# ZioSec — Expanded site summary

> ZioSec builds security for an agentic world. We engineer advanced attacking agents, giving our team direct knowledge of how they reason, adapt, and exploit systems. Voidhawk provides adaptive defense for connected apps, APIs, and agents. The AI Red Teaming Platform supports agent inventory, continuous campaigns, policy, findings, and audit evidence.

Contact: info@ziosec.com | +1-720-807-2737 | 2000 Central Ave, #100, Boulder, CO 80301
Founders: Aaron Walls (CEO), Andrius Useckas (CTO)
Choose a product or engagement: https://ziosec.com/demo

## Voidhawk

Turn the attack around.

Voidhawk is adaptive defense for connected applications, APIs, and AI agents. Its customers include security, platform, and infrastructure teams. A customer does not need to operate AI agents: an attacker can use AI against ordinary web applications and APIs.

Voidhawk combines fast heuristics with AI reasoning for ambiguous cases. It considers application-specific behavior and reasons about an actor's objective across actions. ZioSec applies its offensive understanding to defensive responses that disrupt hostile agentic traffic within the customer's defended environment.

### Development status and design partnerships

Voidhawk is in active development and ZioSec is selecting design partners. A partnership starts with the customer's environment, traffic path, data handling requirements, and an agreed evaluation scope. ZioSec's offensive agents support authorized testing against agreed targets to help evaluate the defense.

Voidhawk product: https://ziosec.com/voidhawk.md
Defense solution: https://ziosec.com/use-cases/defend-against-agentic-attacks.md
Discuss a design partnership: https://ziosec.com/contact?intent=voidhawk

### Deployment and data handling

- **Self-hosted Kubernetes.** Run Voidhawk in the customer's Kubernetes cluster. Request data and per-endpoint calibration stay inside customer infrastructure. The deployment includes a controller, proxy, and GPU inference nodes. Updates are signed OCI artifacts pulled on the customer's schedule.
- **Hosted edge.** Route traffic through Voidhawk before the customer's origin. ZioSec processes request and response traffic on its infrastructure. No Voidhawk installation is required in the customer's cluster.

Both deployment choices use the same analyzers and verdicts. Deployment determines the traffic path and where request data is processed; a universal claim that no data leaves customer infrastructure does not describe the hosted edge option.

Self-hosted traffic attachment options include ext_proc for compatible gateways, request mirroring for observation, and TLS passthrough for selected hostnames. ext_proc sees requests and responses while the gateway retains routing. In TLS passthrough, Voidhawk terminates TLS and owns L7 for the selected hostnames.

Mirroring receives duplicate requests for observation and scoring only. It cannot refuse or block traffic and does not see responses. Response-dependent detections, such as login outcomes and reflected or leaked data in responses, are unavailable in mirror mode. ext_proc dry-run offers an evaluation with both request and response signals without enforcement.

Deployment details: https://ziosec.com/voidhawk/deployment.md

## AI Red Teaming Platform

The AI Red Teaming Platform lets teams operate security across an AI agent fleet. Teams manage inventory, continuous attack campaigns, per-agent policy, findings, remediation routing, executive risk posture, and audit evidence. Its API connects the testing engine and results to the team's existing workflows.

The platform generates bespoke, deep-chained attack trees against an agent's architecture, tools, memory, data access, and trust boundaries. Its autonomous adversaries test for prompt injection, tool misuse, agent-to-agent exploits, privilege escalation, data exfiltration, jailbreaks, system prompt extraction, and credential abuse.

Each finding includes severity, reproduction steps, attack classification, relevant framework mappings, and remediation guidance. Findings support developer remediation, fleet-level security posture, and governance evidence.

Testing is scoped to agreed agents, tools, and data classes. Destructive actions are simulated or approval-gated, with rate limits, a stop control, and a full audit log. Continuous validation can be repeated as models, prompts, tools, and permissions change.

Product overview: https://ziosec.com/ai-red-teaming.md

### Operate the platform and connect your workflows

- **Platform.** The operations console for agent inventory, attack campaigns, per-agent policy, findings, evidence, and executive risk posture. Security teams operate continuous validation across the fleet. https://ziosec.com/platform.md
- **API.** Submit an agent endpoint, run offensive testing, and receive structured findings and an evidence packet. Teams can invoke testing from development pipelines or embed it in security and vendor-risk workflows. This is the offensive testing API, distinct from Voidhawk's deployment and traffic processing. https://ziosec.com/api.md

Sample offensive testing deliverable: https://ziosec.com/sample-report.md

## Why ZioSec understands attackers

We understand advanced attacking agents because we build them.

ZioSec engineers agents that plan attacks, adapt to targets, and exploit vulnerabilities. Building those agents gives our team direct knowledge of how they reason, where they are vulnerable, and how their objectives can be disrupted. We apply that expertise to defense and use our own offensive agents to train and validate Voidhawk.

Voidhawk and the AI Red Teaming Platform each address a distinct customer need and can be used independently. The company’s defensive competence comes from engineering attacking agents. It does not depend on customers operating the two products together or automatically contributing their traffic to model training.

Our approach: https://ziosec.com/approach.md

## Solutions

### Defend against agentic attacks

Bring adaptive defense to connected apps, APIs, and AI agents. Explore a Voidhawk design partnership around the traffic and systems you operate.

https://ziosec.com/use-cases/defend-against-agentic-attacks.md

### Validate your agents

Break your agent before an attacker or a customer security review does. Findings come back with reproduction steps and remediation guidance.

https://ziosec.com/use-cases/validate-your-agents.md

### Continuous agent governance

Connect live attack results to your governance program, with evidence mapped to the frameworks your team reports against.

https://ziosec.com/use-cases/continuous-agent-governance.md

### Pentest agents as they are built

CI for agents. When an agent or agent-builder generates a new workflow, invoke the AI Red Teaming Platform API to validate it as part of your pipeline.

https://ziosec.com/use-cases/agentic-software-on-demand.md

### Build your agent inventory

Connect your agent inventory to continuous validation so discovered agents become testing targets and findings stay attached to the systems you own.

https://ziosec.com/use-cases/diy-agent-inventory.md

The agents-as-built use case describes invoking red-teaming in a development pipeline when a new or changed agent workflow exists. An expert-led scoped pentest is an optional service.

Solutions hub: https://ziosec.com/use-cases.md

## Audiences

- **Security, platform, and infrastructure teams defending traffic.** Evaluate Voidhawk for connected apps, APIs, and AI agents. Review deployment and traffic handling with the team that operates the defended systems. https://ziosec.com/use-cases/defend-against-agentic-attacks.md
- **Security and red teams validating agents.** Add agent-specific adversarial campaigns to an existing offensive security program. Findings support remediation and fleet-level posture. https://ziosec.com/enterprise-red-teams.md
- **Governance, risk, and compliance teams.** Use evidence from the AI Red Teaming Platform in risk and audit workflows. Framework mappings describe offensive findings; they are not a blanket certification of either product or the customer's compliance. https://ziosec.com/governance-risk-compliance-teams.md
- **Developers.** Test the agents they build, receive reproducible findings, and connect validation to CI and issue-tracking workflows. https://ziosec.com/developers.md

## Research, methodology, and evidence

The Agent Attack Taxonomy (AAT) is the classification language for agent attacks. A2OSF, the Agentic AI Offensive Security Framework, is the operational methodology for scoping, attacking, measuring, reporting, and continuously retesting agentic systems. AAT is the classification taxonomy contained within A2OSF; the taxonomy and the operational methodology have distinct roles.

AAT classifies attacks by layer, tactic, and threat scope. It carries references to public attack frameworks and aligns findings with governance risk vocabulary. AAT itself is not a certification standard.

- Methodology overview: https://ziosec.com/methodology.md
- Full Agent Attack Taxonomy: https://ziosec.com/agent-attack-taxonomy.md
- AI Red Teaming Platform evidence and framework mapping: https://ziosec.com/ai-compliance.md
- Standards explorer: https://ziosec.com/ai-compliance/explorer.md
- Cross-framework matrix: https://ziosec.com/ai-compliance/matrix.md
- EU AI Act: https://ziosec.com/ai-compliance/eu-ai-act.md
- NIST AI RMF: https://ziosec.com/ai-compliance/nist-ai-rmf.md
- ISO/IEC 42001: https://ziosec.com/ai-compliance/iso-42001.md
- AIUC-1: https://ziosec.com/ai-compliance/aiuc-1.md
- OWASP AISVS: https://ziosec.com/ai-compliance/owasp-aisvs.md
- Whitepaper: https://ziosec.com/whitepaper.md

## Optional expert-led services

- **AI Red Teaming services.** A fixed-scope, expert-led AI agent penetration test starting at $10,000. The fee is 100% credited toward an annual AI Red Teaming Platform subscription if the customer continues. https://ziosec.com/ai-agent-pentesting.md

ZioSec also provides consulting alongside its products:

- Secure AI adoption and rollout: admin console configuration, permissioning, guardrails, and rollout planning.
- AI transformation advisory: threat modeling, architecture and policy review, and incident readiness.
- Secure agent design: tool, identity, and egress design, boundary review, and pre-launch adversarial testing.
- Team enablement: workshops and practical guidance based on the Agentic AI Security 101 curriculum.

Services: https://ziosec.com/services.md
Training: https://ziosec.com/agentic-security-101.md

## Partnerships

ZioSec is selecting Voidhawk design partners. The company also invites discussions about embedding the AI Red Teaming Platform through its API and collaborating on security service engagements. Partnership categories describe ways to work together, rather than a list of confirmed third-party integrations.

Partners: https://ziosec.com/partners.md

## Company

ZioSec is based in Boulder, Colorado. The team combines offensive security research and production software engineering to build advanced attacking agents. That firsthand technical experience informs the company’s work on security of customer AI agents and defense of connected systems against attackers using AI.

- About and team: https://ziosec.com/about.md
- Careers: https://ziosec.com/careers.md
- Trust: https://ziosec.com/trust.md
- Contact: https://ziosec.com/contact.md
- Product and engagement chooser: https://ziosec.com/demo.md

## Frequently asked questions

### ZioSec and our approach

**What does ZioSec do?**

ZioSec builds security for a world of AI agents. Voidhawk defends connected applications, APIs, and AI agents against adaptive attackers. The AI Red Teaming Platform supports agent inventory, continuous attack campaigns, policy, findings, and audit evidence. Our team builds advanced attacking agents and applies that technical understanding to the security problems each product addresses.

**How does building attacking agents establish defensive expertise?**

We engineer agents that plan attacks, adapt to a target, and exploit vulnerabilities. Building those agents teaches us how they reason, where their weaknesses are, and how their objectives can be disrupted. We apply that expertise to Voidhawk, using our offensive agents to train and validate defenses and inform responses to malicious agentic traffic within the defended environment.

**Do I need to operate AI agents to use Voidhawk?**

No. Voidhawk is for teams defending connected applications and APIs as well as teams deploying AI agents. An attacker can use AI against an ordinary web application. Security, platform, and infrastructure teams can evaluate Voidhawk around the systems and traffic they already operate.

### Voidhawk

**Is Voidhawk available today?**

Voidhawk is in active development, and ZioSec is selecting design partners. We work with partners to define their environment, deployment approach, attack scenarios, and evaluation scope.

**What does Voidhawk look for?**

Voidhawk analyzes traffic to connected apps, APIs, and AI agents. It combines fast heuristics with AI reasoning for ambiguous cases, considers application-specific behavior, and evaluates an actor’s objective across actions. Its defensive responses aim to interrupt the attack within the customer’s defended environment.

**Where does Voidhawk run, and where is traffic processed?**

Voidhawk has two deployment choices. A self-hosted deployment runs in your Kubernetes cluster; request data and per-endpoint calibration remain in your infrastructure. A hosted edge deployment processes request and response traffic on ZioSec infrastructure before forwarding it to your origin. The deployment discussion establishes which model fits your requirements.

**Can I evaluate Voidhawk before enabling blocking?**

Yes. Request mirroring supports observation and scoring, but cannot block and does not see responses. That limits response-dependent detections, including login outcomes and data leakage in responses. An ext_proc dry-run evaluation can retain request and response signals without enabling enforcement.

### AI Red Teaming Platform

**What does the AI Red Teaming Platform include?**

The AI Red Teaming Platform lets teams operate security across an AI agent fleet. Teams inventory agents, run continuous campaigns with bespoke attack trees, set per-agent policy, route reproducible findings to owners, and track risk and audit evidence. Its autonomous adversaries test the agent’s architecture, tools, data access, and trust boundaries, while its API connects validation to existing workflows.

**Can our team operate continuous testing?**

Yes. Your team operates the AI Red Teaming Platform and controls campaign scope, schedules, policies, and findings. Validation runs continuously or on change as models, prompts, tools, and permissions evolve. The API brings those capabilities into your pipelines. Expert-led scoped pentests are also available through optional AI Red Teaming services.

**How are offensive tests controlled?**

Your team defines which agents, tools, and data classes are in scope through the platform’s campaign and policy controls. Destructive actions are simulated or approval-gated, with rate limits, a stop control, and an audit log. Those boundaries are established before attacks run.

**What evidence does a red-team test produce?**

Findings include severity, reproduction steps, attack classification, relevant framework mappings, and remediation guidance. Evidence supports engineering, security review, and governance workflows. Our methodology and compliance pages explain the classification and mapping approach; testing evidence does not by itself certify compliance.

**Is there an API?**

Yes. The AI Red Teaming Platform API accepts an agent endpoint and returns offensive testing results and an evidence packet. It supports teams embedding agent validation in CI, security products, and vendor-risk workflows. This is the offensive testing API described at /api.

### Getting started

**How do I start with the AI Red Teaming Platform?**

Book a platform demo to explore fleet inventory, attack campaigns, policy, findings, and reporting for your environment. Discuss API access if you want to automate validation in your own workflows. An optional expert-led pentest starts at $10,000, with the fee 100% credited toward an annual AI Red Teaming Platform subscription if you continue.

**How do I explore a Voidhawk design partnership?**

Contact the team about Voidhawk. Bring the apps, APIs, or agents you need to defend, your traffic path, and your data handling requirements. We will discuss fit, deployment, and an agreed evaluation using authorized offensive testing.

**Do you provide consulting as well as products?**

Yes. ZioSec offers secure AI adoption and rollout, AI transformation advisory, secure agent design, and team enablement. These services help teams make architecture, permissioning, and operational decisions as they adopt AI.

Full FAQ: https://ziosec.com/faq.md

## Editorial and policies

Editorial content records research, company updates, and product walkthroughs. Historical articles retain their original subject and timing.

- Blog: https://ziosec.com/blog.md
- News: https://ziosec.com/news.md
- Videos: https://ziosec.com/videos.md
- Privacy policy: https://ziosec.com/privacy-policy.md
- Terms of service: https://ziosec.com/terms-of-service.md
- Discovery index: https://ziosec.com/llms.txt
- Sitemap: https://ziosec.com/sitemap.xml