Cent: Taming the Chaos of 500+ Community Nuclei Template Repositories
Hook
The official Nuclei templates repository contains around 5,000 templates. Community repositories? Over 20,000 more. Good luck finding them manually.
Context
Nuclei, ProjectDiscovery’s vulnerability scanner, has become the de facto standard for security researchers and bug bounty hunters. Its power lies in its template-based architecture—YAML files that define how to detect specific vulnerabilities, misconfigurations, or exposures. The official nuclei-templates repository is excellent, but it’s necessarily conservative. Templates need vetting, false positives must be minimized, and legal considerations mean some detection methods never make it into the official collection.
The community filled this gap enthusiastically. Security researchers worldwide maintain their own template repositories—specialized collections for specific technologies, aggressive checks that trade false positives for coverage, and bleeding-edge templates for newly disclosed vulnerabilities. The problem? These templates are scattered across hundreds of GitHub repositories. Before Cent, you’d manually track repos, clone them individually, update them separately, and somehow merge them into a usable structure. Miss an update, and you’re blind to new vulnerabilities. Cent emerged as the solution: a Go-based aggregator that transforms this fragmented ecosystem into a single, manageable template collection.
Technical Insight
Cent’s architecture is refreshingly straightforward—a testament to Go’s strength in building CLI tools. At its core, it operates on a declarative configuration model where a YAML file (cent.yaml) defines which repositories to track, what to exclude, and how to organize everything. The tool doesn’t try to be clever with dependency resolution or complex merging strategies. Instead, it embraces a simple model: clone repos in parallel, apply filters, and organize by source.
The initialization flow demonstrates this clarity. When you run cent init, it creates a configuration file that includes both official ProjectDiscovery templates and a curated list of community sources:
nuclei_templates_path: /home/user/nuclei-templates
threads: 10
repositories:
- url: https://github.com/projectdiscovery/nuclei-templates
exclude-dirs:
- .github
- .gitignore
- url: https://github.com/geeknik/nuclei-templates-1
- url: https://github.com/pikpikcu/nuclei-templates
exclude-dirs:
- cves/2018
exclude-files:
- CVE-2019-0001.yamlThe configuration’s power lies in its filtering capabilities. Security researchers often want community templates but not the noise. Maybe a repository includes outdated CVE checks you’ve already patched, or test files that trigger false positives. Cent’s exclude-dirs and exclude-files options let you curate your collection surgically. This becomes crucial when dealing with repositories containing thousands of templates.
The concurrent cloning implementation reveals thoughtful engineering. Rather than sequentially processing repositories, Cent uses goroutines with a configurable thread count. For users with dozens of repositories configured, this parallelism transforms a 20-minute update into a 2-minute operation. The code pattern is typical Go concurrency: a worker pool pattern with a semaphore to limit parallel operations, preventing system resource exhaustion while maximizing throughput.
The update mechanism is where Cent truly shines. Running cent update doesn’t naively re-clone everything. It performs git pulls on existing repositories and intelligently applies your exclusion rules to new content. If you’ve added a directory to exclude-dirs since your last update, Cent removes it from your local collection without touching the rest. This incremental approach respects both your bandwidth and time—critical for security professionals running updates daily.
Cent’s summary command transforms your template collection into actionable intelligence:
$ cent summary -json
{
"total_templates": 23847,
"by_severity": {
"critical": 1247,
"high": 4891,
"medium": 8234,
"low": 6823,
"info": 2652
},
"cves": 8934,
"top_tags": [
{"tag": "cve", "count": 8934},
{"tag": "lfi", "count": 2341},
{"tag": "xss", "count": 1876}
]
}This JSON output integrates beautifully into scanning workflows. You can pipe it into monitoring systems, track template coverage over time, or build dashboards showing your detection capability evolution. The tag frequency analysis is particularly valuable—it reveals gaps in your coverage. If you’re testing web applications but only have 200 SQL injection templates versus 2,000 XSS templates, you know where to focus your template hunting.
The validation command (cent validate) adds quality control to this aggregation chaos. Community templates vary wildly in quality. Some repositories include work-in-progress templates with syntax errors. Others contain templates that worked with Nuclei 2.x but break on 3.x. Cent’s validation leverages Nuclei’s own validation logic to identify broken templates and optionally remove them, ensuring your collection remains executable. This automated quality gate is essential when pulling from dozens of unvetted sources.
Gotcha
Cent’s simplicity is both its strength and its Achilles’ heel. The tool assumes all templates live in public GitHub repositories. If your organization maintains private template repositories—common in enterprise security teams—you’re out of luck. There’s no authentication mechanism for private repos, and the GitHub token support is limited to avoiding rate limiting rather than accessing private content. You’ll need to manually handle private templates outside Cent’s workflow.
The deduplication problem bites harder than you’d expect. Multiple community repositories often include the same popular templates, either copied directly or slightly modified. Cent clones everything, meaning you might have five versions of the same Log4j detection template across different repository folders. Nuclei handles this somewhat gracefully by skipping duplicate template IDs, but it wastes disk space and makes template management confusing. You’ll find yourself manually reviewing for duplicates, especially when repositories fork popular collections and make minor tweaks. The lack of content-based deduplication or template ID conflict resolution means this manual overhead scales with the number of repositories you track.
Update coordination presents another subtle challenge. If an upstream repository restructures its directory layout or renames files, Cent treats these as new templates rather than moves. Your exclusion rules might suddenly stop working, and you’ll accumulate orphaned files from the old structure. The tool provides no migration assistance for these scenarios—you’ll notice something’s wrong only when your template count unexpectedly spikes or scanning behavior changes.
Verdict
Use Cent if you’re a security researcher, penetration tester, or bug bounty hunter who needs comprehensive vulnerability coverage beyond official templates. It’s invaluable when you’re scanning diverse targets where obscure vulnerabilities matter, or when you need day-zero detection capabilities from community researchers who publish templates faster than official channels. The time savings alone—minutes versus hours of manual repository management—justify adoption for anyone tracking more than five template sources. Skip it if you exclusively scan internal applications with known technology stacks where official templates provide sufficient coverage, if your network policies prohibit bulk GitHub operations, or if you’re in a regulated environment requiring audited template sources with change control. Also skip it if you maintain private template repositories, since the lack of authentication support will force you into manual workflows anyway. For teams needing template version pinning rather than always-latest updates, Cent’s continuous update model might introduce unwanted instability into your scanning pipeline.
