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 pinkpixel-dev/skills-collection-1 --skill analyzing-tls-certificate-transparency-logsgit clone --depth 1 https://github.com/pinkpixel-dev/skills-collection-1Wrote 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/pinkpixel-dev/skills-collection-1/analyzing-tls-certificate-transparency-logs)<a href="https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/analyzing-tls-certificate-transparency-logs"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-tls-certificate-transparency-logs/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/pinkpixel-dev/skills-collection-1/analyzing-tls-certificate-transparency-logs"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/analyzing-tls-certificate-transparency-logs.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 | $0.00067 | $0.00460 |
| Opus 5 | $0.00034 | $0.00230 |
| Sonnet 5 | $0.00013 | $0.00092 |
| Haiku 4.5 | $0.00007 | $0.00046 |
Grade A, and why
analyzing-tls-certificate-transparency-logs 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 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.
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.
This is a copy
86% identical to analyzing-tls-certificate-transparency-logs — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Analyzing TLS Certificate Transparency Logs
When to Use
- When investigating security incidents that require analyzing tls certificate transparency logs
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Query crt.sh Certificate Transparency database to find certificates issued for domains similar to your organization's brand, detecting phishing infrastructure.
from pycrtsh import Crtsh
c = Crtsh()
# Search for certificates matching a domain
certs = c.search("example.com")
for cert in certs:
print(cert["id"], cert["name_value"])
# Get full certificate details
details = c.get(certs[0]["id"], type="id")
Key analysis steps:
- Query crt.sh for all certificates matching your domain pattern
- Identify certificates with typosquatting variations (Levenshtein distance)
- Flag certificates from unexpected CAs
- Monitor for wildcard certificates on suspicious subdomains
- Cross-reference with known phishing infrastructure
Examples
from pycrtsh import Crtsh
c = Crtsh()
certs = c.search("%.example.com")
for cert in certs:
print(f"Issuer: {cert.get('issuer_name')}, Domain: {cert.get('name_value')}")
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.
- 9d ago First seen · 67 lines · 67 tokens per session scan A b1a93005eab2
analyzing-tls-certificate-transparency-logs is a skill published in the GitHub repository pinkpixel-dev/skills-collection-1 (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 67 tokens to every session and 460 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to analyzing-tls-certificate-transparency-logs, differing in 34 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-tls-certificate-transparency-logs
Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.
analyzing-tls-certificate-transparency-logs
Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.
analyzing-tls-certificate-transparency-logs
Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.
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Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.