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 MingyiSecLab/Mingyi-Atlas --skill osintgit clone --depth 1 https://github.com/MingyiSecLab/Mingyi-AtlasWrote 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/mingyiseclab/mingyi-atlas/osint)<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/osint"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/osint/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/mingyiseclab/mingyi-atlas/osint"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/osint.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 | $0.00030 | $0.02301 |
| Opus 5 | $0.00015 | $0.01151 |
| Sonnet 5 | $0.00006 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade C, and why
osint scanned grade C with 2 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 9d ago.
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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -s "https://api.shodan.io/shodan/host/<IP>?key=<SHODAN_KEY>" | python3 -m json.tool Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://api.github.com/orgs/<target>/repos?per_page=100" | \ How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open Source Intelligence (OSINT) Knowledge Base
OSINT collects publicly available information about targets without any direct interaction. This intelligence informs social engineering, credential attacks, and helps map the human attack surface alongside technical infrastructure.
1. Email Harvesting
theHarvester
# Comprehensive email harvesting
theHarvester -d <target> -b all -l 500 -f theharvester_<target>.html
# Specific sources
theHarvester -d <target> -b google,bing,linkedin,twitter -l 200
# Output formats
theHarvester -d <target> -b all -f theharvester_<target> --screenshot screenshots/
Manual Email Pattern Discovery
# Common email formats to test
# [email protected]
# [email protected]
# [email protected]
# [email protected]
# Verify email format via MX + SMTP (if in scope)
dig <target> MX +short
Email Analysis Points
- Naming convention: Determines brute-force pattern for credential stuffing
- Role-based emails: security@, admin@, devops@ reveal team structure
- Personal domains: Cross-reference with social media for password patterns
- Catch-all detection: Some domains accept all addresses → harder to enumerate
2. Employee & Organization Enumeration
LinkedIn Intelligence
- Search
site:linkedin.com/in "<target company>"in Google - Note: Direct LinkedIn scraping may violate ToS — use public search results
- Key data: Job titles, tech stack mentions, team sizes, recent hires
Organizational Mapping
Target Corp
├── Engineering (mentions: Kubernetes, Go, React)
│ ├── Platform Team (AWS, Terraform)
│ ├── Backend Team (Python, FastAPI)
│ └── Frontend Team (React, TypeScript)
├── Security
│ └── SOC Team (Splunk, CrowdStrike mentioned)
├── DevOps/SRE
│ └── (Jenkins, ArgoCD, Datadog mentioned)
└── IT
└── (Okta, Jamf mentioned in job posts)
Tech Stack from Job Postings
Search job boards for:
"<target>" AND ("kubernetes" OR "terraform" OR "aws" OR "azure")
"<target>" AND ("react" OR "angular" OR "vue" OR "nextjs")
"<target>" AND ("python" OR "golang" OR "java" OR "rust")
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.
- 9d ago First seen · 236 lines · 30 tokens per session scan C 2c41c7645f50
osint is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 2,301 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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