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
Parse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-email-headers-for-phishing-investigation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-email-headers-for-phishing-investigation --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-email-headers-for-phishing-investigation .claude/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .claude/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigationType 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-email-headers-for-phishing-investigation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-email-headers-for-phishing-investigation --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-email-headers-for-phishing-investigation .agents/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .agents/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-email-headers-for-phishing-investigation --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-email-headers-for-phishing-investigation .cursor/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .cursor/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigation--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-email-headers-for-phishing-investigation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-email-headers-for-phishing-investigation --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-email-headers-for-phishing-investigation .gemini/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .gemini/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigationInstalls 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-email-headers-for-phishing-investigation -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-email-headers-for-phishing-investigation .github/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .github/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigation -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-email-headers-for-phishing-investigation --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-email-headers-for-phishing-investigation .opencode/skills/analyzing-email-headers-for-phishing-investigation && 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-email-headers-for-phishing-investigation" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-email-headers-for-phishing-investigation into .opencode/skills/analyzing-email-headers-for-phishing-investigation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-email-headers-for-phishing-investigation", 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-email-headers-for-phishing-investigationParse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing.
Analyzing Email Headers For Phishing Investigation is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Parse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing. Use when triaging a suspicious or reported email, investigating a phishing incident, or verifying whether a message's sender domain was spoofed.
Its SKILL.md is about 3.2k 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.
5 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.
Shell commands in SKILL.md call:
python3curlpipFrom 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:
api.abuseipdb.comvirustotal.comFrom 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 Email Headers For Phishing Investigation loads about 3.2k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 481 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). 481 words, ~3,173 tokens.
.claude/skills/analyzing-email-headers-for-phishing-investigation/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.# Export from Outlook: Open email > File > Properties > Internet Headers
# Export from Gmail: Open email > Three dots > Show original
# Export from Thunderbird: View > Message Source
# If working with EML file from forensic image
cp /mnt/evidence/Users/suspect/AppData/Local/Microsoft/Outlook/phishing_email.eml \
/cases/case-2024-001/email/
# If working with PST file, extract individual messages
pip install pypff
python3 << 'PYEOF'
import pypff
pst = pypff.file()
pst.open("/cases/case-2024-001/email/outlook.pst")
root = pst.get_root_folder()
def extract_messages(folder, path=""):
for i in range(folder.get_number_of_sub_messages()):
msg = folder.get_sub_message(i)
headers = msg.get_transport_headers()
subject = msg.get_subject()
if headers:
filename = f"/cases/case-2024-001/email/msg_{i}_{subject[:30]}.txt"
with open(filename, 'w') as f:
f.write(headers)
for i in range(folder.get_number_of_sub_folders()):
extract_messages(folder.get_sub_folder(i))
extract_messages(root)
PYEOF# Parse headers using Python email library
python3 << 'PYEOF'
import email
from email import policy
with open('/cases/case-2024-001/email/phishing_email.eml', 'r') as f:
msg = email.message_from_file(f, policy=policy.default)
print("=== KEY HEADER FIELDS ===")
print(f"From: {msg['From']}")
print(f"To: {msg['To']}")
print(f"Subject: {msg['Subject']}")
print(f"Date: {msg['Date']}")
print(f"Message-ID: {msg['Message-ID']}")
print(f"Reply-To: {msg['Reply-To']}")
print(f"Return-Path: {msg['Return-Path']}")
print(f"X-Mailer: {msg['X-Mailer']}")
print(f"X-Originating-IP: {msg['X-Originating-IP']}")
print("\n=== RECEIVED HEADERS (bottom-up = chronological) ===")
received_headers = msg.get_all('Received')
if received_headers:
for i, header in enumerate(reversed(received_headers)):
print(f"\nHop {i+1}: {header.strip()}")
print("\n=== AUTHENTICATION RESULTS ===")
auth_results = msg.get_all('Authentication-Results')
if auth_results:
for result in auth_results:
print(result)
print(f"\nARC-Authentication-Results: {msg.get('ARC-Authentication-Results', 'Not present')}")
print(f"Received-SPF: {msg.get('Received-SPF', 'Not present')}")
print(f"DKIM-Signature: {msg.get('DKIM-Signature', 'Not present')}")
PYEOF# Extract the envelope sender domain
SENDER_DOMAIN="example-corp.com"
# Check SPF record
dig TXT $SENDER_DOMAIN +short | grep "v=spf1"
# Example: "v=spf1 include:_spf.google.com include:sendgrid.net ~all"
# Check DKIM record (selector from DKIM-Signature header, e.g., "s=selector1")
DKIM_SELECTOR="selector1"
dig TXT ${DKIM_SELECTOR}._domainkey.${SENDER_DOMAIN} +short
# Check DMARC record
dig TXT _dmarc.${SENDER_DOMAIN} +short
# Example: "v=DMARC1; p=reject; rua=mailto:dmarc@example-corp.com; pct=100"
# Verify the sending IP against SPF
# Extract IP from first Received header
SENDING_IP="203.0.113.45"
# Manual SPF check using python
python3 << 'PYEOF'
import spf # pip install pyspf
result, explanation = spf.check2(
i='203.0.113.45',
s='sender@example-corp.com',
h='mail.example-corp.com'
)
print(f"SPF Result: {result}")
print(f"Explanation: {explanation}")
# Results: pass, fail, softfail, neutral, none, temperror, permerror
PYEOF
# Check if sending IP is in known malicious IP lists
# Query AbuseIPDB or VirusTotal
curl -s "https://api.abuseipdb.com/api/v2/check?ipAddress=${SENDING_IP}" \
-H "Key: YOUR_API_KEY" -H "Accept: application/json" | python3 -m json.tool# WHOIS lookup on sender domain
whois $SENDER_DOMAIN | grep -iE '(registrar|creation|expiration|registrant|nameserver)'
# Check domain age (recently registered domains are suspicious)
# DNS record investigation
dig A $SENDER_DOMAIN +short
dig MX $SENDER_DOMAIN +short
dig NS $SENDER_DOMAIN +short
# Reverse DNS on sending IP
dig -x $SENDING_IP +short
# Check for lookalike/typosquatting domains
# Compare with legitimate domain using visual similarity
python3 << 'PYEOF'
import Levenshtein # pip install python-Levenshtein
legitimate = "microsoft.com"
suspicious = "micr0soft.com"
distance = Levenshtein.distance(legitimate, suspicious)
ratio = Levenshtein.ratio(legitimate, suspicious)
print(f"Edit distance: {distance}")
print(f"Similarity ratio: {ratio:.2%}")
if ratio > 0.8:
print("WARNING: Likely typosquatting/lookalike domain!")
PYEOF
# Check domain reputation on VirusTotal
curl -s "https://www.virustotal.com/api/v3/domains/${SENDER_DOMAIN}" \
-H "x-apikey: YOUR_VT_API_KEY" | python3 -m json.tool
# Check if the Reply-To differs from From (common phishing indicator)
python3 -c "
import email
with open('/cases/case-2024-001/email/phishing_email.eml') as f:
msg = email.message_from_file(f)
from_addr = email.utils.parseaddr(msg['From'])[1]
reply_to = email.utils.parseaddr(msg.get('Reply-To', msg['From']))[1]
if from_addr != reply_to:
print(f'WARNING: From ({from_addr}) != Reply-To ({reply_to})')
else:
print('From and Reply-To match')
"# Extract URLs from email body
python3 << 'PYEOF'
import email
import re
from email import policy
with open('/cases/case-2024-001/email/phishing_email.eml', 'r') as f:
msg = email.message_from_file(f, policy=policy.default)
body = msg.get_body(preferencelist=('html', 'plain'))
if body:
content = body.get_content()
urls = re.findall(r'https?://[^\s<>"\']+', content)
print("=== URLs FOUND IN EMAIL BODY ===")
for url in set(urls):
print(f" {url}")
# Check for URL obfuscation (display text != href)
href_pattern = re.findall(r'<a[^>]*href=["\']([^"\']+)["\'][^>]*>(.*?)</a>', content, re.DOTALL)
print("\n=== HYPERLINK ANALYSIS ===")
for href, text in href_pattern:
display_url = re.findall(r'https?://[^\s<]+', text)
if display_url and display_url[0] != href:
print(f" MISMATCH: Display='{display_url[0]}' -> Actual='{href}'")
# Extract and hash attachments
print("\n=== ATTACHMENTS ===")
for part in msg.walk():
if part.get_content_disposition() == 'attachment':
filename = part.get_filename()
content = part.get_payload(decode=True)
import hashlib
sha256 = hashlib.sha256(content).hexdigest()
print(f" File: {filename}, Size: {len(content)}, SHA-256: {sha256}")
with open(f'/cases/case-2024-001/email/attachments/{filename}', 'wb') as af:
af.write(content)
PYEOF
# Submit attachment hashes to VirusTotal
# Submit URLs to URLhaus or PhishTank for reputation check| Concept | Description |
|---|---|
| SPF (Sender Policy Framework) | DNS record specifying authorized mail servers for a domain |
| DKIM (DomainKeys Identified Mail) | Cryptographic signature verifying email content integrity |
| DMARC | Policy framework combining SPF and DKIM for sender authentication |
| Received headers | Server-added headers showing each hop in the delivery chain (read bottom to top) |
| Return-Path | Envelope sender address used for bounce messages; may differ from From |
| Message-ID | Unique identifier assigned by the originating mail server |
| X-Originating-IP | Original sender IP address (added by some mail services) |
| Header forgery | Attackers can forge From, Reply-To, and other headers but not Received chains |
| Tool | Purpose |
|---|---|
| MXToolbox | Online email header analyzer and DNS lookup |
| dig/nslookup | DNS record queries for SPF, DKIM, DMARC verification |
| pyspf | Python SPF record validation library |
| dkimpy | Python DKIM signature verification library |
| PhishTool | Specialized phishing email analysis platform |
| VirusTotal | URL and file reputation checking service |
| AbuseIPDB | IP address reputation database |
| whois | Domain registration information lookup |
Scenario 1: CEO Fraud / Business Email Compromise The email claims to be from the CEO but Reply-To points to a Gmail address, SPF fails because the sending IP is not authorized for the spoofed domain, DKIM is missing, and the From domain is a lookalike (ceo-company.com vs company.com).
Scenario 2: Credential Harvesting Phishing Email contains a link that displays "login.microsoft.com" but href points to a lookalike domain, the attachment is an HTML file containing a fake login page with credential exfiltration JavaScript, the sending domain was registered 3 days ago.
Scenario 3: Malware Delivery via Attachment Email with an Office document attachment containing macros, the sender domain passes SPF but the account was compromised, DKIM signature is valid (sent from legitimate infrastructure), attachment SHA-256 matches known malware on VirusTotal.
Scenario 4: Spear Phishing with Legitimate Service Attacker uses a legitimate email marketing service to send phishing, SPF and DKIM pass because the service is authorized, the phishing is in the content not the infrastructure, requires URL and content analysis rather than header authentication checks.
Email Header Analysis Report:
Subject: "Urgent: Invoice Payment Required"
From: accounting@examp1e-corp.com (SPOOFED)
Reply-To: payments.urgent@gmail.com (MISMATCH)
Return-Path: <bounce@mail-server.xyz>
Date: 2024-01-15 09:23:45 UTC
Delivery Path (4 hops):
Hop 1: mail-server.xyz [203.0.113.45] -> relay1.isp.com
Hop 2: relay1.isp.com -> mx.target-company.com
Hop 3: mx.target-company.com -> internal-filter.target.com
Hop 4: internal-filter.target.com -> mailbox
Authentication:
SPF: FAIL (203.0.113.45 not authorized for examp1e-corp.com)
DKIM: NONE (no signature present)
DMARC: FAIL (p=none, no enforcement)
Indicators of Phishing:
- Lookalike domain (examp1e-corp.com vs example-corp.com, 96% similar)
- From/Reply-To mismatch
- Domain registered 2 days before email sent
- URL in body points to credential harvesting page
- Attachment: invoice.xlsm (SHA-256: a3f2...) - Known malware on VT
Risk Level: HIGH© 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-email-headers-for-phishing-investigation of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Analyzing Email Headers For Phishing Investigation 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 Email Headers For Phishing Investigation this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3.2k | 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 |
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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
Parse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing. Analyzing Email Headers For Phishing Investigation is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Parse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing.
Analyzing Email Headers For Phishing Investigation fits situations like: triaging a suspicious; investigating a phishing incident; verifying whether a messages sender domain was spoofed.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-email-headers-for-phishing-investigation -a claude-code`. Or copy the skill folder (skills/analyzing-email-headers-for-phishing-investigation in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-email-headers-for-phishing-investigation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-email-headers-for-phishing-investigation -a codex`. Or copy the skill folder (skills/analyzing-email-headers-for-phishing-investigation in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-email-headers-for-phishing-investigation 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-email-headers-for-phishing-investigation -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-email-headers-for-phishing-investigation, .gemini/skills/analyzing-email-headers-for-phishing-investigation, .github/skills/analyzing-email-headers-for-phishing-investigation and .opencode/skills/analyzing-email-headers-for-phishing-investigation in your project.
Going by SKILL.md and its folder, Analyzing Email Headers For Phishing Investigation needs Python for the scripts in its folder and the command-line tools its instructions call (python3, curl and pip). Our summary lists: Python 3; A credential in YOUR_API_KEY; A credential in YOUR_VT_API_KEY.
SKILL.md names 2 domains. In commands or code: api.abuseipdb.com and virustotal.com; the agent is likely to contact these when it follows the instructions. 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 Email Headers For Phishing Investigation 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 3.2k tokens (SKILL.md is roughly 13k 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 693 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Analyzing Email Headers For Phishing Investigation: 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.