---
title: AI Security for Developers
description: AI security for developers building agents. Catch agent vulnerabilities before you ship, get findings as tickets with reproduction steps, no security PhD required.
url: https://ziosec.com/developers
---

# AI Security for Developers Who Build Agents

You shipped an agent with tools, memory, and real data access. That is a new attack surface, and traditional scanners do not see it. ZioSec puts an autonomous adversary against your agent and hands you the holes as fixable tickets, with reproduction steps you can paste into a terminal. No security PhD required.

[Book a Demo](/demo) | [See a Sample Report](/sample-report)

## Your agent is code, plus a new class of bug you have never had to think about

Prompt injection, tool misuse, data exfiltration through agent memory, privilege escalation across a tool chain. None of it shows up in your unit tests, your SAST run, or a standard pentest. ZioSec is the offensive layer built for the way you actually build: agents made of custom code, Claude Code, and anything on the MCP or A2A protocols. We find the agent-specific failures while they are still cheap to fix, and we explain them in engineering terms, not audit jargon.

## AI attacks AI, tuned to the agent you actually wrote

This is the core of what we do and the part nobody can copy. ZioSec autonomously generates bespoke, deep-chained attack trees unique to your agent's architecture, its tools, and its data access, then executes them in real time. It is not a static list of jailbreak prompts run on a loop. The attacker reasons about your specific system prompt, the tools you exposed, and the data those tools can reach, then chains steps the way a determined human adversary would, except faster and against every code path. When you change a prompt or wire in a new tool, it re-derives the attack. You get an adversary that evolves with your codebase instead of a checklist that goes stale the day after you merge.

## Send your agent to the API and get results immediately

You do not have to adopt a platform or log into a dashboard to get value on day one. Point the ZioSec API at your agent's endpoint, set what is in scope, and a campaign runs against it right away. Results come back as structured findings you can read, reproduce, and route into your issue tracker, the same shape whether you call it once from your laptop or wire it into CI. No console to learn and no rollout to schedule. Just send the agent and get the holes back. Full details on the [API](/api).

## Vulnerabilities arrive as tickets, not as a PDF you have to decode

Every finding lands the way a good bug report should. A clear title, the severity, the exact prompts and tool calls that triggered it, and reproduction steps you can run yourself to confirm the failure in minutes. Each one carries concrete remediation guidance written for engineers: what to constrain, what to validate, where to add an approval gate. Route findings straight into your issue tracker so they sit in the same backlog as the rest of your work. You fix an agent vulnerability the same way you fix any other bug: read it, reproduce it, patch it, close it.

## It fits the pipeline you already have

Run validation before you ship, then keep it running as your agent changes. Connect through the API and trigger a campaign from CI so a risky change gets caught in review instead of in production. Findings flow into Jira, GitHub Issues, or whatever you already use. There is no new console your team has to live in and no separate security process to babysit. Point ZioSec at the agent, set what is in scope, and let the adversary work while you keep building.

## You do not need to become a red teamer to ship a secure agent

ZioSec does the offensive work so you do not have to learn attack tradecraft to find your own bugs. The hard part, generating and chaining realistic attacks against your specific agent, is automated. Your job is the part you are already good at: reading a clear reproduction, understanding the root cause, and writing the fix. The findings teach as they go, so over time your team writes safer agents by default without anyone earning a security certification first.

## Every finding maps to the standards your buyers and auditors ask about

When a finding matters beyond your team, it is already framed for that conversation. Each one is mapped at the control level to OWASP AISVS, MITRE ATLAS, ISO 42001, NIST AI RMF, the EU AI Act, and AIUC-1. That mapping is produced by our methodology (A2OSF), the high-resolution taxonomy we classify each attack result in before exporting it to the language of the six public standards. So when your security team, an enterprise customer, or an auditor asks how your agent was tested, you hand them evidence instead of a shrug. See our [methodology (A2OSF)](/methodology).

## Live attacks, run under your control

ZioSec runs real attacks against your agents, so it is built to stay inside the lines you draw. You decide the blast radius before anything runs.

- **You set the blast radius.** Before a campaign runs, you scope exactly which agents, which tools, and which data classes are in bounds. Nothing outside that scope gets touched.
- **Destructive actions never run blind.** Anything destructive is simulated or approval-gated, never executed without a check. Rate limits keep load sane and a one-click stop halts everything instantly.
- **Audit-ready evidence by default.** Every run produces a packet: attacks attempted, which succeeded, severity, reproduction steps, control-level framework mappings, and timestamps, exportable for GRC and trust workflows.

## Frequently Asked Questions

**Do I need to know anything about security to use this?**
No. ZioSec generates and runs the attacks for you. What you get back reads like any other bug report: a clear description, severity, reproduction steps, and remediation guidance written for engineers. If you can read a stack trace and write a fix, you can close a ZioSec finding. The point of the product is that you do not have to become a red teamer to secure your own agent.

**What kinds of agents does ZioSec test?**
Custom agents you built yourself, Claude Code, and any agent built on the MCP or A2A protocols. If your agent has tools, memory, and data access, ZioSec can model it and attack it. The attack trees are derived from your specific architecture, so coverage adapts to how you wired the agent rather than assuming a fixed shape.

**How is this different from a static scanner or a normal pentest?**
Scanners and standard pentests look for SQL injection, XSS, and network flaws. They do not understand prompt injection, tool misuse, agent-to-agent exploits, data exfiltration through memory, or privilege escalation across a tool chain. ZioSec is built only for the agent attack surface, and instead of a fixed test list it uses AI to attack AI: autonomous, deep-chained attack trees generated fresh for your agent and re-derived whenever you change it.

**How do findings get into my workflow?**
Through the API and your issue tracker. You can trigger a campaign from CI so risky changes get caught in review, and findings flow into Jira, GitHub Issues, or your existing tooling as actionable tickets. There is no separate console your team has to adopt. For the end-to-end action of validating an agent, see [Validate Your Own Agents](/use-cases/validate-your-agents).

**Is it safe to run real attacks against my agent?**
Yes, because you control the boundaries. You scope which agents, tools, and data classes are in bounds before anything runs. Destructive actions are simulated or approval-gated and never executed blind, rate limits keep things controlled, and a one-click stop halts everything. Every run is fully logged in an audit trail.

**What is the smallest way to start?**
A scoped pentest engagement starting at $10,000 is the low-commitment on-ramp. ZioSec security engineers run a focused validation against your agent and deliver framework-mapped findings. If you move to the continuous platform, 100% of that fee credits toward an annual subscription. It is the easiest way to see real findings against your own agent before committing to ongoing validation.

## Related

- [Validate Your Own Agents](/use-cases/validate-your-agents)
- [Agentic Software on Demand](/use-cases/agentic-software-on-demand)
- [How It Works: Our Methodology (A2OSF)](/methodology)

## Find the holes before your users do

Put an autonomous adversary against your agent and get back fixable tickets, not a security lecture. Book a demo or see a sample report to watch how a finding reads before it lands in your backlog.

[Book a Demo](/demo) | [See a Sample Report](/sample-report)

## Contact

- Email: info@ziosec.com
- Phone: +1-720-807-2737
- Boulder, CO