AI Agent Penetration Testing
AI agents act with real permissions and call real tools. We test what happens when an attacker manipulates them — prompt injection into tool abuse, data exfiltration and unsafe autonomous actions.
What is AI Agent Penetration Testing?
AI agents act with real permissions and call real tools, which turns a prompt-injection into a real-world action. We test the whole chain — injection into tool abuse, data exfiltration and unsafe autonomous decisions — against your actual tool-set and permissions.
An AI agent is dangerous precisely because it's useful: it holds permissions, calls tools and acts autonomously, which means a successful prompt injection isn't just bad text — it's a real action taken with your credentials. We test the whole chain, from an injection hidden in the content the agent reads to the tool it can be coerced into calling, against your actual permissions and guardrails rather than a generic model.
Agent testing also confronts a new and unintuitive trust boundary: the content an agent reads is effectively code it might execute. A calendar invite, a webpage, a support ticket — anything the agent ingests can carry instructions, and if the agent has tools and permissions, those instructions become actions. We test that boundary explicitly, because most teams haven't yet internalised that data is now a control channel.
AI Agent Penetration Testing is a manual, exploit-driven assessment: real people attacking your target the way an adversary would, then proving each finding with a working proof of concept. It is not an automated scan with a logo on it — the point is to find and demonstrate the issues that actually put you at risk, and hand your team a clear plan to fix them.
Why it matters
AI systems introduce an entirely new attack surface on top of the classic ones. Prompt injection, unsafe tool use and data leakage are already being exploited in production, and traditional testing doesn't cover them.
A ai agent penetration testing engagement replaces guesswork with evidence. Instead of hoping your controls hold, you get a ranked, reproducible picture of where they don’t — before someone hostile finds the same gaps.
Industries & use cases
AI agent testing matters for any product embedding autonomous agents — customer support, coding assistants, workflow automation, financial and data-access agents — where a manipulated agent can move money, leak data or take destructive action.
What we test
Manual, exploit-driven coverage focused on real impact — not scanner noise.
- Direct and indirect prompt injection
- Tool and function-call abuse
- Excessive agent permissions
- Data exfiltration via agent actions
- Unsafe autonomous decisions
- Guardrail and policy bypass
Signs you should run a ai agent penetration testing
If any of these apply, testing is overdue.
- You've deployed or are building autonomous agents
- Your agent can call tools, APIs or take actions
- The agent handles or can reach sensitive data
- You allow the agent to read untrusted external content
- You have no egress or action controls on the agent
Common vulnerabilities we find
The issues that show up again and again in ai agent penetration testing — and the ones that actually get exploited.
Indirect prompt injection
Instructions hidden in content the agent reads then obeys.
Tool abuse
Coercing the agent to call tools beyond intended use.
Excessive permissions
An agent able to take damaging actions with no guardrail.
Confused-deputy tool use
The agent uses its privileges on behalf of an attacker's instruction.
Missing egress and action controls
No limits on what data the agent can send or what actions it can take.
Tool-chaining to reach unintended actions
Legitimate tools combined to achieve an attacker's goal.
Insufficient human-in-the-loop on high-risk actions
Sensitive actions taken autonomously without confirmation.
Context and memory poisoning
Persistent state manipulated to influence future decisions.
Example attack chain
Real impact rarely comes from one bug — it comes from chaining several. A representative example:
Why choose webhook.press
Attacker mindset
We’re offensive security people who also build the free tools bug-bounty hunters use daily. We test the way real adversaries do — and prove it.
No scanner theatre
You get findings a human exploited and verified, ranked by real business risk — not an unfiltered tool dump padded to look thorough.
Fixed price, free retest
A clear quote after scoping, a report your team and auditors can use, and a free retest to confirm the fixes hold.
Our methodology
A structured, transparent process aligned to OWASP and PTES — with a named point of contact throughout.
Scoping & rules of engagement
We agree the exact targets, depth, timing and constraints for your ai agent penetration testing, and set clear rules of engagement so testing is safe and predictable.
Reconnaissance & mapping
We enumerate the full attack surface — endpoints, roles, technologies and trust boundaries — and threat-model where an attacker would focus.
Manual testing & exploitation
We attack by hand, verifying and chaining weaknesses into real impact. Automated tooling supports coverage; humans find the logic and authorization bugs it can’t.
Analysis & risk rating
Each finding is validated, rated by real business risk rather than raw scanner severity, and de-duplicated so you get signal, not noise.
Reporting
You receive an executive summary for leadership and a technical section with reproducible PoCs, evidence and concrete, stack-specific remediation.
Free retest
After you remediate, we re-test the closed findings to confirm they are actually fixed — at no extra cost.
What you get
Reproducible PoCs
Every finding ships with a working proof and step-by-step reproduction your engineers can replay and verify.
Risk-ranked findings
Prioritised by real business impact, so you fix what matters first instead of drowning in low-severity noise.
Actionable remediation
Concrete, stack-specific fixes and guidance — not generic “apply best practice” filler.
Free retest
We re-check the closed findings after remediation and confirm they’re resolved.
The report is written for two audiences at once: an executive summary that a non-technical stakeholder can act on, and a detailed technical section — findings, evidence, CVSS and reproduction — that your developers and auditors can use directly.
Manual testing, not just a scan
Automated scanners are fast and useful for coverage, but they only find patterns they already know, and they flood you with false positives. They cannot understand your business logic, chain several small issues into a breach, or tell you which alert actually matters. Our ai agent penetration testing is led by experienced testers who exploit findings by hand and rank them by the damage they’d really do — the difference between a 300-page tool dump and a short list of things worth fixing.
Standards & compliance
Our ai agent penetration testing reports are written to support the frameworks your auditors and customers care about — including SOC 2, ISO 27001, PCI DSS, HIPAA, GDPR, and the EU’s NIS2 and DORA. Each engagement produces clear, independent evidence of testing with scope, methodology and findings documented the way assessors expect, so the same test both hardens your systems and helps satisfy your obligations.
Frameworks we follow
Recognised methodologies, adapted to your target — never a rigid checklist.
- OWASP — Web Security Testing Guide, ASVS and the API Security Top 10
- PTES — the Penetration Testing Execution Standard
- NIST SP 800-115 — technical guide to security testing
- OSSTMM — Open Source Security Testing Methodology Manual
- MITRE ATT&CK — to frame real-world adversary techniques
FAQ
What is agentic risk?
Agents combine an LLM with tools and permissions — a prompt-injection can become a real action (send email, move money, delete data). We test that chain.
Do you test our specific tools?
Yes — we test the actual tool-chain and permissions your agent has, not a generic model.
Do you test our specific tools and permissions?
Yes — we test the actual tool-chain and scopes your agent holds, because that's what determines real impact.
Can prompt injection be fully prevented?
Not entirely — but impact can be contained. We focus on what an injection can actually reach and do.
Do you test our actual agent, not a generic one?
Yes — we test your real tools, permissions and guardrails, since those determine actual impact.
Do you recommend architectural controls?
Yes — egress limits, human-in-the-loop and least-privilege tool scoping to contain injection.
How long does a ai agent penetration testing take?
Most focused engagements run one to two weeks depending on scope; we agree the exact timeline during scoping.
Is a retest included?
Yes — after you remediate, we re-check the closed findings to confirm they’re fixed, at no extra cost.
How do you price it?
Per engagement, based on scope and depth — you get a fixed quote after a short scoping call. No cookie-cutter packages.
Why teams trust our ai agent penetration testing
Aligned to recognised standards
Testing follows OWASP, PTES, NIST SP 800-115 and MITRE ATT&CK, and reports support SOC 2, ISO 27001, PCI DSS, HIPAA, GDPR, NIS2 and DORA.
Every engagement includes
Reproducible PoCs, risk-ranked findings, concrete remediation, a named point of contact, a free retest, and a summary letter of attestation.
Confidential by default
Work is covered by an NDA, scoped with clear rules of engagement, and data is handled with care throughout — including residency requirements.
Sample report available on request — see our reporting format and depth before you commit. Ask for a sample →
Get a quote for AI Agent Penetration Testing
Tell us about the target — we’ll come back with scope and a fixed price. Manual, exploit-driven testing with reproducible proof and a free retest.