Services / Blue Team

Defend AI products with evidence your business can use.

Defensive AI security for products that need inventory, threat modeling, guardrails, logging, evaluation, and evidence-backed remediation before enterprise risk becomes customer pressure.

Start with a Discovery Call Benchmark Your Program Explore SecEng Trace

Product SecurityAI InventoryRAG AuthorizationAgent HardeningSecure SDLCLogging & TelemetryDetection EngineeringGovernance Evidence

Inputs & context

AI Features & Copilots

Inventory features, copilots, and AI touchpoints.

Agents & Workflows

Map actions, tool authority, and approvals.

RAG & Knowledge

Validate retrieval, tenancy, and provenance.

APIs & Integrations

Trace connectors, webhooks, APIs, and dependencies.

Cloud & Infrastructure

Review runtime, secrets, cloud services, and exposure.

+ Identity & Access

Defensive

Control Plane

AI product
hardening layer

InventoryControlsTelemetry

Outcomes & value

Backlog

Prioritized remediation

Controls

Designed & mapped

Telemetry

Logs & signals ready

Evidence

Audit-ready artifacts

Architecture Findings

Roles & trust boundaries

Risk Narrative

Executive summary

Surfaces Services Flow Outputs System Next Step

Defensive surfaces

AI products need controls across architecture, data, agents, logs, and operations.

Defensive AI security is not one guardrail or one policy. It is the operating layer around AI-enabled products: what exists, what is connected, how it behaves, what gets logged, what gets detected, and what evidence proves the controls are working.

Defensive

Inventory & Architecture

AI features, models, vendors, APIs, data flows, and trust boundaries.

Defensive

RAG & Data Authorization

Tenant boundaries, retrieval permissions, context leakage, and provenance.

Defensive

Agentic Workflows

Tool permissions, approval gates, delegated actions, and blast radius.

Defensive

Product Security Controls

AuthN/AuthZ, tenancy, APIs, admin surfaces, integration checks, and secrets.

Defensive

Logging & Detection

Prompt events, tool calls, retrieval events, alerts, and SOC handoff.

Defensive

Governance Evidence

Control maps, customer trust language, audit artifacts, and remediation proof.

Service formats

Defensive work for AI-native and SaaS teams.

The page is organized like the mockup: flagship work up top, then the broader blue-team service line beneath it.

Flagship

Blue TeamAvailable

assessment

AI Product Security Assessment

Assess LLM-powered product features, RAG systems, copilots, internal AI tools, model integrations, data flows, logging, evaluation, and customer-facing AI surfaces before they become enterprise risk. The output is a prioritized security backlog, architecture findings, control recommendations, and evidence product and engineering teams can act on.

Outcome

4 deliverables

Best for

CISO, Head of Product Security, VP Engineering, AI Product Lead

•AI system inventory and data-flow review
•RAG authorization and prompt injection exposure review
•Model/vendor, logging, and evidence gap review

Duration: 2-4 weeksScoped in discovery call

View service Request an AI security review See people fit

Flagship

Blue TeamAvailable

assessment

Agentic Workflow Security & Hardening

Secure AI systems that can take actions: call tools, send messages, query data, update records, trigger workflows, browse, code, or operate across business systems. The focus is permission design, approval boundaries, blast-radius reduction, logging, rollback, and abuse resistance.

Outcome

4 deliverables

Best for

AI Platform Lead, Product Security, Security Architect, Automation Lead

•Tool permission and action boundary review
•Approval, escalation, and least-privilege design
•Workflow abuse cases and audit logging recommendations

Duration: 3-6 weeksScoped in discovery call

View service Harden agentic workflows See people fit View proof

Flagship

Blue TeamAvailable

assessment

SaaS Product Security Review

A senior review of B2B SaaS architecture, auth, APIs, tenancy, integrations, admin surfaces, and abuse paths. The review maps authentication, authorization, tenancy, APIs, admin surfaces, integrations, data flows, cloud architecture, secrets, logging, and operational abuse paths into an executive risk narrative and engineering backlog.

Outcome

4 deliverables

Best for

CTO, VP Engineering, Product Security Lead, Security Architect

•Architecture, data-flow, and trust-boundary review
•Authn/authz, tenancy, admin, API, and integration review
•Logging, detection, and abuse-case analysis

Duration: 3-6 weeksScoped in discovery call

View service Book a SaaS product security review See people fit

Specialized sprints

Standard

Blue TeamAvailable

project

Secure SDLC & Product Security Baseline

Build a practical product security operating model engineering teams can actually run. Uses SDL, BSIMM, OWASP SAMM, threat modeling, secure code review patterns, CI/CD controls, vulnerability workflows, and developer enablement without heavyweight bureaucracy.

Outcome

4 deliverables

Best for

CTO, VP Engineering, Product Security Lead, AppSec Lead

•Maturity baseline and secure SDLC workflow
•Threat modeling process and security requirements templates
•CI/CD, SAST, SCA, and secrets workflow recommendations

Duration: 4-8 weeksScoped in discovery call

View service Build a product security baseline See people fit

Specialized

Blue TeamAvailable

assessment

High-Risk Feature Code & Design Review

Targeted code and design review for risky product surfaces: authorization, tenancy, APIs, file upload, webhooks, admin features, billing, integrations, AI actions, data exports, secrets, and privileged workflows. This is senior security review around the places SaaS products actually fail.

Outcome

4 deliverables

Best for

Engineering Lead, Product Security, AppSec, Security Architect

•Design and selected code review
•Authz, tenancy, and abuse-case checks
•Integration, webhook, AI action, and data exposure review

Duration: 1-3 weeksScoped in discovery call

View service Review a high-risk feature See people fit

Specialized

Blue TeamAvailable

implementation

Detection Engineering & SIEM Modernization

Improve detection quality, SIEM content, dashboards, and security telemetry. This is senior detection engineering, content quality, migration support, dashboarding, and telemetry architecture with Splunk credibility, plus Sentinel, Chronicle, Datadog, Elastic, Sigma, KQL, SPL, and detection-as-code where appropriate.

Outcome

4 deliverables

Best for

Security Engineering, Detection Engineering, SOC Lead, Product Security

•Detection coverage and log source inventory
•Splunk alert, SPL, app, and dashboard review
•Sigma, KQL, SPL, ATT&CK, and use-case mapping

Duration: 3-8 weeksScoped in discovery call

View service Plan a SIEM modernization sprint See people fit View proof

Specialized

Blue TeamAvailable

assessment

Cloud & Identity Security Hardening

A focused hardening sprint for cloud-native SaaS environments. Reviews IAM, service accounts, SSO/MFA, secrets, network exposure, storage, Kubernetes/container risk, Terraform/IaC, logging, and administrative access patterns.

Outcome

4 deliverables

Best for

Engineering Lead, Cloud Platform Lead, Security Architect, CTO

•IAM, service account, SSO, MFA, and admin access review
•Cloud exposure, secrets, storage, and network review
•Container, Kubernetes, Terraform, and IaC control review

Duration: 2-5 weeksScoped in discovery call

View service Harden cloud and identity See people fit

Delivery flow

Structured like an assessment. Delivered like a remediation system.

This is the work sequence the page is selling: no vague advisory loop, just a repeatable control and evidence path.

Scope the product

Define the product, AI features, systems, data, stakeholders, and evidence requirements.

control step

Map the architecture

Inventory models, vendors, APIs, RAG paths, tools, identities, logs, and trust boundaries.

control step

Identify control gaps

Review authorization, tenancy, approval gates, logging, detection, secure SDLC, and operational abuse paths.

control step

Prioritize the backlog

Rank findings by business impact, exploitability, customer pressure, and engineering effort.

control step

Package the evidence

Deliver architecture findings, control recommendations, and public-safe evidence artifacts.

control step

Outputs

Leave with artifacts product and engineering teams can use.

The deliverables are operational: inventory, findings, control recommendations, telemetry mapping, and evidence pack artifacts.

usable

AI System Inventory

Features, models, vendors, data flows, integrations, and customer-facing AI surfaces.

usable

Architecture Findings

Trust boundaries, control gaps, approvals, and exposure concerns.

usable

Control Recommendations

Guardrails, approval gates, logging requirements, and secure SDLC actions.

usable

Remediation Backlog

Prioritized engineering tasks with owners, sequencing, and follow-through.

usable

Detection & Telemetry Map

Events, logs, thresholds, dashboards, and SOC handoff guidance.

usable

Evidence Pack

Screenshots, traces, findings, controls, and audit-ready proof.

Assessment outputs are scoped to the systems, artifacts, access, and evidence reviewed. They do not prove the absence of vulnerabilities or replace formal audit/certification.

Connected system

Blue-team work connects into the workbench.

The service line should point directly into the products and evidence surfaces teams use after the assessment.

SecEng Surface Scanner

Discover and inventory every AI surface before it becomes an attack surface.

Explore Surface Scanner

SecEng Runtime Proxy

Capture AI runtime behavior, prompts, logs, tool calls, and evidence.

Explore Runtime Proxy

SecEng Authority Graph

Map AI action paths, approval boundaries, and blast-radius risks.

Explore Authority Graph

AIPSA Scorecard

Benchmark program posture and compare evidence maturity against the field.

Benchmark Your Program

Evidence Packs

Convert findings into governance- and sales-support evidence artifacts.

View Evidence Packs

Workshops

Use jumpstarts to scope, execute, or operationalize the work.

View Workshops

Next step

Start with the AI surface your business depends on.

Bring one product, feature, agent workflow, RAG path, or platform surface. We will scope the risk, map the system, identify the defensive gaps, and leave you with a backlog and evidence your teams can use.

Start with a Discovery Call Benchmark Your Program Explore SecEng Trace