Results for “log parsing”

Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.

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Analyze Windows authentication logs for repeated password guesses against Remote Desktop services. Group failures by source IP and account, check for later successful logins, and produce a JSON report highlighting attack patterns and possible compromise.

• Investigate repeated login failures on exposed RDP services
• Identify accounts targeted by password guessing
• Check for successful logins after repeated failures

Turn Git history into release notes and recommend the next version based on commit types and breaking changes. Check commit formatting, filter changes by package, and generate Markdown or JSON for automated release workflows.

• Prepare release notes before publishing a version
• Determine the next version from commit history
• Check commit message formats before merging

Use when working with Coralogix — coralogix observability platform for log analytics, metrics, tracing, security, and alerting. Covers log querying with DataPrime, metric exploration, alert management, parsing rules, and data usage insights. Use when searching Coralogix logs, investigating application errors, managing alert rules, or analyzing log ingestion patterns.

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Use when designing, validating, deploying, changing, or troubleshooting Volcengine TLS LogCollector collection on Linux hosts or Kubernetes, including Project, Topic, host group, collector rule, index, binding, heartbeat, parsing, and end-to-end log ingestion checks through volclog. 当用户需要设计、部署、 变更或排查火山引擎日志服务 LogCollector 采集（主机、Kubernetes DaemonSet/Controller、机器组、采集配置、 心跳、解析、日志未入库）时调用。

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Analyze proxy, DNS, and firewall traffic logs to uncover unapproved SaaS and cloud services. Group usage by domain, compare it with approved applications, and produce a report with traffic volumes, user counts, risk scores, and remediation recommendations.

• Finding unapproved SaaS and cloud services
• Measuring traffic volumes and users by service
• Prioritizing services by potential data leakage risk

Read, analyze, modify, and visualize molecular structures with RDKit in Python. Calculate molecular properties, search for similar structures or specific structural patterns, apply reaction rules, and generate 2D or 3D coordinates with detailed control over processing.

• Calculating properties for a collection of molecules
• Searching for molecules with similar structures
• Filtering molecules by specific structural patterns

Process DNA, RNA, and protein sequences with Biopython, convert biological files, and retrieve NCBI records. Supports batch workflows for sequence comparison, searches for similar sequences, protein structure analysis, and evolutionary trees.

• Convert GenBank files to FASTA
• Calculate sequence length and GC content in batches
• Retrieve sequences and publication records from NCBI

Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For single-cell workflows use scanpy. For direct literature REST API, use pubmed-database.

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Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel

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Assess dependency confusion, where a build retrieves a public package instead of an intended private one. Discover internal package names, review registry settings, plan callback-based proofs of execution, and document fixes across major package ecosystems.

• Reviewing package registry settings in CI/CD
• Finding internal package names in lock files
• Planning an authorized callback-based proof of concept

Unified biological database evidence owner. Use for gene annotation, variant clinical significance, cancer mutation evidence, GWAS trait associations, pathway mapping, target-disease evidence, protein structures, protein interaction networks, reference single-cell census queries, and cross-database biological ID mapping. Do not use for full single-cell analysis, bulk RNA-seq differential expression, BAM/VCF processing, protein embedding models, metabolic flux modeling, genomic interval ML, or flow-cytometry file parsing.

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Read biological sequence files (FASTA, FASTQ, GenBank, EMBL, ABI, SFF) using Biopython Bio.SeqIO. Use when parsing sequence files, iterating multi-sequence files, random access to large files, or high-performance parsing.

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An overview of the core data API of ObsPy, a Python framework for processing seismological data. It is useful for parsing common seismological file formats, or manipulating custom data into standard objects for downstream use cases such as ObsPy's signal processing routines or SeisBench's modeling API.

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A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.

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Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.

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Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.

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A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.

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Primary Python toolkit for molecular biology. Preferred for Python-based PubMed/NCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.

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Maintain or embed pkg/authclient for portal login, password/TOTP and API-key authentication, native credential transport, configuration parsing, and credential files. Covers authdbctl login wiring; management commands and the admin API have separate owners.

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Maintain authorization-policy OAuth login without an authentication portal, including provider selection, directive parsing, gatekeeper callbacks, opaque sessions, ACL checks, logout, lifecycle, TLS E2E tests, and embedding contracts. Upstream protocol and JWT verification remain with oauth-identity-provider.

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Parse Claude Code JSONL session logs from ~/.claude/projects/ for tool call inventory, token costs, error detection, subagent traces, and compaction detection

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Deep OAuth 2.0 / OpenID Connect security assessment. Covers the full attack surface: redirect_uri validation bypass (path traversal, open redirect chains, subdomain confusion, URL parsing tricks, parameter pollution, response mode switching), missing/broken state parameter CSRF, PKCE downgrade and absent-challenge attacks, implicit grant token leakage (Referer, browser history, XSS fragment theft), authorization code injection, scope escalation, client confusion attacks, mutable-claims account takeover (iss+sub confusion, email-keyed identity merging), pre-account takeover via unverified registration, OpenID Connect dynamic client registration SSRF (logo_uri, jwks_uri, sector_identifier_uri, request_uri), nonce replay, ID token validation failures, Device Code phishing flow, mobile custom URI scheme hijacking, refresh token persistence, token introspection enumeration, consent screen clickjacking, host header injection, and cross-IdP mix-up attacks. Uses KOAuth, jwt_tool, nuclei oauth templates, and manual http(action="request", ...) payloads. Every technique includes actual request payloads and verification logic. Chains from /pentester or /api-security when OAuth endpoints are discovered. Chains into /web-exploit for open redirect, XSS, and SSRF chaining. Chains into /post-exploit when full account takeover is achieved. Chains into /credential-audit when access tokens or refresh tokens are recovered.

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Extracts indicators of compromise from raw analysis artifacts: parsing strings dumps, sandbox reports, PCAP summaries, and logs for URLs, domains, IPs, hashes, mutexes, and file paths, then deduplicating and typing them. Activates for requests to extract IOCs from analysis output, pull indicators from a report, or harvest atomic indicators.

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