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Exchange Owa Attack

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uphiago
exchange-owa-attack

Exchange/OWA NTLM AD leak, spray attack when mail subdomain.

Overview

Publisheruphiago
Repositoryrecon-skills
Skill nameexchange-owa-attack
Stars
1.3K
Forks
213
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by uphiago on GitHub. Read the source before you install it.

Installation

Install the Exchange Owa Attack AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/uphiago/recon-skills.git /tmp/recon-skills
mkdir -p .claude/skills
cp -r /tmp/recon-skills/recon/exchange-owa-attack .claude/skills/exchange-owa-attack
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exchange Owa Attack in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Exchange Owa Attack on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Exchange Owa Attack is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Exchange/OWA Attack Skill

Exchange Outlook Web Access reconnaissance covering endpoint mapping, NTLM Type-2 metadata, authentication controls, and version evidence. Password or lockout testing requires explicit authorization and approved identities.

When to Use

  • Target has owa., mail., webmail., exchange., or autodiscover. subdomains.
  • crt.sh reveals Exchange-related SAN names (mail.domain.com, autodiscover.domain.com).
  • Port 443 returns NTLM WWW-Authenticate: Negotiate or WWW-Authenticate: NTLM.
  • After subdomain-enumeration discovers mail-related hosts.
  • After port-service-discovery finds HTTPS on port 443 with Exchange fingerprints.

Prerequisites

  • terminal with curl, python3.
  • Target Exchange/OWA URL.
  • For password spray: list of usernames (from recon) and password candidates.

How to Run

bash
# Quick Exchange detection
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/owa/" | grep -iE "x-owa-version|x-feserver|exchange|microsoft"

# NTLM challenge capture (AD domain leak)
curl --max-time 30 --connect-timeout 10 -skI "https://TARGET/owa/" -H "Authorization: Negotiate TlRMTVNTUAABAAAAB4IIogAAAAAAAAAAAAAAAAAAAAAGAbEdAAAADw==" | grep -i "www-authenticate"

Quick Reference

TechniqueWhat It RevealsSeverity
NTLM Type-2 decodeAD domain, NetBIOS name, computer name, AD timestampHigh
OWA version headerExchange version, CU level, patch statusMedium
/owa/auth/logon.aspxLogin page, brute force surfaceMedium
/ecp/Exchange Control Panel (admin)High
/ews/Exchange Web Services (SOAP API)Medium
/autodiscover/Autodiscover configurationMedium
/mapi/MAPI over HTTPLow
/Microsoft-Server-ActiveSyncMobile device syncMedium
/rpc/Outlook Anywhere (RPC over HTTP)Low

Procedure

Phase 1 — Exchange Detection & Fingerprinting

bash
TARGET="$1"
OUTDIR="$OUTDIR/exchange"
mkdir -p "$OUTDIR"

echo "[*] Exchange detection on $TARGET"

# OWA probe
OWA_RESP=$(curl -skI --max-time 10 --connect-timeout 10 "https://$TARGET/owa/" 2>/dev/null)
echo "$OWA_RESP" > "$OUTDIR/owa_headers.txt"

# Version extraction
X_OWA=$(echo "$OWA_RESP" | grep -i "x-owa-version" | sed 's/.*: //')
X_FE=$(echo "$OWA_RESP" | grep -i "x-feserver" | sed 's/.*: //')

if [[ -n "$X_OWA" ]]; then
  echo "[+] Exchange confirmed — OWA Version: $X_OWA"
  echo "  Frontend server: ${X_FE:-unknown}"

  # Map version to CU
  # 15.1.x = Exchange 2016, 15.2.x = Exchange 2019
  MAJOR=$(echo "$X_OWA" | cut -d. -f1-2)
  if [[ "$MAJOR" == "15.1" ]]; then
    echo "  Product: Exchange 2016"
  elif [[ "$MAJOR" == "15.2" ]]; then
    echo "  Product: Exchange 2019"
  fi
else
  echo "[-] No OWA version header — may not be Exchange"
fi

# Key endpoints probe
declare -A EX_ENDPOINTS
EX_ENDPOINTS["/owa/auth/logon.aspx"]="Login page"
EX_ENDPOINTS["/ecp/"]="Exchange Control Panel (admin)"
EX_ENDPOINTS["/ews/exchange.asmx"]="Exchange Web Services (SOAP)"
EX_ENDPOINTS["/autodiscover/autodiscover.xml"]="Autodiscover"
EX_ENDPOINTS["/mapi/emsmdb/"]="MAPI over HTTP"
EX_ENDPOINTS["/Microsoft-Server-ActiveSync/"]="ActiveSync"
EX_ENDPOINTS["/rpc/rpcproxy.dll"]="Outlook Anywhere"
EX_ENDPOINTS["/owa/healthcheck.htm"]="Health check"

echo ""
echo "[*] Endpoint probe:"
for ep in "${!EX_ENDPOINTS[@]}"; do
  code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 5 --connect-timeout 5 "https://$TARGET$ep")
  [[ "$code" == "200" ]] && echo "  [OPEN] $ep${EX_ENDPOINTS[$ep]}"
  [[ "$code" == "302" ]] && echo "  [REDIR] $ep${EX_ENDPOINTS[$ep]}"
  [[ "$code" == "401" ]] && echo "  [AUTH] $ep${EX_ENDPOINTS[$ep]}"
done

Phase 2 — NTLM Type-2 Challenge Capture & Decode

bash
TARGET="$1"

echo "[*] NTLM challenge capture from $TARGET"

# Send NTLM Type-1 (Negotiate) message via Authorization header
NTLM_RESP=$(curl -skI --max-time 10 --connect-timeout 10 "https://$TARGET/owa/" \
  -H "Authorization: Negotiate TlRMTVNTUAABAAAAB4IIogAAAAAAAAAAAAAAAAAAAAAGAbEdAAAADw==" 2>/dev/null)

WWW_AUTH=$(echo "$NTLM_RESP" | grep -i "www-authenticate: negotiate" | sed 's/.*negotiate //i' | tr -d '\r\n ')

if [[ -n "$WWW_AUTH" ]]; then
  echo "[+] NTLM Type-2 challenge received!"
  echo "  Raw: ${WWW_AUTH:0:80}..."

  # Decode with Python (extract AV_PAIRS structure)
  echo "$WWW_AUTH" | python3 -c "
import base64, struct, sys

data = base64.b64decode(sys.stdin.read().strip())

# NTLM Type-2 message structure:
# Offset 12: Target Name
# Offset 16: Negotiate Flags
# Offset 20: Server Challenge
# Offset 28: Reserved
# Offset 32: Target Info (AV_PAIRS)

# Parse Target Info
if len(data) > 40:
    target_info_offset = struct.unpack_from('<I', data, 40)[0]
    target_info_len = struct.unpack_from('<I', data, 44)[0]
    av_pairs = data[target_info_offset:target_info_offset + target_info_len]

    print()
    print('=== NTLM Type-2 Decoded ===')
    pos = 0
    while pos < len(av_pairs) - 4:
        av_type = struct.unpack_from('<H', av_pairs, pos)[0]
        av_len = struct.unpack_from('<H', av_pairs, pos + 2)[0]
        av_value = av_pairs[pos + 4:pos + 4 + av_len]

        # AV_PAIR types
        types = {
            1: 'NetBIOS Computer Name',
            2: 'NetBIOS Domain Name',
            3: 'DNS Computer Name',
            4: 'DNS Domain Name',
            5: 'DNS Tree Name',
            6: 'Product Version',
            7: 'Timestamp',
        }
        label = types.get(av_type, f'Unknown({av_type})')
        if av_type in (1, 2, 3, 4, 5):
            value = av_value.decode('utf-16-le', errors='replace')
            print(f'  {label}: {value}')
        elif av_type == 7:
            ts = struct.unpack_from('<Q', av_value)[0]
            from datetime import datetime, timezone
            dt = datetime.fromtimestamp(ts / 10000000 - 11644473600, tz=timezone.utc)
            print(f'  Timestamp: {dt}')
        else:
            print(f'  {label}: {av_value.hex()}')

        pos += 4 + av_len
else:
    print('  No AV_PAIRS in response')
"
fi

Phase 3 — Password Spray Surface Assessment

bash
TARGET="$1"

echo "[*] Password spray surface assessment"

# Check for account lockout by testing rapid logins with invalid password
echo "[*] Rate limiting test (5 rapid attempts with wrong password)..."
for i in $(seq 1 5); do
  code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 10 --connect-timeout 10 \
    -X POST "https://$TARGET/owa/auth.owa" \
    -d "destination=https://$TARGET/owa/&username=testuser$i@domain.com&password=WrongPass123!" 2>/dev/null)
  echo "  Attempt $i: HTTP $code"
done

# Check if Basic Auth is enabled (rare post-2022, but exists)
BASIC_AUTH=$(curl -skI --max-time 5 --connect-timeout 5 "https://$TARGET/owa/" \
  -H "Authorization: Basic dGVzdDp0ZXN0" 2>/dev/null | grep -i "www-authenticate.*basic")
if [[ -n "$BASIC_AUTH" ]]; then
  echo "  [!] Basic Auth ENABLED — easier brute force vector"
fi

# Check healthcheck endpoint (sometimes exposes version/config)
HEALTH=$(curl -sk --max-time 5 --connect-timeout 5 "https://$TARGET/owa/healthcheck.htm" 2>/dev/null)
if [[ -n "$HEALTH" ]] && echo "$HEALTH" | grep -qi "200 ok"; then
  echo "  [+] Healthcheck accessible — server status exposed"
fi

Phase 4 — ADFS/Office 365 Recon (hybrid environments)

bash
TARGET_DOMAIN="$1"  # e.g., company.com

echo "[*] ADFS/Office 365 recon on $TARGET_DOMAIN"

# Check for ADFS
ADFS_URL="https://sts.$TARGET_DOMAIN/adfs/ls/IdpInitiatedSignOn.aspx"
ADFS_CODE=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 5 --connect-timeout 5 "$ADFS_URL")
[[ "$ADFS_CODE" == "200" || "$ADFS_CODE" == "302" ]] && echo "  [+] ADFS: $ADFS_URL (HTTP $ADFS_CODE)"

# Check Office 365 tenant
O365_XML=$(curl -sk --max-time 5 --connect-timeout 5 "https://login.microsoftonline.com/getuserrealm.srf?login=user@$TARGET_DOMAIN&xml=1" 2>/dev/null)
if echo "$O365_XML" | grep -qi "Federated\|Managed"; then
  echo "  [+] Office 365 tenant: $(echo "$O365_XML" | grep -Eo '<NameSpaceType>\K[^<]+')"
  echo "  $(echo "$O365_XML" | grep -Eo '<DomainName>\K[^<]+')"
fi

# Autodiscover (leaks internal server names)
AUTODISCOVER=$(curl -sk --max-time 10 --connect-timeout 10 "https://autodiscover.$TARGET_DOMAIN/autodiscover/autodiscover.xml" \
  -H "Content-Type: text/xml" \
  -d '<?xml version="1.0"?><Autodiscover xmlns="http://schemas.microsoft.com/exchange/autodiscover/outlook/requestschema/2006"><Request><EMailAddress>user@'$TARGET_DOMAIN'</EMailAddress><AcceptableResponseSchema>http://schemas.microsoft.com/exchange/autodiscover/outlook/responseschema/2006a</AcceptableResponseSchema></Request></Autodiscover>' 2>/dev/null)
if echo "$AUTODISCOVER" | grep -qi "server\|internal"; then
  echo "  [+] Autodiscover response — internal server names leaked"
  echo "$AUTODISCOVER" | grep -Eo '(?:<Server>|<InternalRpcClientServer>|<ASUrl>)[^<]+' | head -5
fi

Pitfalls

  • NTLM relay requires specific network position. Unless you control a machine the Exchange server can reach, NTLM relay is not exploitable remotely.
  • Modern Exchange (Exchange Online, 2019+) blocks Basic Auth by default. Test with Modern Auth (OAuth2) if Basic is blocked.
  • Account lockout policies vary. Test with a single known-bad password before spraying.
  • ADFS is NOT Exchange. ADFS is a separate service with its own attack surface (SAML, WS-Trust).

Verification

  • NTLM Type-2 MUST decode to reveal at minimum DNS Domain Name and NetBIOS Domain Name.
  • OWA version MUST be extracted from X-OWA-Version header.
  • Password spray surface: confirm NO rate limiting (5 rapid attempts all return the same HTTP code).
  • Autodiscover MUST return internal server names (not just external URLs).
  • Document: Exchange version, AD domain, NetBIOS name, computer names, rate limiting status.

Related Skills

  • password-spray-methodology — Universal password spray pipeline across all protocols + error code differentials

Frequently asked questions

What does the Exchange Owa Attack AI skill do?

Exchange/OWA NTLM AD leak, spray attack when mail subdomain.

Why use Exchange Owa Attack on TypingMind?

Because you install it once and use it with any model. Exchange Owa Attack is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Exchange Owa Attack in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/uphiago/recon-skills/tree/main/recon/exchange-owa-attack. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Exchange Owa Attack?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Exchange Owa Attack?

As many as you like. As long as a model supports skills, you can use Exchange Owa Attack with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Exchange Owa Attack AI skill free?

Yes. It is published on GitHub by uphiago under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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