vibe-coding-cn is a Chinese tutorial on using AI as a programming partner, covering prompts, reusable skills, workflows, context management, and software engineering practices. It guides developers from an initial idea through implementation and verification with AI coding tools such as Claude Code and Codex. The catalogue entries are the project’s documented skills, instruction, plugin, and command for applying this workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tradecatlabs/vibe-coding-cn --skill correlating-threat-campaignsgit clone --depth 1 https://github.com/tradecatlabs/vibe-coding-cnWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tradecatlabs/vibe-coding-cn/correlating-threat-campaigns)<a href="https://agentmods.dev/skills/tradecatlabs/vibe-coding-cn/correlating-threat-campaigns"><img src="https://agentmods.dev/badge/skills/tradecatlabs/vibe-coding-cn/correlating-threat-campaigns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tradecatlabs/vibe-coding-cn/correlating-threat-campaigns"><img src="https://agentmods.dev/badge/skills/tradecatlabs/vibe-coding-cn/correlating-threat-campaigns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.01566 |
| Opus 5 | $0.00049 | $0.00783 |
| Sonnet 5 | $0.00020 | $0.00313 |
| Haiku 4.5 | $0.00010 | $0.00157 |
Grade A, and why
correlating-threat-campaigns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Correlating Threat Campaigns
When to Use
Use this skill when:
- Multiple unrelated-appearing incidents share IOCs (same C2 IP, same malware hash, similar TTPs)
- An ISAC partner shares indicators from an incident that match your own historical events
- Building a campaign report linking adversary activity over weeks or months to a single operation
Do not use this skill to force correlation based on weak signals — false campaign attribution misleads defenders and wastes resources on incorrect threat models.
Prerequisites
- TIP or SIEM with historical indicator and event data (90+ days recommended)
- MISP correlation engine enabled with event sharing configured
- Graph analysis tool (Maltego, Neo4j, or OpenCTI) for relationship visualization
- Reference to MITRE ATT&CK intrusion set and campaign objects for structuring output
Workflow
Step 1: Collect and Normalize Events
Gather all candidate events for correlation from:
- Internal SIEM (raw events, alert history)
- TIP (historical indicators and events)
- ISAC sharing (partner-submitted events in MISP or TAXII)
- Commercial intelligence (Recorded Future, Mandiant, CrowdStrike reports)
Normalize all events to STIX 2.1 schema with consistent timestamp (UTC), indicator types, and confidence scores. Ensure all indicators have source attribution and collection date.
Step 2: Identify Correlation Pivot Points
Apply systematic pivot analysis across four dimensions:
Infrastructure pivots:
- Same IP address or /24 subnet across events
- Same domain registrant email or WHOIS organization
- Same ASN or hosting provider with same account fingerprint
- Same SSL certificate fingerprint or serial number across C2 domains
Capability pivots:
- Same malware hash or YARA signature match
- Same C2 communication protocol (Cobalt Strike beacon config, Sliver implant parameters)
- Same exploit code or weaponized document template
- Same obfuscation method or packer fingerprint
Temporal pivots:
- Events occurring within same time window (operational hours suggesting same timezone)
- Sequential events with logical kill chain progression
- Malware compilation timestamps clustering in same date range
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 169 lines · 99 tokens per session scan A 7d7a0ec11e9a
correlating-threat-campaigns is a skill published in the GitHub repository tradecatlabs/vibe-coding-cn (16,181 stars, last pushed today), licensed MIT. It adds 99 tokens to every session and 1,566 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-13.
Other skills, from other repositories
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 indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack…
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 indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack…
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 consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use…
Threat Intelligence & CTI
Cyber threat intelligence production — the intelligence cycle, IOC extraction/normalization/enrichment, STIX/TAXII and MISP, structured analytic models (Diamond, Kill Chain, ATT&CK), source scoring, actor/campaign tracking, and finished intelligence reporting.
building-threat-feed-aggregation-with-misp
Deploy MISP (Malware Information Sharing Platform) to aggregate, correlate, and distribute threat intelligence feeds from multiple sources for centralized IOC management and automated SIEM integration.
building-threat-intelligence-platform
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.