Deepsec Documentation Guide
vercel-labs/deepsec
Points the agent at deepsec's own docs to answer questions about initializing, configuring, resuming, scanning with and extending the vulnerability scanner.
Agent skill
Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .claude/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .claude/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .agents/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .agents/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .cursor/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .cursor/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/analyzing-certificate-transparency-for-phishing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .gemini/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .gemini/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .github/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .github/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-certificate-transparency-for-phishing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyzing-certificate-transparency-for-phishing .opencode/skills/analyzing-certificate-transparency-for-phishing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-certificate-transparency-for-phishing" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-certificate-transparency-for-phishing into .opencode/skills/analyzing-certificate-transparency-for-phishing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-certificate-transparency-for-phishing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
analyzing-certificate-transparency-for-phishingMonitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
Analyzing Certificate Transparency For Phishing is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
crt.shAlso links to:
certstream.calidog.ioriversecurity.euletsencrypt.orgsslmate.comcybersierra.coFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Analyzing Certificate Transparency For Phishing loads about 3.5k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 58 tokens; SKILL.md has 397 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 397 words, ~3,522 tokens.
.claude/skills/analyzing-certificate-transparency-for-phishing/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Certificate Transparency (CT) is an Internet security standard that creates a public, append-only log of all issued SSL/TLS certificates. Monitoring CT logs enables early detection of phishing domains that register certificates mimicking legitimate brands, unauthorized certificate issuance for owned domains, and certificate-based attack infrastructure. This skill covers querying CT logs via crt.sh, real-time monitoring with Certstream, building automated alerting for suspicious certificates, and integrating findings into threat intelligence workflows.
requests, certstream, tldextract, Levenshtein librariesCT logs are cryptographically assured, publicly auditable, append-only records of TLS certificate issuance. Major CAs (Let's Encrypt, DigiCert, Sectigo, Google Trust Services) submit all issued certificates to multiple CT logs. As of 2025, Chrome and Safari require CT for all publicly trusted certificates.
Attackers register lookalike domains and obtain free certificates (often from Let's Encrypt) to make phishing sites appear legitimate with HTTPS. CT monitoring detects these early because the certificate appears in logs before the phishing campaign launches, providing a window for proactive blocking.
crt.sh is a free web interface and PostgreSQL database operated by Sectigo that indexes CT logs. It supports wildcard searches (%.example.com), direct SQL queries, and JSON API responses. It tracks certificate issuance, expiration, and revocation across all major CT logs.
import requests
import json
from datetime import datetime
import tldextract
class CTLogMonitor:
CRT_SH_URL = "https://crt.sh"
def __init__(self, monitored_domains, brand_keywords):
self.monitored_domains = monitored_domains
self.brand_keywords = [k.lower() for k in brand_keywords]
def query_crt_sh(self, domain, include_expired=False):
"""Query crt.sh for certificates matching a domain."""
params = {
"q": f"%.{domain}",
"output": "json",
}
if not include_expired:
params["exclude"] = "expired"
resp = requests.get(self.CRT_SH_URL, params=params, timeout=30)
if resp.status_code == 200:
certs = resp.json()
print(f"[+] crt.sh: {len(certs)} certificates for *.{domain}")
return certs
return []
def find_suspicious_certs(self, domain):
"""Find certificates that may be phishing attempts."""
certs = self.query_crt_sh(domain)
suspicious = []
for cert in certs:
common_name = cert.get("common_name", "").lower()
name_value = cert.get("name_value", "").lower()
issuer = cert.get("issuer_name", "")
not_before = cert.get("not_before", "")
not_after = cert.get("not_after", "")
# Check for exact domain matches (legitimate)
extracted = tldextract.extract(common_name)
cert_domain = f"{extracted.domain}.{extracted.suffix}"
if cert_domain == domain:
continue # Legitimate certificate
# Flag suspicious patterns
flags = []
if domain.replace(".", "") in common_name.replace(".", ""):
flags.append("contains target domain string")
if any(kw in common_name for kw in self.brand_keywords):
flags.append("contains brand keyword")
if "let's encrypt" in issuer.lower():
flags.append("free CA (Let's Encrypt)")
if flags:
suspicious.append({
"common_name": cert.get("common_name", ""),
"name_value": cert.get("name_value", ""),
"issuer": issuer,
"not_before": not_before,
"not_after": not_after,
"serial": cert.get("serial_number", ""),
"flags": flags,
"crt_sh_id": cert.get("id", ""),
"crt_sh_url": f"https://crt.sh/?id={cert.get('id', '')}",
})
print(f"[+] Found {len(suspicious)} suspicious certificates")
return suspicious
monitor = CTLogMonitor(
monitored_domains=["mycompany.com", "mycompany.org"],
brand_keywords=["mycompany", "mybrand", "myproduct"],
)
suspicious = monitor.find_suspicious_certs("mycompany.com")
for cert in suspicious[:5]:
print(f" [{cert['common_name']}] Flags: {cert['flags']}")import certstream
import Levenshtein
import re
from datetime import datetime
class CertstreamMonitor:
def __init__(self, watched_domains, brand_keywords, similarity_threshold=0.8):
self.watched_domains = [d.lower() for d in watched_domains]
self.brand_keywords = [k.lower() for k in brand_keywords]
self.threshold = similarity_threshold
self.alerts = []
def start_monitoring(self, max_alerts=100):
"""Start real-time CT log monitoring."""
print("[*] Starting Certstream monitoring...")
print(f" Watching: {self.watched_domains}")
print(f" Keywords: {self.brand_keywords}")
def callback(message, context):
if message["message_type"] == "certificate_update":
data = message["data"]
leaf = data.get("leaf_cert", {})
all_domains = leaf.get("all_domains", [])
for domain in all_domains:
domain_lower = domain.lower().strip("*.")
if self._is_suspicious(domain_lower):
alert = {
"domain": domain,
"all_domains": all_domains,
"issuer": leaf.get("issuer", {}).get("O", ""),
"fingerprint": leaf.get("fingerprint", ""),
"not_before": leaf.get("not_before", ""),
"detected_at": datetime.now().isoformat(),
"reason": self._get_reason(domain_lower),
}
self.alerts.append(alert)
print(f" [ALERT] {domain} - {alert['reason']}")
if len(self.alerts) >= max_alerts:
raise KeyboardInterrupt
try:
certstream.listen_for_events(callback, url="wss://certstream.calidog.io/")
except KeyboardInterrupt:
print(f"\n[+] Monitoring stopped. {len(self.alerts)} alerts collected.")
return self.alerts
def _is_suspicious(self, domain):
"""Check if domain is suspicious relative to watched domains."""
for watched in self.watched_domains:
# Exact keyword match
watched_base = watched.split(".")[0]
if watched_base in domain and domain != watched:
return True
# Levenshtein distance (typosquatting detection)
domain_base = tldextract.extract(domain).domain
similarity = Levenshtein.ratio(watched_base, domain_base)
if similarity >= self.threshold and domain_base != watched_base:
return True
# Brand keyword match
for keyword in self.brand_keywords:
if keyword in domain:
return True
return False
def _get_reason(self, domain):
"""Determine why domain was flagged."""
reasons = []
for watched in self.watched_domains:
watched_base = watched.split(".")[0]
if watched_base in domain:
reasons.append(f"contains '{watched_base}'")
domain_base = tldextract.extract(domain).domain
similarity = Levenshtein.ratio(watched_base, domain_base)
if similarity >= self.threshold and domain_base != watched_base:
reasons.append(f"similar to '{watched}' ({similarity:.0%})")
for kw in self.brand_keywords:
if kw in domain:
reasons.append(f"brand keyword '{kw}'")
return "; ".join(reasons) if reasons else "unknown"
cs_monitor = CertstreamMonitor(
watched_domains=["mycompany.com"],
brand_keywords=["mycompany", "mybrand"],
similarity_threshold=0.75,
)
alerts = cs_monitor.start_monitoring(max_alerts=50)def enumerate_subdomains_ct(domain):
"""Discover all subdomains from Certificate Transparency logs."""
params = {"q": f"%.{domain}", "output": "json"}
resp = requests.get("https://crt.sh", params=params, timeout=30)
if resp.status_code != 200:
return []
certs = resp.json()
subdomains = set()
for cert in certs:
name_value = cert.get("name_value", "")
for name in name_value.split("\n"):
name = name.strip().lower()
if name.endswith(f".{domain}") or name == domain:
name = name.lstrip("*.")
subdomains.add(name)
sorted_subs = sorted(subdomains)
print(f"[+] CT subdomain enumeration for {domain}: {len(sorted_subs)} subdomains")
return sorted_subs
subdomains = enumerate_subdomains_ct("example.com")
for sub in subdomains[:20]:
print(f" {sub}")def generate_ct_report(suspicious_certs, certstream_alerts, domain):
report = f"""# Certificate Transparency Intelligence Report
## Target Domain: {domain}
## Generated: {datetime.now().isoformat()}
## Summary
- Suspicious certificates found: {len(suspicious_certs)}
- Real-time alerts triggered: {len(certstream_alerts)}
## Suspicious Certificates (crt.sh)
| Common Name | Issuer | Flags | crt.sh Link |
|------------|--------|-------|-------------|
"""
for cert in suspicious_certs[:20]:
flags = "; ".join(cert.get("flags", []))
report += (f"| {cert['common_name']} | {cert['issuer'][:30]} "
f"| {flags} | [View]({cert['crt_sh_url']}) |\n")
report += f"""
## Real-Time Certstream Alerts
| Domain | Issuer | Reason | Detected |
|--------|--------|--------|----------|
"""
for alert in certstream_alerts[:20]:
report += (f"| {alert['domain']} | {alert['issuer']} "
f"| {alert['reason']} | {alert['detected_at'][:19]} |\n")
report += """
## Recommendations
1. Add flagged domains to DNS sinkhole / web proxy blocklist
2. Submit takedown requests for confirmed phishing domains
3. Monitor CT logs continuously for new certificate registrations
4. Implement CAA DNS records to restrict certificate issuance for your domains
5. Deploy DMARC to prevent email spoofing from lookalike domains
"""
with open(f"ct_report_{domain.replace('.','_')}.md", "w") as f:
f.write(report)
print(f"[+] CT report saved")
return report
generate_ct_report(suspicious, alerts if 'alerts' in dir() else [], "mycompany.com")© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in skills/analyzing-certificate-transparency-for-phishing of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Analyzing Certificate Transparency For Phishing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analyzing Certificate Transparency For Phishing this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Deepsec Documentation Guidevercel-labs/deepsec | 8.1k | — | ~956 | Automated safety check: Pass | Apache-2.0 | |
| Skill Scannergetsentry/skills | 1k | 4 repos | ~2.5k | Automated safety check: Warn | Apache-2.0 | |
| Serenity Aleabitoreddityan-labs/serenity-aleabitoreddit | 481 | 1 repos | ~3.3k | Automated safety check: Pass | None | |
| Security Alert Triageelastic/agent-skills | 592 | 1 repos | ~3.5k | Automated safety check: Notes | Apache-2.0 | |
| Shiro Attack CLISummerSec/ShiroAttack2 | 2.6k | — | ~945 | Automated safety check: Pass | MIT |
vercel-labs/deepsec
Points the agent at deepsec's own docs to answer questions about initializing, configuring, resuming, scanning with and extending the vulnerability scanner.
getsentry/skills
Scan agent skills for security issues. An agent skill from getsentry/skills.
yan-labs/serenity-aleabitoreddit
Apply trader Serenity's (@aleabitoreddit) AI/semiconductor supply-chain analytical lens to US-stock ideas and market judgment.
elastic/agent-skills
Triage Elastic Security alerts — gather context, classify threats, create cases, and acknowledge.
SummerSec/ShiroAttack2
当用户要求利用、检测或测试 Apache Shiro rememberMe 反序列化漏洞 (Shiro-550, CVE-2016-4437) 时使用。触发词包括 "Shiro"、"rememberMe"、"shiro attack"、"CVE-2016-4437"、"Shiro-550"、"爆破 Shiro key"、"利用 Shiro"、"Shiro…
rundeck/rundeck
Verify if a CVE affects the project and remediate it. An agent skill from rundeck/rundeck.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Categories
Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization. Analyzing Certificate Transparency For Phishing is an agent skill from mukul975/Anthropic-Cybersecurity-Skills.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
Analyzing Certificate Transparency For Phishing fits situations like: security work in your project.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a claude-code`. Or copy the skill folder (skills/analyzing-certificate-transparency-for-phishing in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-certificate-transparency-for-phishing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a codex`. Or copy the skill folder (skills/analyzing-certificate-transparency-for-phishing in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-certificate-transparency-for-phishing in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-certificate-transparency-for-phishing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzing-certificate-transparency-for-phishing, .gemini/skills/analyzing-certificate-transparency-for-phishing, .github/skills/analyzing-certificate-transparency-for-phishing and .opencode/skills/analyzing-certificate-transparency-for-phishing in your project.
Going by SKILL.md and its folder, Analyzing Certificate Transparency For Phishing needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md names 6 domains. In commands or code: crt.sh; the agent is likely to contact it when it follows the instructions. As links in the text: certstream.calidog.io, riversecurity.eu, letsencrypt.org, sslmate.com and cybersierra.co. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Analyzing Certificate Transparency For Phishing is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 713 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Analyzing Certificate Transparency For Phishing: Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Skill Scanner (getsentry/skills, 1k stars), Serenity Aleabitoreddit (yan-labs/serenity-aleabitoreddit, 481 stars) and Security Alert Triage (elastic/agent-skills, 592 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.