AI Security/Agentic AI & MCP Security

Agentic AI & MCP Security

Agentic AI & MCP security testing for AI that can act

Your agents read, write and act with real credentials. We test them, and the MCP servers they call, from the agent’s position — the way an attacker who controls one input, document or tool response would — with findings mapped to every OWASP Agentic category in scope.

Agent goal hijack, tool misuse and memory and context poisoning
MCP server authentication, authorization and tool permissions
Non-human identities, token scope and human-approval bypass
A written pass condition and result for each OWASP Agentic category in scope

Scope my agent security test See how we test ↓

The credentials behind every engagement

2026 CyberSecurity Breakthrough Awards winner

Penetration Testing Solution of the Year2026 CyberSecurity Breakthrough Awards

Trusted by Fortune 100, financial services, insurance and SaaS security teams

The short answer

What is agentic AI security?

Agentic AI security is the protection of AI systems that plan, decide and act through tools, rather than only generating text. AI agent security covers the risks that come with that autonomy: an agent’s goal being hijacked by untrusted input, tools being misused, memory being poisoned, and agents acting with more privilege than they need.

MCP security is the part of it that deals with the Model Context Protocol, the standard many agents use to connect to tools and data. Testing MCP servers means checking how they authenticate and authorize requests, what each tool can do, and what happens when a tool description or response is written by an attacker.

You need agentic AI testing if

Your agents read email, web pages, tickets or documents from outside
Your agents call tools, APIs or MCP servers with real credentials
You are exposing your own MCP server to customers or partners
Agents can act without a human approving each step

Where agents break

Every tool an agent can call is an attack surface.

Agents cross trust boundaries all day: they read untrusted content, act through MCP servers and hold credentials. Here is where each OWASP Agentic risk shows up.

Diagram: untrusted inputs cross a trust boundary into an AI agent with planner, memory and human approval; the agent calls MCP servers through an MCP client across a second trust boundary to reach APIs, data and code execution, acting under tokens and service accounts. Chips mark where ASI01 to ASI10 are tested. — **Source:** OWASP Top 10 for Agentic Applications (OWASP GenAI Security Project, December 2025); Model Context Protocol specification; ioSENTRIX test methodology.

What we test

What we test in agentic AI systems

Coverage is mapped to the OWASP Top 10 for Agentic Applications.

Behavior

Agent behavior

Can untrusted input change what the agent is trying to do?

Agent goal hijack
Indirect injection via tools
Memory & context poisoning
Cascading failures across steps

Tools

Tools & MCP servers

Every tool an agent can call is an attack surface.

MCP server authorization
Over-permissioned tools
Untrusted tool descriptions
Unexpected code execution

Identity

Identity & privilege

Agents act with credentials. We test what they can reach.

Non-human identity review
Token scope & audience checks
Privilege escalation paths
Human approval bypass

Ecosystem

Multi-agent & supply chain

Where agents trust each other and third-party components.

Inter-agent communication
Agentic supply chain
Rogue agent scenarios
Logging & audit evidence

Methodology

How we test: example test cases

A sample of the test cases in a typical agentic AI engagement, each with a written pass condition.

ASI01

Goal hijack through a tool response

We control a web page, email or API response the agent reads and check whether it abandons the user’s task for ours.

ASI02

Tool misuse within granted permissions

We push the agent to use a legitimate tool in a harmful way, such as deleting records or emailing data out.

ASI03

Identity and privilege abuse

We map what the agent’s tokens can reach and try to use the agent to act beyond the user’s own permissions.

ASI04

Untrusted MCP tool descriptions

We change a tool’s name, description or schema and test whether the agent trusts it without checking.

ASI06

Memory and context poisoning

We plant false facts or instructions in agent memory and test whether they change later sessions.

ASI09

Approval manipulation

We test whether the agent can present a risky action in a misleading or authoritative way so that a human reviewer approves it.

Sample finding

What a finding looks like in our report

An illustrative example in our report format. Not client data.

Finding 01 · IllustrativeCritical

A poisoned GitHub issue makes a coding agent push a credential to a public gist

OWASP Agentic ASI01 Agent Goal Hijack · ASI02 Tool Misuse and Exploitation

What we found

The agent triages new issues with an MCP server that exposes repository, file and gist tools. An issue body carried instructions to read the deployment config and publish it as a gist for debugging. The agent followed them, because the gist tool was available and no step required approval.

Impact

Anyone who can open an issue can exfiltrate secrets the agent can read.

How to fix it

Remove the gist tool from the triage agent, scope its token to read-only issue access, and require human approval for any tool that publishes content outside the organization.

What you get

What you get from an agentic AI test

A result per category, with the evidence to back it.

Results mapped to the OWASP Agentic Top 10

Each in-scope category gets a written pass condition, a result, evidence and severity.

MCP server and tool review

How each MCP server authenticates and authorizes, what each tool can do, and where permissions exceed need.

Identity and privilege map

What every agent identity can reach, the escalation paths we found and the fix for each.

ioSENTRIX sample penetration test report cover

See how we write findings before you talk to us

A redacted sample penetration test report (web application) — finding write-ups, proof-of-concept evidence and remediation. No form required.

Download the sample report (PDF) →

Verified reviews

What security leaders say about working with us

★★★★★

“Unlike other providers, Omair and his team truly dive deep into our infrastructure, delivering findings that go well beyond the surface level. Communication is direct and seamless.”

Jesus B.

Cybersecurity Manager, Banking

Verified G2 review ↗

★★★★★

“We were impressed with ioSENTRIX’s ability to independently validate the security of our customer-facing product.”

Zeehasham R.

Data Scientist, Security Operations · CNA

Verified Clutch review ↗

★★★★★

“The team at ioSENTRIX is professional and highly skilled at their craft.”

Awwab A.

SVP, Chief Information Security Officer

Verified G2 review ↗

How it works

How we test an agentic AI system

A test is only useful if it has a written pass condition. Every category we test gets one.

Map the agent

Goals, tools, MCP servers, identities, data sources and the actions each can take.

Week 1

Threat model

Attack paths mapped to the OWASP Top 10 for Agentic Applications, with a pass condition for each.

Before testing

Test from the agent’s position

We control inputs, documents and tool responses the way an attacker could, and record what the agent does.

Most of the engagement

Report pass or fail

A result per category, with evidence, severity and the fix for each failure.

At close

Reply within 1 business day → fixed quote in writing → engagements from 2 weeks → pass/fail report and walkthrough

How we compare

Agents need more than a prompt test

What agentic AI testing covers compared with the usual alternatives.

ioSENTRIX agentic testing

Prompt-only LLM testing

Standard API pentest

Tests what the agent does

Yes — tool calls, identity and downstream effects

No — model output only

Partly — APIs, not agent behavior

MCP coverage

Server auth, tool permissions, untrusted tool descriptions

Not covered

Endpoints only

Standard

OWASP Top 10 for Agentic Applications

OWASP LLM Top 10 only

OWASP API Top 10

Result

Pass/fail per category with evidence

Prompt pass rate

Finding list

Scope my agent security test

Scope and price

What affects the scope and price of an agentic AI test

Agentic engagements are priced on effort. These are the decisions that move the quote.

What moves the quote

01How many agents, and how many steps each can take
02How many tools and MCP servers they can call
03Which identities and tokens the agents hold
04Whether multi-agent communication is in scope
05Test environment, or limited actions against production systems

Read: How do you penetration test an AI agent? →

What we need from you to start

A list of agents, their goals and the tools or MCP servers each can call
A test environment with the same tools wired in
Test identities that mirror the agents’ real permissions
Logs or traces of agent actions, if you have them

Scope my agent security test

Proof, not promises

AI systems we have already tested

A real engagement, described without the client’s name.

Case study

Fortune 500 financial services: AI/ML threat model across AWS and Azure

We threat-modeled the client’s AI estate — RAG pipelines, LLM orchestration layers and ML inference workflows — using STRIDE, NIST SP 800-30 and the NVIDIA AI Red Team framework.

Read the case study →

30+

AI components reviewed across AWS and Azure

threats identified and mapped

high-severity threats in RAG, orchestration and inference

Clients: Fortune 100, financial services, insurance and SaaS. Engagements: 2 weeks to 4 months, quoted on effort.

RAG systemsCustom LLM pipelines & trainingChatbotsOrganization-wide AI enablementAI features in SaaS productsMCP testing

Track record

Numbers you can check

Ratings you can verify on G2 and Clutch.

4.9 / 5

on G2 from 12 verified reviews

5.0 / 5

on Clutch, Premier Verified

2017

founded; CREST-accredited, ISO 27001 certified, SOC 2 Type 2 attested

Who you work with

Who does the testing

Offensive security engineers do the hands-on testing and write up the findings, so the person who found an issue explains it to your team.

Certified testers

Each tester holds one or more of OSCP, OSWE, OSCE, CISSP, CISA or AWS security certifications.

Accredited firm

ioSENTRIX is CREST-accredited for penetration testing, ISO/IEC 27001 certified and SOC 2 Type 2 attested.

Since 2017

Founded in 2017, with offensive security work for Fortune 100, financial services, insurance and SaaS companies.

Do you know what your agents could be tricked into doing?

A senior engineer replies within 1 business day · no sales pitch

Scope my agent security test

Standards

Frameworks we test and map to

◆OWASP Top 10 for LLM Applications◆OWASP Top 10 for Agentic Applications◆MITRE ATLAS◆NIST AI RMF◆ISO/IEC 42001◆STRIDE

FAQ

Frequently asked questions

What is MCP security testing?

The Model Context Protocol (MCP) lets AI agents connect to tools and data sources through MCP servers. MCP security testing checks how those servers authenticate and authorize requests, what each tool can do, and whether an agent can be tricked into calling a tool in a harmful way. Read our guide to MCP security.

Do you test against the OWASP Top 10 for Agentic Applications?

Yes. The OWASP GenAI Security Project published the OWASP Top 10 for Agentic Applications in December 2025. We map our test cases and findings to its ten categories, from agent goal hijack to rogue agents.

Have you tested MCP servers before?

Yes. MCP testing is one of the AI engagement types we run.

How long does it take, and how is it priced?

Engagements run from 2 weeks to 4 months depending on the number of agents, tools and environments. Each is a fixed quote based on effort, bought with PTaaS credits or a subscription.

What security gaps do AI agents create?

AI agents turn untrusted content into actions. The biggest risks are goal hijack through content the agent reads, misuse of legitimate tools, agents holding broader credentials than the user, poisoned memory, and actions that bypass human approval. The OWASP Top 10 for Agentic Applications lists ten such risks, from ASI01 Agent Goal Hijack to ASI10 Rogue Agents.

How do you test an MCP server?

We test how the server authenticates clients and authorizes each tool call, whether tools expose more than the agent needs, how it handles malicious input and tool responses, and whether clients trust its tool descriptions. Read how to test an MCP server for security issues.

Resources

Go deeper before you scope a test

Practical guides from our testers on the questions buyers ask most.

Flat illustration of an AI agent chip wired to three tool cards, one carrying an orange seal where an action fired, with a magnifier alongside

Guide · 12 min read

How Do You Penetration Test an AI Agent?

Forty prompt-injection payloads, none successful, risk low — and six weeks later the agent refunds the same customer twice. The unit of an agent test…

Read the guide →

Flat illustration of an MCP server card with three tool rows refusing a token offered from the left, an orange cross marking the refusal, with a magnifier alongside

Guide · 13 min read

How Do You Test an MCP Server for Security Issues?

An MCP server is an API with an unusually trusting client and an unusually powerful backend. Testing it means exposure and transport, three…

Read the guide →

Flat vector illustration of an AI agent action being checked against four assessment questions, ioSENTRIX blog hero

Guide · 9 min read

The Four Questions You Can't Answer About Your AI Agents

Boards ask four questions about AI agents, and the honest answer is usually “we believe so.” Here is how each one maps to a concrete assessment…

Read the guide →

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Ready when you are

Test your agents before they act on an attacker’s behalf

Tell us what your agents can do. We will scope a test mapped to the OWASP Agentic Top 10 and send a fixed quote based on effort.

A senior engineer replies within 1 business day · Fixed quote in writing before work starts · Your details are never shared