Marketplace
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.
- 146.7K
- listings
- 1
- installs
- 0
- reviews
- 40.4K
- publishers
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-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-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
analyzing-threat-landscape-with-misp
Query a MISP (Malware Information Sharing Platform) instance via PyMISP to compute event statistics, IOC type breakdowns, threat actor galaxy clusters, and tag trends, and generate threat landscape re
automating-ioc-enrichment
Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standa
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-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
correlating-threat-campaigns
Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared in
generating-threat-intelligence-reports
Generates structured cyber threat intelligence reports at strategic, operational, and tactical levels tailored to specific audiences including executives, security operations teams, and technical anal
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-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
managing-intelligence-lifecycle
Manages the end-to-end cyber threat intelligence lifecycle from planning and direction through collection, processing, analysis, dissemination, and feedback to ensure intelligence products meet stakeh
modeling-threats-with-opencti
Deploy OpenCTI (Filigran) via Docker Compose and use the pycti Python client to model threat actors, intrusion sets, campaigns, and indicators as a STIX 2.1 knowledge graph with relationships (uses, a
monitoring-darkweb-sources
Monitors dark web forums, marketplaces, paste sites, and ransomware leak sites for mentions of organizational assets, leaked credentials, threatened attacks, and threat actor communications to provide
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-landscape-assessment-for-sector
Conducts a sector-specific threat landscape assessment (financial, healthcare, energy, government, etc.) by profiling targeting threat actors, mapping attack vectors and MITRE ATT&CK TTPs with the att
processing-stix-taxii-feeds
Processes STIX 2.1 threat intelligence bundles delivered via TAXII 2.1 servers, normalizing objects into platform-native schemas and routing them to appropriate consuming systems. Use when onboarding
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
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.