Vami Solutions · IT security & GRC

AI solutions that automate IT security and GRC.

VamiSec builds AI solutions that take on security and compliance work: agents analyze, test, and document; your team controls the approvals. EU regulation such as NIS2, DORA, the Cyber Resilience Act, and the EU AI Act is at the core, so that meeting requirements becomes efficient and manageable. The solutions can be used on their own and are connected through VamiGRC — an ecosystem for security and compliance.

  • SaaS on T Cloud Public
  • Exclusively German data centers
  • VamiSec: ISO 27001 certified
  • No AI training on customer data

IT security and compliance without AI is a vulnerability.

Valeri MilkeFounder & CEO, VamiSec
About VamiSec

Technical depth meets regulatory clarity.

VamiSec GmbH, based in Bonn, is a founder-led consulting and software company for IT security and GRC. Since April 2026, it has formed the Vami Group together with its sister company softScheck GmbH, based in Sankt Augustin. Its roots go back to 2009, to SoftSCheck, a research project on threat modeling and fuzzing at Bonn-Rhein-Sieg University of Applied Sciences, funded by the German Federal Ministry of Education and Research (BMBF).

Our AI solutions grow out of our work for clients in regulated industries — banks and insurers, critical infrastructure, pharma and chemicals, hospitals, automotive, manufacturing, software vendors, and the public sector. They automate recurring security and compliance tasks and deliver auditable evidence; the decisions stay with your team.

More about VamiSec →
Since 2009
Roots in the SoftSCheck research project at Bonn-Rhein-Sieg University of Applied Sciences
Vami Group
VamiSec and softScheck under common leadership since April 2026
ISO 27001
Certified ISMS of VamiSec GmbH, valid until September 2028
T Cloud Public
SaaS solutions hosted by Deutsche Telekom, exclusively in German data centers
  • ISO/IEC 27001 certified
  • Software Made in Germany 2026 · for VamiGRC
  • Member of the Wiz Partner Alliance
  • Member of Bitkom
  • Member of BITMi
  • EcoVadis Committed · October 2026
Why now

Regulation, tool silos, and AI demand a new approach.

NIS2, DORA, the Cyber Resilience Act, and the EU AI Act make security and compliance an ongoing duty that must be backed by evidence. At the same time, attack surfaces, supply chains, and the use of AI are growing faster than the teams expected to manage it all.

01

Providing evidence becomes an ongoing task

In Germany, NIS2 has applied since December 2025 (to around 29,500 entities, according to BSI estimates), DORA since January 2025, and the reporting obligations of the Cyber Resilience Act since September 2026. What is needed is continuous, auditable evidence instead of annual documentation.

02

Security work fragments into silos

Scanner results, pentest reports, threat models, and risk registers are created in separate tools. Findings rarely turn into risk decisions, and the same evidence is collected multiple times.

03

AI is both a risk and a lever

The transparency obligations of the EU AI Act have applied since August 2026, and employees are entering sensitive data into AI chatbots. At the same time, AI is the realistic way to handle the growing workload — provided its work is traceable and humans control the approvals.

Solution map

One ecosystem, four focus areas.

Each Vami solution covers a clearly defined focus area and can be used on its own. Select a solution to jump straight to its details.

Govern & prove

Governance, risk, and compliance for organizations and products in one graph.

Build securely

Model threats, test code and running applications — with evidence per release.

Attack & analyze

Authorized pentests with evidence-backed findings and AI-assisted analysis of binary code and malware.

Protect data

Protect sensitive data in AI prompts — locally in the browser, before the prompt is sent.

Core solutions

Five core solutions — from the GRC graph to pentesting.

The core solutions cover the central tasks of modern IT security and compliance. You can adopt them individually and combine them step by step.

VamiGRC

Agentic Integrated Management System

GRC for organizations and products · NIS2 · CRA · DORA · AI ActLive · Production

CISOs, data protection officers, AI officers, and product security teams often work from separate lists: the same processes are described multiple times, the same evidence is collected multiple times — and risk decisions stall.

VamiGRC is an agentic integrated management system for manufacturers and operators: NIS2 for your organization and the CRA for your products in one system. ISMS, PIMS, AIMS, CSMS, and BCMS share the same assets, suppliers, risks, and evidence on one GRC graph; risks and measures are assessed in euros. AI agents handle the routine work according to your approval rules.

Frameworks (examples)
  • NIS2
  • CRA
  • DORA
  • EU AI Act
  • GDPR
  • ISO 27001
  • ISO 42001
  • Five management systems in one IMS: ISMS, PIMS, AIMS, CSMS, and BCMS on the same GRC graph with a shared risk scale
  • VamiAI answers questions based on your IMS with source references, including in Microsoft Teams; autonomy levels L0–L3 determine what requires approval
  • Product Security Lifecycle for the CRA: release gates, threat modeling and TARA, plus an SBOM per release
  • Cyber risk in euros: assess risks and measures in monetary terms and calculate the return on security and compliance investment
  • Framework Composer and OSCAL: one control set for multiple standards, your own frameworks via import, through to the Statement of Applicability
  • Keep track of reporting deadlines under NIS2, GDPR, DORA, the CRA, and the AI Act: VamiAI drafts notifications that your team reviews and submits
  • Supplier Intelligence and questionnaires: assess suppliers using OSINT, trust centers, and questionnaires; answer customer questionnaires with evidence for every response
Who it's for
Manufacturers of connected products · Companies subject to NIS2 · Financial entities under DORA · Organizations using AI · CISOs, data protection officers, AI officers, and product security teams
What's different
Corporate and product compliance in one graph: a control is implemented once and used for multiple frameworks. Launch automated pentests in VamiRedteam directly from VamiGRC.
Deployment & AI
SaaS on T Cloud Public, exclusively in German data centers · Enterprise also on-prem or air-gapped on your own Kubernetes cluster · LLM of your choice for chat, assistant, and agents: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own; in the SaaS, embeddings and certain specialized functions run via OpenAI · no AI training on customer data

VamiAppSec

Secure SDLC & Product Security Compliance

DevSecOps · SBOM & supply chain · CRA reporting obligations · OWASPLive · Production

Scanners deliver lists of findings in different formats, dynamic tests often come only after the release, and it is hard to prove which components ship in which release.

VamiAppSec is VamiSec's LLM-assisted platform for the secure SDLC and product security compliance: seven scan types, including DAST with the fully integrated VamiDAST, run in the CI/CD pipeline you already use. All findings are mapped to OWASP and tracked in DefectDojo or your ticketing system, every shipped SBOM is monitored for actively exploited vulnerabilities, and every release produces evidence for regulations and standards such as the CRA, MDR, IEC 62443, or ISO/SAE 21434.

Frameworks (examples)
  • CRA
  • MDR
  • RED
  • IEC 62443
  • UNECE R155
  • ISO/SAE 21434
  • Seven scan types in one pipeline: SAST, SCA, SBOM, secrets, IaC, containers, and DAST with VamiDAST
  • SBOM per release (CycloneDX, SPDX), continuously monitored for actively exploited vulnerabilities, using sources such as CISA KEV, and prioritized with EPSS
  • CRA reporting, prepared: early warning, notification, and final report as pre-filled drafts for submission — no automatic submission
  • Quality gates native to GitLab, GitHub, and Azure DevOps: blocking on critical findings, SARIF in the IDE and in pull requests
  • DefectDojo as the central findings system — tracking, not scanning — with sync to Jira, Azure DevOps Boards, or ServiceNow
  • OWASP mapping of findings, for example to ASVS, MASVS, WSTG, and AISVS; evidence per release with SBOM, VEX/VDR, SARIF, and gate decisions
Who it's for
Manufacturers of software, connected products, and medical devices · Automotive and industrial suppliers · PSIRTs · DevSecOps and AppSec teams on GitLab, GitHub, or Azure DevOps
What's different
Compliance evidence as a by-product of the pipeline: the LLM you choose enriches findings and drafts the VEX status for dependencies but does not act autonomously. VamiAppSec supplies the evidence; your auditor or notified body decides.
Deployment & AI
SaaS on T Cloud Public, exclusively in German data centers, or the full stack on-prem on your Kubernetes cluster, even air-gapped · LLM of your choice: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own · no AI training on customer data
Integrated module

VamiDAST

AI-Assisted DAST

Dynamic application security testing · standalone or in VamiAppSecLive · Production

VamiDAST tests running web applications and APIs from the outside, the way an attacker sees them, and backs every finding with the payload and response evidence. A deterministic engine controls every scan; within the scan flow, an LLM advises only at exactly three bounded points.

  • More than 30 vulnerability classes across the OWASP Top 10 and the OWASP API Security Top 10; more extensive checks can be enabled
  • Testing behind the login with forms, JWT, cookies, and API keys, including a second identity for BOLA/IDOR
  • Passive, Safe, and Aggressive modes; production systems only in Passive or Safe mode and only with authorization
  • Standalone with dashboard, REST API, and reports (PDF, SARIF, CSV) or fully integrated into VamiAppSec

VamiThreat

AI-Assisted Threat Modeling

Threat modeling · STRIDE · MAESTRO for agentic AI · MITRE ATT&CK and ATLASLive · Production

Threat modeling rarely fails for lack of will — it fails because of the effort: workshops take time, diagrams go out of date, and there is often no structured approach for agentic AI systems.

VamiThreat is VamiSec's AI-assisted threat modeling platform: architecture descriptions, documents, and diagrams become an editable data flow diagram with trust boundaries, on which VamiThreat models threats using STRIDE and, for agentic AI systems, MAESTRO. For each threat, VamiThreat delivers the attack path, risk, and mitigation — the AI enriches and suggests.

  • Input conversationally, as a document (Word, text, PDF), or as a diagram image — your team reviews parsed diagrams before they are used
  • Editable data flow diagram with trust boundaries as a reviewable basis for the model
  • STRIDE for IT and application components, MAESTRO from the Cloud Security Alliance for agentic AI across seven layers
  • Mapping of threats to MITRE ATT&CK and ATLAS per component
  • Attack path, risk, and mitigation for each threat — prioritized in the system context, with code and configuration examples
  • PDF reports for executive management with prioritized risks and summarized attack paths
Who it's for
Engineering and security teams before release · Manufacturers that need to assess their product risks in a documented way · Teams building agentic AI systems · Architects working on cloud projects
What's different
Model classic applications and agentic AI systems in the same tool — traceable from architecture to mitigation. The AI does not act autonomously.
Deployment & AI
SaaS on T Cloud Public, exclusively in German data centers, or on-prem on your Kubernetes cluster on request · LLM of your choice: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own · no AI training on customer data

VamiRedteam

Multi-Agent Penetration Testing

Offensive security · Pentests for web applications, APIs, hosts, and networks · AI applicationsLive · Production

Pentests shouldn't depend on heroics: attack surfaces change with every release, and AI applications need tests of their own.

VamiRedteam is VamiSec's agentic penetration testing platform: three specialized AI agents — Recon, Smart Crawler, and Pentester — test web applications, APIs, hosts, and networks exclusively within the authorized scope. Every action is checked before execution and logged, newly discovered targets are tested only after your approval, and every finding includes evidence, reproduction steps, and proof.

Frameworks (examples)
  • DORA
  • NIS2
  • CRA
  • Three specialized AI agents — Recon, Smart Crawler, and Pentester — work in parallel; every action is visible in real time
  • Scope per engagement: every agent action is checked against the authorized targets before execution; anything outside them is rejected
  • Optional supervised mode with approval for each command; newly discovered targets are tested only after operator approval
  • Every finding with evidence, reproduction steps, and proof; every step logged and audit-ready
  • Test AI applications following the OWASP AI Testing Guide for risks such as prompt injection and system prompt leakage
  • Connected to VamiGRC: launch automated pentests from an engagement in VamiGRC and import findings into the vulnerability inventory with one click
Who it's for
Financial entities and critical infrastructure operators with testing obligations · Manufacturers under the CRA · Organizations with AI applications · Security teams that want to test more often
What's different
Honest autonomy: the agents report their actual status and check back with you instead of fabricating success — and every action remains traceable within the authorized scope.
Deployment & AI
Hosted on T Cloud Public, exclusively in German data centers · isolated sandbox and dedicated network per organization · LLM configurable, EU-hosted or local on request (AI processing depends on the chosen model) · no AI training on customer data

VamiGuard

Data Protection for AI Prompts in the Browser

Data loss prevention for GenAI · Browser extension for Chrome and EdgeLive · Chrome & Edge

Anyone using AI chatbots can quickly paste customer data, credentials, or internal names into prompts — often without realizing it.

VamiGuard is a free browser extension for Chrome and Microsoft Edge. In prompts to ChatGPT, Claude, Microsoft Copilot, Gemini, Grok, and DeepSeek, it locally detects personal data such as email addresses and phone and credit card numbers, as well as API keys, tokens, and labeled passwords, and, after your confirmation, replaces them with placeholders before the prompt is sent. Responses containing placeholders can be displayed locally with the original values in the same tab.

Frameworks (examples)
  • GDPR
  • Local checks as you type in the web versions of ChatGPT, Claude, Microsoft Copilot, Gemini, Grok, and DeepSeek
  • Pattern-based detection, without a guarantee of completeness, of email addresses, phone and credit card numbers, API keys and tokens, for example from AWS, GitHub, or OpenAI, as well as labeled passwords
  • Warns on matches and replaces them with stable placeholders such as <EMAIL_1> only after your confirmation
  • Add your own words and patterns, such as project code names; turn off individual data types
  • No AI model, backend, account, or telemetry — the extension sends no data to VamiSec or third parties
Who it's for
Companies whose teams use AI chatbots · Consultancies with confidentiality obligations · Development teams sharing code snippets that contain secrets · Data protection and compliance teams
What's different
Protection at the source: the check runs locally in the browser as you type — no server, no account, free of charge.
Deployment & AI
Runs entirely locally in the browser · no backend and no language model · sends no data to VamiSec or third parties

Complementary building block

A specialized solution that covers a specific task.

VamiReverse

AI-Assisted Reverse Engineering & Malware Analysis

VamiReverse is VamiSec's AI-assisted multi-agent platform for reverse engineering and malware analysis — from binary to attack path in a single session. Specialized agents build on self-operated tools such as Ghidra, ILSpy, and jadx, classify behavior, and deliver detection rules and an analysis report; the AI suggests, your analysts review.

  • Android apps (APK) as well as Windows and Linux programs (PE/ELF, including .NET)
  • AI-annotated pseudocode, behavioral analysis, and vulnerability hypotheses
  • YARA, Sigma, and Suricata rules, IOCs, and mapping to MITRE ATT&CK
  • Dynamic analysis of Android apps with Frida in a sandbox and emulator

SaaS on T Cloud Public, exclusively in German data centers, or on-prem on request · LLM of your choice: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own · no AI training on customer data

Ecosystem

Standalone solutions, connected through VamiGRC.

Each Vami solution can be used on its own and covers one stage of security and compliance. Their results flow into VamiGRC — only VamiGuard checks locally in the browser and sends no data. VamiDAST is also integrated into VamiAppSec.

  1. 01

    Model

    Derive threats from the architecture — STRIDE for applications, MAESTRO for agentic AI.

  2. 02

    Build & test

    Test code, dependencies, and the running application in the pipeline — with evidence per release.

  3. 03

    Attack & analyze

    Prove attack paths within the authorized scope and analyze binary code and malware.

  4. 04

    Protect

    Detect sensitive data in AI prompts and replace it with placeholders after your confirmation.

VamiGRC — governance layer for risks, controls, and evidence

Risks, controls, suppliers, and evidence in one GRC graph — where the results of the Vami solutions come together; you connect other systems via connectors, the Public API, and MCP.

VamiGRC ↔ VamiRedteam

Launch automated pentests from an engagement in VamiGRC. Import findings, scope, and the attack graph into the vulnerability inventory and attack surface with one click. With another click, VamiGRC drafts risks from them for you to review and finalize.

VamiDAST in VamiAppSec

Dynamic tests run as a fixed pipeline stage: runtime findings land in the same DefectDojo backlog as SAST, SCA, and SBOM, behind the same quality gates.

Open to your tools

VamiGRC uses connectors to import data from Azure, AWS, Google Cloud, Entra ID, Intune, Defender, GitHub, GitLab, and KnowBe4, syncs tasks with Jira, ServiceNow, Azure DevOps, and GitHub Issues, and connects AI assistants via MCP.

EU regulation at the core

Which solution supports which framework.

The Vami solutions translate requirements into work and evidence. The overview shows which solutions help with the key frameworks.

NIS2

Organize risk management, supply chains, reporting deadlines, effectiveness reviews, and training in a way you can prove.

DORA

Manage ICT risks, third parties, reporting deadlines, and security testing — and back them with evidence.

Cyber Resilience Act

SBOM, vulnerability handling, security testing, threat analysis, and draft notifications.

EU AI Act

AI management system with AI inventory, risk classes, impact assessments, and human oversight.

GDPR

Data protection management system, reporting deadlines, and protection of personal data in AI prompts.

Product regulation and industry standards

IEC 62443, ISO/SAE 21434, UNECE R155, or MDR: TARA, a secure development process, and verification evidence.

The solutions deliver results and evidence; your auditors, supervisory authorities, or notified bodies decide on conformity.

Hosted in Germany · auditable

Operated in Germany. AI on your terms.

The hosted Vami solutions run on Deutsche Telekom's T Cloud Public, exclusively in German data centers in Magdeburg and Biere. For VamiGRC, VamiAppSec, VamiThreat, VamiDAST, and VamiReverse, you choose the language model: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own LLM. With the local Qwen3.8, AI processing stays in Germany — for VamiGRC in the SaaS, except for embeddings and certain specialized functions that run via OpenAI. For VamiRedteam, the LLM is configurable, EU-hosted or local on request (AI processing depends on the chosen model). VamiGuard works entirely locally in the browser.

T Cloud Public

Deutsche Telekom · exclusively in German data centers · BSI C5 attestation for the platform

LLM of your choice

For VamiGRC, VamiAppSec, VamiThreat, VamiDAST, and VamiReverse: local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own LLM

On-prem

VamiGRC (Enterprise), VamiAppSec, and VamiDAST on your own Kubernetes cluster, even air-gapped; VamiThreat and VamiReverse on-prem on request

No AI training on customer data

We do not train or fine-tune AI models with your data; we connect external AI models only under contractual terms that exclude training use

ISO/IEC 27001:2022

Certified ISMS of VamiSec GmbH · Proks Certification · valid until September 2028

ISO/IEC 42001

AI management system of VamiSec GmbH, built in line with ISO/IEC 42001

Frequently asked questions.

No. Each solution can be used on its own. Start where the pressure is greatest: VamiGRC for NIS2, DORA, the CRA, or the EU AI Act; VamiAppSec for product security and SBOM; VamiRedteam for pentests; VamiGuard when teams use AI chatbots. You can add further solutions later.
VamiGRC and VamiRedteam are agentic: agents carry out tasks, and you control the approvals — in VamiGRC through autonomy levels, in VamiRedteam through the authorized scope and, if desired, approval per command. VamiReverse uses specialized agents whose results your analysts review. VamiAppSec and VamiThreat are LLM-assisted: the model enriches and suggests but does not act autonomously. In VamiDAST, a deterministic engine controls every scan; an LLM advises at exactly three limited points in the scan flow. VamiGuard works without a language model.
The hosted Vami solutions run on Deutsche Telekom's T Cloud Public, exclusively in German data centers in Magdeburg and Biere; the platform holds a BSI C5 attestation. If you prefer, you can run VamiGRC (Enterprise), VamiAppSec, and VamiDAST on-prem on your own Kubernetes cluster, and VamiThreat and VamiReverse on request. VamiGuard runs entirely locally in the browser.
VamiGRC, VamiAppSec, VamiThreat, VamiDAST, and VamiReverse are LLM-agnostic: you can choose the local Qwen3.8 in VamiSec's data center in Sankt Augustin, Anthropic Claude, OpenAI, or your own model; in the VamiGRC SaaS, embeddings and certain specialized functions run via OpenAI. For VamiRedteam, the LLM is configurable — EU-hosted or local on request. VamiGuard works without a language model. We do not use customer data as training data: we do not train or fine-tune AI models with it, and we connect external AI models only under contractual terms that exclude training use.
VamiGRC is the governance layer for risks, controls, and evidence. All Vami solutions are connected to VamiGRC: VamiThreat, VamiAppSec, VamiDAST, VamiRedteam, and VamiReverse deliver their results to VamiGRC, while VamiGuard checks locally in the browser and sends no data. VamiDAST is also integrated into VamiAppSec. You can connect other systems via connectors, the Public API, and VamiGRC's MCP server. The hosted solutions each run on Deutsche Telekom's T Cloud Public, exclusively in German data centers; we do not use customer data as training data.
Book a 30-minute initial consultation. We discuss your starting point and show you the right solution in a demo. You can use VamiGRC free of charge for one month in your own tenant; for VamiRedteam, a scoped pilot on your systems can follow the demo.
Next step

One solution, one ecosystem — your starting point.

In 30 minutes, we work out where you stand and which Vami solution offers the most leverage — whether it's regulatory pressure, a pentest obligation, or AI use in your organization.

  1. 01
    Initial consultation30 minutes with Valeri Milke
  2. 02
    Demowith a trial month or pilot if desired, depending on the solution
  3. 03
    Step-by-step rolloutsolution by solution