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AI Application Security needs a reset. Every application security tool in production today was built on a quiet assumption: that an application produces the same output for the same input. AI features have invalidated that assumption, and most AppSec programs do not yet realize it. SAST, DAST, WAFs, penetration tests, bug bounties: each sees a fraction of the actual behavior of an AI-enabled application, and misses the rest. This engagement closes the gap.
The moment an application calls a language model, retrieves dynamic context, or hands control to an autonomous agent, the entire AppSec stack starts seeing partial behavior. Scans pass. Runtime defenses match patterns that no longer reflect what the application actually does. Bug bounties pay for reproducible exploits in an environment where reproducibility has become probabilistic.
The old application had three stages: input, code, and output. Every instrument the discipline owns assumes the behavior lives in the code. An AI application has six: input, interpretation, decision, authority, action, and consequence. Three of those did not exist before, and the toolchain sees one of them. Eleven controls can report green while covering a single stage out of six.
This engagement names that condition The Runtime Determinism Gap™, the single most important shift in application security since the move to cloud. Teams that close it use AI to compress the review and triage cycles they have been losing for a decade, and rebuild runtime defenses around behavioral validation rather than pattern matching. Teams that do not keep shipping applications that pass every scan and still fail in production.
The engagement is a defensible review of your AppSec program against the realities of AI-enabled applications, aligned with the OWASP LLM Top 10, the Google Secure AI Framework, and emerging AI procurement expectations. It runs against five working frameworks, each installed as an instrument with an owner and a cadence rather than a policy.
The application surface areas that change once AI is introduced: language inputs, retrieval paths, output renderers, and agent boundaries. Mapped against your own portfolio, not a reference architecture, so the surface is the one you actually run.
The new bug taxonomy that exists at the meaning layer rather than the syntax layer, and how it maps to and extends the OWASP Top 10 and OWASP LLM Top 10. The governing rule is the one the whole discipline turns on: untrusted content may inform the model, but it must never authorize a side effect.
The arithmetic of vulnerability management when AI changes both the production rate of code and the inspection rate of security, with named inputs your team can measure. This is the number that turns a backlog complaint into a decision a CFO can act on.
The integrated operating model that merges DevSecOps with AI-specific controls without slowing release cadence. Scored across seven areas, dated and reviewed, and it is the artifact every other instrument reads.
The release-and-runtime model that replaces point-in-time scanning with ongoing behavioral validation, with reference architecture for each layer. Because pre-runtime assurance is not merely hard in the general case, it is impossible, the bound has to hold while the application runs.
Every deliverable is a working instrument, operated against your portfolio rather than handed over as a template. The engagement is complete when the artifacts are producing decisions, not when the documents exist.
Three properties organize the entire model, stated as properties a running estate must hold rather than principles a team should value. Known: every application that calls a model is in the register, with an owner and a tier, and coverage is measured rather than assumed. Bounded at runtime: no application can cause more than its tier permits, enforced outside the model by a plane it did not build and cannot bypass. Observed: what each application actually did is reconstructable from telemetry the enterprise owns.
The distinction the market now tests for is the one between a gate you passed once and verification that runs at the rate the application changes. Only the second produces evidence that is current on the day it is asked for.
Each week produces the artifact the next week reads. Weeks one through four establish the numbers: the program baseline scored, the discovery sweep run, and the register built so coverage has a real denominator. Weeks five through eight build the boundaries: applications tiered by blast radius, the authority ledger filled, semantic classes mapped onto triage, and the first bound live in the pipeline. Weeks nine through twelve put it into operation: telemetry specified, the validation loop running, the behavior baseline observing, and the evidence pack assembled for the first reviewer who asks.
A team that reaches week twelve has done in a quarter what most organizations spend a year discovering, because the sequence has already been discovered. The gaps that remain are the roadmap for the second ninety days.
AppSec leaders and program managers, security architects, senior developers and tech leads, DevSecOps and platform engineers, CISOs and security directors, and product engineering managers in organizations shipping AI-enabled applications. The tone is technical-executive: precise enough that a principal engineer respects it, accessible enough that a VP of Engineering walks into a Monday review with a specific list of questions.
OWASP LLM Top 10 is becoming a procurement question. Customer questionnaires are expanding to cover AI vendor risk. Enterprise contracts are starting to require evidence of prompt injection coverage and output validation, and four parties will eventually ask what your applications can reach, on their schedule rather than yours: the board, internal audit, the external auditor and insurer, and the regulator.
Organizations that build the operating model now own the AppSec maturity narrative inside their procurement cycles. Organizations that wait inherit a remediation scramble when the questionnaire arrives. And the gap compounds: every sprint that ships an AI-enabled feature adds to a surface nobody has mapped, and the first complete map is cheapest the day you start it.
The book is the operating manual, written for the application security leaders who will run the program themselves: the register, the tier map, the authority plane, the behavior baseline, and the debt model, installed against their own estate, with every figure and all twenty-two instruments of the Consulting Toolkit free to download on the book page. The engagement is for organizations that want the baseline scored, the discovery sweep run, the bounds drawn, and the first ninety days sequenced inside a defined timeline, with the judgment calls made alongside someone who has run product and application security incident response at Intel and McAfee scale.
Teams that want the discipline in book form work from the Library. Teams that want it running by week twelve work directly with the firm.
Pillar II runs in sequence. The AI IT Security Audit™ proves what AI exposure exists across the enterprise. The AI IT Security Implementation & Strategy™ converts the audit into a running security program. Secure by Design in the Age of AI™ turns the discipline onto the products you ship, before insecure patterns harden into the architecture. Application Security in the Age of AI™ secures those applications in production, and the AI now embedded in them. Cloud and Infrastructure Security in the Age of AI™ secures the layer everything runs on. Each engagement stands alone; together they are one operating discipline.
The first conversation is thirty minutes and free: which applications, which tiers, what your current coverage actually is, and whether the ninety-day sequence fits your release cadence. If the fit is right, the engagement is scoped to your portfolio size and tier mix. If the book is the better next step, that is what will be recommended, and every instrument it installs is already free on the book page. Schedule the consultation and bring your most ambitious release date.
A 30-minute consultation to scope the question your leadership team needs answered. No deck, no pitch. A conversation about where your organization currently stands and what the right next step looks like.