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Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
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A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
analyzing-campaign-attribution-evidence
Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP co
analyzing-indicators-of-compromise
Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use
analyzing-threat-actor-ttps-with-mitre-attack
Systematically map threat actor behavior and observed IOCs to the MITRE ATT&CK framework, build technique coverage heatmaps with the ATT&CK Navigator, identify detection gaps, and produce actionable t
analyzing-threat-actor-ttps-with-mitre-navigator
Map advanced persistent threat (APT) group TTPs to the MITRE ATT&CK framework using the attackcti Python library to query STIX/TAXII data for group-technique associations, then generate ATT&CK Navigat
analyzing-threat-intelligence-feeds
Analyzes structured and unstructured threat intelligence feeds to extract actionable indicators, adversary tactics, and campaign context. Use when ingesting commercial or open-source CTI feeds, evalua
building-attack-pattern-library-from-cti-reports
Parse cyber threat intelligence reports (Mandiant, CrowdStrike, Talos, Microsoft) with stix2, mitreattack-python, and spaCy to extract adversary behaviors, map them to MITRE ATT&CK technique IDs, and
building-ioc-defanging-and-sharing-pipeline
Build an automated pipeline that ingests raw IOCs (URLs, IPs, domains, emails), normalizes and deduplicates them, then produces defanged renderings for safe human reading alongside canonical STIX 2.1
building-ioc-enrichment-pipeline-with-opencti
Build an automated IOC enrichment pipeline on OpenCTI (STIX 2.1 native threat intel platform) using its internal enrichment connectors to pull context from VirusTotal, Shodan, AbuseIPDB, and GreyNoise
building-threat-intelligence-feed-integration
Builds automated threat intelligence feed integration pipelines connecting STIX/TAXII feeds, open-source threat intel, and commercial TI platforms into SIEM and security tools for real-time IOC matchi
building-threat-intelligence-platform
Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows,
collecting-threat-intelligence-with-misp
Deploy MISP, configure threat feeds (MISP community, freetext, TAXII, CSV), and use the PyMISP API to programmatically fetch, add, and search events and IOCs, building automated collection pipelines t
implementing-diamond-model-analysis
The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. This skill c
implementing-security-information-sharing-with-stix2
Create, validate, and share STIX 2.1 threat intelligence objects (indicators, malware, campaigns, relationships, bundles) using the stix2 Python library, and publish them over TAXII 2.1. Use when buil
implementing-stix-taxii-feed-integration
Implements a STIX 2.1/TAXII 2.1 threat-intelligence feed consumer and producer in Python, covering TAXII server discovery, collection polling, parsing STIX bundles with the stix2 library, and standing
implementing-taxii-server-with-opentaxii
Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator exchan
performing-dark-web-monitoring-for-threats
Dark web monitoring involves systematically scanning Tor hidden services, underground forums, paste sites, and dark web marketplaces to identify threats targeting an organization, including leaked cre
performing-indicator-lifecycle-management
Tracks IOCs through discovery, enrichment/validation (VirusTotal, Shodan, passive DNS), deployment to SIEM/IDS watchlists, hit-rate and false-positive monitoring, confidence-score decay, and automated
performing-malware-ioc-extraction
Malware IOC extraction is the process of analyzing malicious software to identify actionable indicators of compromise including file hashes, network indicators (C2 domains, IP addresses, URLs), regist
performing-threat-intelligence-sharing-with-misp
Uses PyMISP (the official MISP REST API library) to create events with structured IOCs (IPs, domains, hashes, URLs), enrich them with MITRE ATT&CK tags and galaxy clusters, manage sharing groups and d
tracking-threat-actor-infrastructure
Discovers and maps adversary-controlled infrastructure (C2 servers, phishing domains, exploit-kit hosts, bulletproof hosting) by pivoting across passive DNS, certificate transparency logs, Shodan/Cens
implementing-diamond-model-analysis
The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. This skill c
analyzing-campaign-attribution-evidence
Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr
analyzing-campaign-attribution-evidence
Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP co
analyzing-campaign-attribution-evidence
Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP co
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Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
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Prefer the terminal? osr stack apply registry://starter installs the starter template.