Application & AI Security

Find and reduce risk in the software itself

Testing and review for applications, APIs, and AI-backed features, run against a threat model and closed out with a verification pass.

Review a Product or AI System

The Problem

Most software fails in predictable ways, until it doesn't

The common classes are well documented and still ship: broken authorization, injection into a query or a template, tenancy boundaries that hold in the UI but not in the API. What is newer is the AI surface. A feature that reads untrusted text and then acts on it collapses the boundary between instruction and data, and most testing programs were designed before that was a thing.

A scanner finds the first category and misses the second. Both need someone who understands what the system is supposed to do before deciding what counts as a break.

Who this is for

Software and SaaS companies shipping to enterprise customers
Teams putting an LLM in front of customer data or internal tools
Product manufacturers with software or firmware in the product
Engineering organizations without a dedicated product security team
Security leaders who need an independent read on a specific system

Common triggers

A customer or prospect is asking for a recent penetration test
An AI feature is close to launch and nobody has tested it adversarially
A significant re-architecture, migration, or acquisition
A finding from a bug bounty or a disclosure that suggests a wider problem
An annual cadence that has become a formality and stopped finding anything

What We Do

Services in this Practice

Scoped individually or combined. Most engagements pair a threat model with the testing that follows from it.

Application Security Assessments

Authentication and session handling, authorization and tenancy boundaries, input handling, business-logic abuse, and the trust assumptions between services. Manual work against a threat model, not a scanner run with a cover page.

What you get Findings report with severity, impact, and reproduction steps, plus a re-test pass

AI and LLM Security Reviews

Prompt and output handling, retrieval boundaries, tool-use and agent permissions, data segregation between tenants and sessions, and the model and data supply chain that feeds the feature.

What you get AI threat model, findings report, and a prioritized hardening plan

Penetration Testing

Methodology-driven offensive testing of applications, APIs, and the infrastructure behind them. Scoped to a stated objective so the result answers a question rather than filling a checklist.

What you get Findings report with reproduction steps, an attack narrative, and a re-test pass

Threat Modeling

Structured decomposition of a system: what it trusts, where the boundaries sit, what an attacker gains at each one, and which controls are load-bearing. Run as a working session with your engineers, not delivered over the wall.

What you get Threat model artifact your team can maintain, plus a ranked control gap list

Security Architecture Reviews

Design-level review before the code exists or before it is rewritten. Identity, secrets, data flow, isolation, failure modes, and the cost of the control you are about to commit to.

What you get Architecture review memo with decisions, trade-offs, and recommended changes

Source Code Reviews

Targeted reading of the code paths that matter: authentication, authorization, cryptography, deserialization, query construction, and the places where framework escape hatches get used.

What you get Annotated findings mapped to files and functions, with fix guidance per issue

Software Supply-Chain Reviews

Direct and transitive dependencies, build-pipeline integrity, artifact provenance, container base images, and the signing and verification steps between commit and deploy.

What you get Dependency risk inventory, SBOM, and pipeline hardening recommendations

Adversarial Security Testing

Goal-driven testing against a defined objective: reach this data, escalate to this role, break this tenancy boundary. Useful when you need to know whether a specific outcome is reachable.

What you get Attack path documentation, evidence of what was reachable, and containment advice

Deliverables

What You Receive

Executive summary stating risk in business terms, suitable for a board pack or a customer conversation
Technical findings with severity, impact, affected components, and reproduction steps
Threat model artifact your engineers can keep updating after we leave
Prioritized remediation plan ordered by risk reduction per unit of effort
Attack narrative showing how individual findings chain into a real outcome
Re-test report recording each finding as closed, open, or accepted in writing

After the Report

What Happens Once Gaps Are Identified

A findings report is the start of the work, not the end of it. Three things usually follow, and you can take any of them separately.

Have a system worth testing?

Tell us what it does and what would hurt if it broke. The first conversation is short and costs nothing.