply when using or adopting samber/do, when the codebase imports github.com/samber/do or github.com/samber/do/v2, or when refactoring manual constructor injection into a DI container.

中文简介正在准备中。当前显示原文说明。

Golang refactoring — safe, at-scale restructuring of existing Go code: a coverage-adaptive safety net, behavior-preserving transforms (gopls Rename/Extract, `gofmt -r`, `gopatch`), the Fowler catalog mapped to Go, breaking import cycles, and small stacked PRs. Apply when a function or type has grown too large, a code smell blocks a feature, or the user asks to refactor Go code — also for renaming at scale, extracting functions or interfaces, moving code between packages, or planning a multi-step refactor. Target styles owned elsewhere → See `samber/cc-skills-golang@golang-naming` (renames), `samber/cc-skills-golang@golang-project-layout` (splits), `samber/cc-skills-golang@golang-modernize` (idioms), `samber/cc-skills-golang@golang-code-style` (control flow), `samber/cc-skills-golang@golang-design-patterns` (patterns/DI).

中文简介正在准备中。当前显示原文说明。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

中文简介正在准备中。当前显示原文说明。

AWS SAM and AWS CDK deployment for serverless applications. Triggers on phrases like: use SAM, SAM template, SAM init, SAM deploy, CDK serverless, CDK Lambda construct, NodejsFunction, PythonFunction, SAM and CDK together, serverless CI/CD pipeline. For general app deployment with service selection, use deploy-on-aws plugin instead.

中文简介正在准备中。当前显示原文说明。

Use when reviewing a Rezolus sampler change before merge — a new sampler, a change to an existing sampler's probes/refresh/metrics, or core changes that affect samplers; or whenever a sampler's overhead, cadence, or data source is in question.

中文简介正在准备中。当前显示原文说明。

Establishes a disciplined malware sample repository: content-addressed storage by hash, encrypted/password-protected archiving, consistent metadata records, and chain-of-custody tracking so samples are reproducible and safe to handle. Activates for requests to organize a malware repository, manage samples, or track sample metadata and provenance.

中文简介正在准备中。当前显示原文说明。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

中文简介正在准备中。当前显示原文说明。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

中文简介正在准备中。当前显示原文说明。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

中文简介正在准备中。当前显示原文说明。

Analyze a set of design samples (HTML mockups + website URLs) and produce a structured style guide that anchors the rest of the stardust redesign pipeline. Use when the user supplies reference designs ("design samples", "mockups", "inspiration sites", "style references") and wants to extract a consistent visual language — type system, color palette, spacing, motion, and reusable component patterns — before redesigning a target site. Triggers on phrases like "distill these samples", "extract a style guide from these examples", "use these as design references", or "analyze these mockups". Outputs a `trait-matrix.json` (structured per-sample + cross-sample design tokens) and a `SAMPLES.md` narrative brief that `stardust:direct` reads under Mode B (anchor-reference precedence) when picking a redesign direction.

中文简介正在准备中。当前显示原文说明。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

中文简介正在准备中。当前显示原文说明。

Locate CCSGameRules::SameMapTeardown in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CCSGameRules::SameMapTeardown" (symbol CCSGameRules_SameMapTeardown). This is a non-virtual function - emit a byte signature (func_sig), not an offset. Locate it via cross-references, distinctive constants/strings in its body, or callers of related symbols; verify by decompilation before committing to a candidate. Trigger: CCSGameRules_SameMapTeardown, CCSGameRules::SameMapTeardown

中文简介正在准备中。当前显示原文说明。

Build, run, and troubleshoot data processing pipelines with Nextflow and nf-core. The skill guides modular workflow development, input preparation, testing, cached restarts, and configuration for local computers, computing clusters, or cloud environments.

中文简介正在准备中。当前显示英语简介。

• Run an nf-core workflow with a samplesheet
• Build and test reusable DSL2 modules
• Investigate failed runs and restart with cached results

Plan experiments before collecting data. Helps choose study designs, randomly assign subjects or samples, organize treatment combinations, and generate reproducible schedules while checking for confounding and repeated measurements incorrectly counted as independent samples.

中文简介正在准备中。当前显示英语简介。

• Create random assignments for subjects or samples
• Screen multiple experimental factors
• Balance conditions across batches, days, or plate positions

Build AWS applications that run without managing servers directly. Covers Lambda functions, APIs, DynamoDB storage, message-driven workflows with SQS/SNS, deployment through SAM/CDK, and reducing the delay when a function starts for the first time.

中文简介正在准备中。当前显示英语简介。

• Building an API with Lambda and API Gateway
• Developing an application backed by DynamoDB
• Designing event-driven workflows with SQS/SNS

Estimate a venture’s market size using industry reports, customer counts and pricing, or willingness to pay. Organize results into total, serviceable, and realistically obtainable revenue opportunities to support business planning and investor presentations.

中文简介正在准备中。当前显示英语简介。

• Estimating the market size for a new venture
• Assessing revenue potential for a customer segment
• Preparing market analysis for an investor pitch