MCP Server Pentesting

MCP server security testing

Your MCP servers connect AI assistants to databases, file systems, and internal APIs. We test whether an attacker can exploit that connection.

Fixed scope. Tool-by-tool evidence. Retest included within 30 days.

157+

GitHub stars on vulnerable-mcp-servers-lab

9

MCP vulnerability categories documented

13

Phase testing methodology

Checklist

Authors of the public MCP pentesting checklist

Our MCP security work is public and practitioner-led — including the MCP pentesting checklist (23+ GitHub stars) and the vulnerable MCP servers lab (157+ GitHub stars).

What's at risk

MCP turns model output into system access.

MCP servers let assistants invoke tools, read resources, and act on connected systems. When those servers are vulnerable, prompt-layer attacks can become database queries, file reads, internal API calls, or workflow actions.

Command injection through tool parameters
Context poisoning via hidden instructions in tool descriptions
Data exfiltration through side channels
Tool shadowing - malicious tool overrides a trusted one
Privilege escalation via tool chaining
Authentication hijacking through OAuth/token flaws

What we test

Six MCP security domains, tested against your implementation.

Each domain maps to a concrete failure mode in MCP deployments: transport trust, unsafe tools, prompt-to-tool abuse, resource exposure, credential handling, and supply chain trust.

Transport & Connection Security

We test stdio, HTTP, and SSE transport boundaries for tampering, replay, exposure, and unsafe trust assumptions.

Tool Safety & Parameter Validation

We exercise every tool parameter for command injection, traversal, SSRF, unsafe parsing, and missing validation.

Prompt Injection & Data Leakage

We trace whether malicious content can change model behavior, expose secrets, or leak data through tool outputs.

Resource Access Controls

We verify which files, databases, APIs, and tenant resources the server can reach and whether boundaries hold.

OAuth & Credential Hygiene

We review scopes, token storage, refresh flows, logs, and multi-user isolation for credential abuse paths.

Supply Chain & Trust

We check package provenance, dependency exposure, tool registration integrity, and malicious-server assumptions.

Our credibility

We don't just test MCP servers. We built the tools the industry uses to learn about MCP security.

Our assessment approach is grounded in public research, intentionally vulnerable labs, and hands-on tooling for real MCP server behavior. That means the test plan is not a generic AI checklist with MCP wording added later.

9 documented vulnerability categories

Tool poisoning Rug pull attacks Tool shadowing Command injection Prompt injection Context poisoning Data exfiltration OAuth abuse Supply chain compromise

pentesting-mcp-servers-checklist

The public checklist used by security teams worldwide

23+ stars

vulnerable-mcp-servers-lab

Training lab with intentionally vulnerable MCP servers

157+ stars

mcp-client-and-proxy

Interception tooling for stdio-based MCP servers

12+ stars

How it works

A focused MCP assessment from map to verified fixes

We start with the actual servers and tools you run, then test the places where AI interpretation meets system access.

Step 1

Map the environment

Enumerate servers, tools, resources, transport, auth, and runtime boundaries.

What happens

We build an inventory of MCP servers, exposed tools, resource permissions, trust boundaries, transport modes, and authentication flows.

What you do

Share the server list, access paths, architecture notes, and rules of engagement.

What we do

Confirm the test matrix and mark the highest-risk tool and data paths before active testing starts.

What comes next

A clear assessment map anchors every finding to the server, tool, and resource it affects.

Step 2

Test every tool

Run injection, traversal, SSRF, and unsafe parsing checks on each parameter.

What happens

Each tool is exercised with adversarial inputs, malformed requests, boundary bypass attempts, and chained tool-call scenarios.

What you do

Provide safe test data or staging access where destructive behavior must be avoided.

What we do

Record reproducible evidence and separate exploitable issues from defensive noise.

What comes next

You receive a tool-by-tool matrix that makes remediation ownership clear.

Step 3

Test the data flow

Probe prompt injection at every stage of the prompt, resource, tool, and response pipeline.

What happens

We test whether hidden instructions, tool descriptions, resource content, and retrieved data can alter behavior or leak information.

What you do

Identify sensitive data classes, tenant boundaries, and content sources in scope.

What we do

Trace attack paths through model context, tool outputs, side channels, and downstream systems.

What comes next

Findings show how data moves, where trust is misplaced, and how to reduce exposure.

Step 4

Review credentials and auth

Assess secret storage, token handling, OAuth flows, scopes, and tenant isolation.

What happens

We inspect how credentials are stored, passed, logged, refreshed, scoped, and isolated across users and servers.

What you do

Share the intended permission model and any constraints for tokens or connected services.

What we do

Look for scope creep, token leakage, replay paths, weak OAuth assumptions, and auth confusion.

What comes next

Credential findings include least-privilege recommendations and validation steps.

Step 5

Verify supply chain

Audit dependencies, package provenance, and tool registration integrity.

What happens

We review installed MCP packages, dependency vulnerabilities, malicious-server assumptions, and whether registered tools can be trusted.

What you do

Provide package manifests, deployment details, and approved source locations.

What we do

Check provenance, dependency risk, update posture, and integrity controls around server registration.

What comes next

You receive a defensible inventory and prioritized fixes for trust and dependency gaps.

Talk through your MCP scope
3-5 days for a single server
5-10 days for multi-server ecosystems
Retest included within 30 days

Who this is for

MCP testing matters when AI assistants can reach systems that were never designed to be prompt-facing.

Building MCP servers

You are shipping integrations to customers and need confidence that exposed tools cannot be abused.

You receive:

Tool-by-tool assessment matrix with reproducible findings

Deploying AI assistants internally

You are connecting assistants to internal tools, files, databases, or workflows used by your team.

You receive:

Access boundary review and configuration recommendations

Shipping AI features

You are embedding AI capabilities in a product and need evidence for customers, security, or leadership.

You receive:

Integration security report with attack-path narratives

Pricing

Fixed pricing for MCP server security testing.

Scope depends on the number of servers, exposed tools, connected resources, tenant model, and auth complexity.

Scope
Price
Duration
Single MCP server (< 10 tools)
$3,500-$5,000
3-5 days
Multi-server (2-5 servers)
$7,500-$12,500
5-7 days
Enterprise (5+ servers, multi-tenant)
From $15,000
7-10 days
Add-on to existing pentest
$2,000-$3,500
1-2 days

Fixed price. No hourly. Quote in 48 hours. Retest included within 30 days.

What you get

Report artifacts your engineers can act on.

The output is built for remediation, review, and proof. You get the attack path, the affected tool or resource, and the specific change needed to close the issue.

Executive summary with prioritized findings
Technical report with attack-path narratives
Tool-by-tool assessment matrix
Remediation guidance specific to your MCP framework
Supply chain audit results
Verification letter / attestation on request
Walkthrough call included
One free retest within 30 days

Explore the MCP security surface

Related MCP security services and resources

Continue from the concept into testing scope, implementation risks, tools, and adjacent AI security topics.

Service

MCP Server Security Testing

Scoped testing for transport security, tool safety, prompt injection, OAuth hygiene, and access boundaries.

Service

AI & MCP Security Testing

Product security testing for AI apps, agent workflows, MCP tools, prompts, and connected data sources.

Glossary

Prompt Injection

How malicious instructions enter prompts through users, documents, retrieved content, and tool output.

Glossary

AI Agent Security

Security controls for agents that use tools, memory, approvals, and connected workflows.

Glossary

LLM Security

Risks and controls for LLM applications, RAG systems, embeddings, and model-connected workflows.

Training

Pentesting MCP Servers Masterclass

A focused training page on attacking MCP servers, tool definitions, prompt injection, and assessment methodology.

Tool

MCP Pentesting Checklist

Open-source checklist for reviewing MCP server security, tool safety, auth boundaries, and data exposure paths.

Tool

Universal MCP Client

Appsecco testing client and proxy for exercising MCP servers during security reviews.

Tool

Vulnerable MCP Servers Lab

Intentionally vulnerable MCP servers for learning attack paths and validating defensive controls.

Safe next step

Test your MCP serversbefore someone else does

Share what your MCP servers can reach and how they are used. We will outline a scoped assessment, answer questions, and give you a fixed quote before any work begins.

Start a conversation

or download the MCP pentesting checklist first

No sales pressure
Fixed pricing
You decide pace