SkillAgentSearch skills...

Create Fake Materials: Fake Website

'Analyzes indicators of compromise (IOCs) including IP addresses, domains,

Install / Use

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-indicators-of-compromise

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Category

Security

Supported Platforms

Universal

Our assessment of Create Fake Materials: Fake Website

Create Fake Materials: Fake Website scores 95/100 on our quality scale, 121st of 544 Security skills we index (top 23%).

Its SKILL.md is 7.6 KB long, well organised into 14 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

With 33,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
12/15
Adoption
19/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 25 days ago, so Create Fake Materials: Fake Website is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

Create Fake Materials: Fake Website compared with similar skills

All 4 of these similar skills score higher than Create Fake Materials: Fake Website; compare them before choosing.

SkillScoreStarsUpdatedFormat
Create Fake Materials: Fake Website (this skill)by mukul9759533.3k25d agoSKILL.md
algorithmic-artby anthropics100177.9k3d agoSKILL.md
pptxby anthropics100177.9k3d agoSKILL.md
designby nextlevelbuilder100130.2k4d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k4d agoSKILL.md

Frequently asked questions

How do I install Create Fake Materials: Fake Website?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill "Create Fake Materials: Fake Website". The install tabs above show the steps for each supported agent.
Which AI agents does Create Fake Materials: Fake Website work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is Create Fake Materials: Fake Website safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is Create Fake Materials: Fake Website still maintained?
The repository was last updated 25 days ago, so Create Fake Materials: Fake Website is actively maintained.

name: analyzing-indicators-of-compromise description: 'Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

' domain: cybersecurity subdomain: threat-intelligence tags:

  • IOC
  • VirusTotal
  • AbuseIPDB
  • MalwareBazaar
  • MISP
  • threat-intelligence
  • STIX
  • NIST-CSF version: 1.0.0 author: mahipal license: Apache-2.0 atlas_techniques:
  • AML.T0052 nist_csf:
  • ID.RA-01
  • ID.RA-05
  • DE.CM-01
  • DE.AE-02 mitre_attack:
  • T1071
  • T1105
  • T1041
  • T1567 mitre_f3: version: '1.1' tactics:
    • reconnaissance
    • resource-development
    • initial-access techniques:
    • id: T1598 name: Phishing for Information tactic: reconnaissance source: attack
    • id: T1660 name: Phishing tactic: initial-access source: attack
    • id: T1583.001 name: 'Acquire Infrastructure: Domains' tactic: resource-development source: attack
    • id: F1020.002 name: 'Create Fake Materials: Fake Website' tactic: resource-development source: f3

Analyzing Indicators of Compromise

When to Use

Use this skill when:

  • A phishing email or alert generates IOCs (URLs, IP addresses, file hashes) requiring rapid triage
  • Automated feeds deliver bulk IOCs that need confidence scoring before ingestion into blocking controls
  • An incident investigation requires contextual enrichment of observed network artifacts

Do not use this skill in isolation for high-stakes blocking decisions — always combine automated enrichment with analyst judgment, especially for shared infrastructure (CDNs, cloud providers).

Prerequisites

  • VirusTotal API key (free or Enterprise) for multi-AV and sandbox lookup
  • AbuseIPDB API key for IP reputation checks
  • MISP instance or TIP for cross-referencing against known campaigns
  • Python with requests and vt-py libraries, or SOAR platform with pre-built connectors

Workflow

Step 1: Normalize and Classify IOC Types

Before enriching, classify each IOC:

  • IPv4/IPv6 address: Check if RFC 1918 private (skip external enrichment), validate format
  • Domain/FQDN: Defang for safe handling (evil[.]com), extract registered domain via tldextract
  • URL: Extract domain + path separately; check for redirectors
  • File hash: Identify hash type (MD5/SHA-1/SHA-256); prefer SHA-256 for uniqueness
  • Email address: Split into domain (check MX/DMARC) and local part for pattern analysis

Defang IOCs in documentation (replace . with [.] and :// with [://]) to prevent accidental clicks.

Step 2: Multi-Source Enrichment

VirusTotal (file hash, URL, IP, domain):

import vt

client = vt.Client("YOUR_VT_API_KEY")

# File hash lookup
file_obj = client.get_object(f"/files/{sha256_hash}")
detections = file_obj.last_analysis_stats
print(f"Malicious: {detections['malicious']}/{sum(detections.values())}")

# Domain analysis
domain_obj = client.get_object(f"/domains/{domain}")
print(domain_obj.last_analysis_stats)
print(domain_obj.reputation)
client.close()

AbuseIPDB (IP addresses):

import requests

response = requests.get(
    "https://api.abuseipdb.com/api/v2/check",
    headers={"Key": "YOUR_KEY", "Accept": "application/json"},
    params={"ipAddress": "1.2.3.4", "maxAgeInDays": 90}
)
data = response.json()["data"]
print(f"Confidence: {data['abuseConfidenceScore']}%, Reports: {data['totalReports']}")

MalwareBazaar (file hashes):

response = requests.post(
    "https://mb-api.abuse.ch/api/v1/",
    data={"query": "get_info", "hash": sha256_hash}
)
result = response.json()
if result["query_status"] == "ok":
    print(result["data"][0]["tags"], result["data"][0]["signature"])

Step 3: Contextualize with Campaign Attribution

Query MISP for existing events matching the IOC:

from pymisp import PyMISP

misp = PyMISP("https://misp.example.com", "API_KEY")
results = misp.search(value="evil-domain.com", type_attribute="domain")
for event in results:
    print(event["Event"]["info"], event["Event"]["threat_level_id"])

Check Shodan for IP context (hosting provider, open ports, banners) to identify if the IP belongs to bulletproof hosting or a legitimate cloud provider (false positive risk).

Step 4: Assign Confidence Score and Disposition

Apply a tiered decision framework:

  • Block (High Confidence ≥ 70%): ≥15 AV detections on VT, AbuseIPDB score ≥70, matches known malware family or campaign
  • Monitor/Alert (Medium 40–69%): 5–14 AV detections, moderate AbuseIPDB score, no campaign attribution
  • Whitelist/Investigate (Low <40%): ≤4 AV detections, no abuse reports, legitimate service (Google, Cloudflare CDN IPs)
  • False Positive: Legitimate business service incorrectly flagged; document and exclude from future alerts

Step 5: Document and Distribute

Record findings in TIP/MISP with:

  • All enrichment data collected (timestamps, source, score)
  • Disposition decision and rationale
  • Blocking actions taken (firewall, proxy, DNS sinkhole)
  • Related incident ticket number

Export to STIX indicator object with confidence field set appropriately.

Key Concepts

| Term | Definition | |------|-----------| | IOC | Indicator of Compromise — observable network or host artifact indicating potential compromise | | Enrichment | Process of adding contextual data to a raw IOC from multiple intelligence sources | | Defanging | Modifying IOCs (replacing . with [.]) to prevent accidental activation in documentation | | False Positive Rate | Percentage of benign artifacts incorrectly flagged as malicious; critical for tuning block thresholds | | Sinkhole | DNS server redirecting malicious domain lookups to a benign IP for detection without blocking traffic entirely | | TTL | Time-to-live for an IOC in blocking controls; IP indicators should expire after 30 days, domains after 90 days |

Tools & Systems

  • VirusTotal: Multi-engine malware scanner and threat intelligence platform with 70+ AV engines, sandbox reports, and community comments
  • AbuseIPDB: Community-maintained IP reputation database with 90-day abuse report history
  • MalwareBazaar (abuse.ch): Free malware hash repository with YARA rule associations and malware family tagging
  • URLScan.io: Free URL analysis service that captures screenshots, DOM, and network requests for phishing URL triage
  • Shodan: Internet-wide scan data providing hosting provider, open ports, and banner information for IP enrichment

Common Pitfalls

  • Blocking shared infrastructure: CDN IPs (Cloudflare 104.21.x.x, AWS CloudFront) may legitimately host malicious content but blocking the IP disrupts thousands of legitimate sites.
  • VT score obsession: Low VT detection count does not mean benign — zero-day malware and custom APT tools often score 0 initially. Check sandbox behavior, MISP, and passive DNS.
  • Missing defanging: Pasting live IOCs in emails or Confluence docs can trigger automated URL scanners or phishing tools.
  • No expiration policy: IOCs without TTLs accumulate in blocklists indefinitely, generating false positives as infrastructure is repurposed by legitimate users.
  • Over-relying on single source: VirusTotal aggregates AV opinions — all may be wrong or lag behind emerging malware. Use 3+ independent sources for high-stakes decisions.

Related Skills

View on GitHub
GitHub Stars33.3k
CategorySecurity
Updated25d ago
Forks4.0k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions