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You are a code education expert specializing in explaining complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Transform difficult concepts into understandable explanations for developers at all levels.
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Complete guide for xUnit test output and logging. Use when you need to implement test output, diagnostic logging, or ILogger alternatives in xUnit tests. Covers ITestOutputHelper injection, AbstractLogger pattern, structured output design. Includes XUnitLogger, CompositeLogger, performance test diagnostic tool implementations. Keywords: ITestOutputHelper, ILogger testing, test output xunit, test output, test logging, AbstractLogger, XUnitLogger, CompositeLogger, testOutputHelper.WriteLine, test diagnostics, logger mock, test log, structured output, Received().Log
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Complete guide for .NET Aspire Testing integration testing framework. Use when testing .NET Aspire distributed applications, configuring AppHost tests, or migrating from Testcontainers to Aspire testing. Covers DistributedApplicationTestingBuilder, container lifecycle management, multi-service orchestration, Respawn configuration, and time testability design. Keywords: aspire testing, .NET Aspire, DistributedApplicationTestingBuilder, AppHost testing, distributed testing, AspireAppFixture, IAsyncLifetime, ContainerLifetime.Session, cloud-native testing, multi-service integration, Aspire.Hosting.Testing, Respawn
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Optimizes MAUI for iOS/Catalyst. Native AOT pipeline, size/startup gains, library gaps, trimming.
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Creates GitHub-native docs. README badges, CONTRIBUTING, issue/PR templates, repo metadata.
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Use for non-trivial, design-bearing, or architecture-affecting work before execution planning. Creates or updates a versioned spec under planning/specs/active/ with design intent, alternatives, risks, and acceptance criteria.
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Plan and sequence complex implementation work into deterministic, testable steps. Use when the user asks for planning, roadmap breakdown, execution strategy, effort estimation, or multi-step delivery coordination across domains.
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Plan and sequence complex implementation work into deterministic, testable steps for this repository. Use when the user asks for planning, roadmap breakdown, execution strategy, effort estimation, or multi-step delivery coordination across domains.
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Use for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.
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Rapid codebase assessment — lightweight alternative to $gsd-map-codebase
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Exploit Kerberos Constrained Delegation misconfigurations in Active Directory to impersonate privileged users via S4U2self and S4U2proxy extensions for lateral movement and privilege escalation.
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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.
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Detect Mimikatz execution through command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.
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Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.
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Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.
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Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anomalies including mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures in domain controller event logs.
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Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.
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Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.
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Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.
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Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.
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Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations
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Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.
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Business Email Compromise (BEC) is a sophisticated fraud scheme where attackers impersonate executives, vendors, or trusted partners to trick employees into transferring funds, sharing sensitive data,
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Building a Threat Intelligence Platform (TIP) involves deploying and integrating multiple CTI tools into a unified system for collecting, analyzing, enriching, and disseminating threat intelligence. T
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