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 liortesta/ClawdAgent --skill dark-web-recongit clone --depth 1 https://github.com/liortesta/ClawdAgentWrote 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/liortesta/clawdagent/dark-web-recon)<a href="https://agentmods.dev/skills/liortesta/clawdagent/dark-web-recon"><img src="https://agentmods.dev/badge/skills/liortesta/clawdagent/dark-web-recon/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/liortesta/clawdagent/dark-web-recon"><img src="https://agentmods.dev/badge/skills/liortesta/clawdagent/dark-web-recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00837 |
| Opus 5 | $0.00000 | $0.00418 |
| Sonnet 5 | $0.00000 | $0.00167 |
| Haiku 4.5 | $0.00000 | $0.00084 |
Grade A, and why
dark-web-recon 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 5d 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.
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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dark Web Reconnaissance — Da7rkx0
For authorized threat intelligence and security research only.
Overview
Da7rkx0 represents dark web reconnaissance capabilities used during authorized threat intelligence gathering and security assessments. Understanding dark web monitoring is essential for proactive defense — identifying leaked credentials, sold data, and emerging threats before they are exploited.
Core Capabilities
- Credential Monitoring: Monitor paste sites and forums for leaked organizational credentials
- Data Leak Detection: Identify if organizational data appears on dark web marketplaces
- Threat Intelligence: Track threat actor activities, TTPs (Tactics, Techniques, Procedures)
- Brand Monitoring: Detect phishing kits and fraudulent sites targeting the organization
- Vulnerability Intelligence: Track zero-day discussions and exploit availability
- Insider Threat Indicators: Monitor for employee data being sold or shared
Threat Intelligence Workflow
1. DEFINE SCOPE → Organizational assets to monitor
- Domain names, email patterns
- IP ranges, technology stack
- Key personnel names
- Product names, internal project names
2. PASSIVE MONITORING → Automated scanning
- Paste sites (Pastebin, Ghostbin, etc.)
- Breach databases
- Dark web forums and marketplaces
- Telegram channels
- Hacker forums
3. ANALYSIS → Correlate and validate findings
- Verify credential validity (against own systems only)
- Assess data freshness and severity
- Identify threat actors and their patterns
- Map to MITRE ATT&CK framework
4. RESPONSE → Act on findings
- Force password resets for exposed credentials
- Takedown fraudulent sites
- Update firewall rules for identified IOCs
- Brief security team on emerging threats
5. REPORT → Document for stakeholders
- Executive summary with business impact
- Technical details with IOCs
- Remediation recommendations
- Ongoing monitoring plan
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.
- 5d ago First seen · 89 lines · 0 tokens per session scan A 6ee891c2a6a7
dark-web-recon is a skill published in the GitHub repository liortesta/ClawdAgent (11 stars, last pushed 12d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 837 tokens. 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 2026-09-03.
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