ConsultingWorkbench-backed AI security engagements — map, attack, defend, and prove your AI systems.
Scope a Review

AI SECURITY ENGINEERING WORKBENCH

The workbench for mapping, attacking, defending, and proving AI systems.

Map.Attack.Defend.Prove.

Four integrated instruments for AI security engineering — built to support red-team validation, blue-team hardening, and governance evidence from the same fixture-driven workflow.

Red Team ValidationBlue Team HardeningGovernance EvidenceControl-Mapped
SecEng Workbench

Delivery system

SecEng Workbench is the tool-backed delivery system we use during AI security engagements.

It helps us map AI systems, run adversarial scenarios, harden release paths, and produce evidence buyers, auditors, and security teams can actually use — deployed during assessments, hardening sprints, red-team reviews, and evidence-pack engagements.

Scope a Review

Map the AI system

Diagnostic / scoping layer: discover every surface, agent, workflow, tool, retrieval path, data exposure, and trust boundary.

Attack the AI system

Red-team layer: run adversarial tests against prompts, agents, tools, retrieval, authorization, memory, and model behavior.

Defend the AI system

Blue-team layer: turn findings into controls, guardrails, detections, approval gates, telemetry, and release criteria.

Prove the AI system

Governance layer: generate evidence packs, control mappings, framework crosswalks, buyer answers, and audit-ready exports.

Live demos — fixture-driven

See each instrument in action.

Every instrument ships with a fixture-driven live demo. Walk through a real run — no setup required.

Open Adversarial Range demo
SecEng Threat Canvas live demo

Where are the trust boundaries?

SecEng Threat Canvas

Service modes

Red-team depth. Blue-team hardening. Governance evidence.

The Workbench keeps the service buckets connected. Red-team work produces reproducible findings. Blue-team work turns them into controls and telemetry. Governance work packages the proof.

Red Team · Map + Attack

We find real attack paths.

  • Map AI surfaces before adversaries fingerprint them
  • Reproduce prompt injection, jailbreak, RAG, and agent abuse paths as product-security findings
  • Build agent abuse chains from real tool compositions
  • Poison RAG corpus and validate detection coverage
  • Generate regression tests from every confirmed exploit

Blue Team · Defend

We turn findings into controls.

  • Design permission boundaries, approval gates, and rollback paths
  • Build logging, telemetry, and detection requirements for prompts, retrieval, and tool calls
  • Convert exploits into evals, regression tests, and release gates
  • Define control owners and operational runbooks
  • Track remediation from finding to shipped fix

Governance · Prove

We package evidence buyers and auditors can use.

  • Generate evidence bundles for product security, AppSec, GRC, legal, and procurement
  • Map findings to OWASP LLM, NIST AI RMF, MITRE ATLAS, ISO 42001, SOC 2, and EU AI Act language
  • Create control ownership maps and evidence lifecycle notes
  • Produce buyer-ready trust language and questionnaire support
  • Deliver board, legal, and governance exports

Standards alignment

Every finding maps to a control framework.

Framework

OWASP LLM Top 10

Application-level LLM risks: prompt injection, insecure output handling, data disclosure, and supply chain.

Framework

NIST AI RMF / GenAI Profile

Risk management language for AI governance: govern, map, measure, manage. GenAI profile adds model-specific controls.

Framework

MITRE ATLAS

Adversarial tactics, techniques, and procedures for AI systems. Maps red-team findings to known adversary behavior.

Framework

ISO 42001

AI management system standard. Evidence packages from every instrument map to ISO 42001 controls for audit readiness.

AI SECURITY ENGINEERING WORKBENCH

Start with a scoped Workbench review.

We'll map your AI surfaces, identify the highest-priority red-team, blue-team, and governance gaps, and show which Workbench instruments apply before you commit to a larger engagement.