AI Security Evaluations Need Different Questions From Accuracy Tests
Design AI release checks that distinguish answer quality from unauthorized access, unsafe actions, and failures of business controls.
Application security, AI threats, and the decisions behind stronger defenses. Written by Mario Luckeneder, founder of Ceron.
Design AI release checks that distinguish answer quality from unauthorized access, unsafe actions, and failures of business controls.
Connect reusable security answers to system changes, evidence versions, review triggers, and correction records before stale statements are reused.
Assess extension permissions, business use, update ownership, and access to sensitive browser pages alongside ordinary SaaS integrations.
Review redirects, DNS resolution, destination rules, and response limits when applications fetch links supplied by users or AI tools.
Examine authentication methods, fallback paths, privilege, and session behavior for external administrators and support providers.
Examine how document ownership, ingestion, version history, and source verification affect the integrity of answers from a company knowledge base.
Connect a discoverable security contact to report intake, triage, scope, acknowledgments, and a maintained vulnerability disclosure process.
A CVE with a 9-plus CVSS score lands in your inbox, a vendor's security page turns red, and five different people in Slack ask the same question in five different ways: are we affected?
Review package scopes, registry routing, lockfiles, and install behavior to prevent private dependencies resolving from unintended sources.
Trace uploaded files through validation, storage, scanning, previews, downloads, and deletion to review the full processing path.
Most website security problems aren't hidden.
A missing security header rarely takes more than one line to fix.
Before an attacker ever touches a login form or tries a single exploit, they've usually already learned a lot about your company just from your domain name.
The padlock icon in a browser's address bar has become shorthand for safe.
Run any website security scan and you'll get a list back. Some of it will look alarming.
Security assessment providers all sound similar on a sales call.
Review domain verification, tenant selection, account linking, and ownership changes in enterprise single sign-on onboarding.
Review model files, loading code, dependencies, and artifact provenance before introducing a downloaded model into business infrastructure.
Distinguish discovery, engineering completion, deployment, retesting, and accepted exceptions when reporting vulnerability remediation.
None of the traditional lines of defense move at the speed of an agent swarm coordinating over its own private channel.
Review persistent state, network reachability, credentials, and job isolation when builds run on company-managed CI infrastructure.
Separate sender verification, replay checks, duplicate handling, and business-state validation in webhook consumers.
The contract with your old IT provider ends on a Friday. The new provider starts Monday.
Between August 8 and August 18, 2025, attackers used stolen OAuth tokens from a single third-party chat integration to pull data out of more than 700 Salesforce environments, plus a subset of connected Google Workspace inboxes.
Most security assessment providers get paid the same amount whether they find a critical vulnerability or nothing at all.
Two CTOs can spend the same security budget on completely different things and end up with completely different answers to the same question: what's actually wrong with our systems.
Every SaaS product eventually earns a login screen that matters more than the rest of the site combined.
A cloud migration doesn't move your security posture along with your data. It resets it.
Investors used to evaluate a startup on three things: the team, the market, and the traction.
You can describe an entire SaaS product in a chat window and have a working, deployed application within a weekend.
Ask most companies how many domains and subdomains they operate, and the number they give you is almost always wrong, not because anyone is lying, but because nobody has actually looked.
The website is done. The agency sends the final invoice, you make the last payment, and the project moves into "launched" status.
Attackers don't wait for Black Friday to start planning for it.
Buying a company means buying its data, its infrastructure, and every unresolved vulnerability sitting inside it, whether anyone disclosed those vulnerabilities or not.
A vulnerability assessment report tells you what's broken.
Security assessment gets treated as one product on most sales pages, but web application testing and infrastructure testing check fundamentally different layers of your environment, using different methodology, finding different categories of risk.
An enterprise prospect's security team sends over a questionnaire, or a one-line email asking for your latest penetration test report, and the deal that was moving through your pipeline suddenly stalls on a document you don't have.
Pre-launch is the cheapest point in your company's life to find a security problem, and the most expensive point to skip looking for one.
A website security audit means something specific: a scoped engagement where your web applications, APIs, cloud infrastructure, and access controls get tested against real exploitation techniques, not just matched against a list of known software versions.
The old framing was simple: automated vulnerability scanning was fast and shallow, manual penetration testing was slow and thorough, and businesses picked one or budgeted for both.
The right cadence depends on compliance obligations, how fast your attack surface changes, and what happens between assessments if something new gets exposed and nobody catches it.
An external security assessment tests your organization the way an actual attacker sees it: from outside your network, with no privileged access, using only what's publicly reachable.
Security testing has run on the same basic model for two decades: automated scanners flag known issues, and human testers manually dig for what the scanners miss.
Security assessment pricing spans an enormous range in 2026, anywhere from a few hundred dollars for an automated scan subscription to well into the six figures for a full penetration test across a complex enterprise environment.
Compliance frameworks like SOC 2 and PCI DSS often require both a vulnerability assessment and a penetration test, but plenty of security budgets get spent on one when the mandate actually called for the other.
Follow deprovisioning from the identity provider to SaaS roles, active sessions, API credentials, and scheduled work.
Trace prompts, responses, and retrieved documents across AI logs to define retention, access, and evidence collection for business data.
Combine severity, predicted exploitation, known exploitation, and local exposure without treating any one score as a complete risk decision.
AI has changed the economics of cyberattacks. Mario Luckeneder explores what happens when offense scales faster than defense.
Connect container digests, base-image updates, rebuilds, and running deployments to verify that a patch reaches production.
Review depth, breadth, aliases, batching, and resolver authorization when testing the workload behind a GraphQL request.
Evaluate emergency account dependencies, custody, monitoring, and recovery drills without weakening normal administrator access.
Examine how token budgets, concurrent jobs, retries, and tenant quotas affect the cost and availability of an AI business feature.
Design and test audit events that connect actors, customer accounts, actions, outcomes, and request identifiers without retaining unnecessary secrets.
Understand what dependency lockfiles establish, how clean installs use them, and which package changes still require security review.
Review response fields, editable properties, nested updates, and schema changes when a user may access a record but not every value inside it.
Build a reviewable lifecycle for automated identities, including ownership, permissions, credential use, and safe retirement.
Separate structured output, authorization, and transaction validation before model-generated content reaches databases or business systems.
Review approval, scope, actor attribution, restricted actions, and expiry for tools that let support staff view customer accounts.
Trace a disclosed credential through revocation, replacement, access review, and repository cleanup to verify the exposure is contained.
Follow subdomains, provider bindings, certificates, and ownership records when decommissioning a hosted application or campaign site.
Review repository, workflow, environment, and audience conditions when CI jobs exchange OIDC tokens for cloud deployment credentials.
Understand token audience, delegated access, and consent boundaries when connecting business applications through Model Context Protocol.
Connect provider payment status to order fulfillment, duplicate handling, delayed methods, and customer-account binding.
Use component inventories and exploitability statements together while checking release identity, completeness, and deployment context.
Distinguish management events from data events and verify which cloud actions are visible before an investigation depends on them.
Follow concurrent token renewal, replay detection, lost responses, and recovery without turning integration failures into repeated credential reuse.
Follow document permissions through retrieval, cached answers, and citations to test whether an AI search system respects access changes.
Test whether concurrent requests preserve single-use actions, balances, and approval limits across business transactions.
Examine OIDC publishing, workflow identity, package ownership, and remaining credentials when moving npm releases to trusted publishing.
Examine workload creation, secrets, service accounts, and namespace boundaries when assessing Kubernetes access permissions.
Test reset-token binding, expiry, reuse, notifications, and session behavior across the full account recovery workflow.
Map an AI agent’s tools to business authority, separate preparation from execution, and verify permissions with controlled workflow tests.
Follow queued exports from request through generation and download, including permission changes, retries, and tenant-bound storage.
Separate artifact identity, build provenance, and software quality when evaluating signed release evidence in a deployment pipeline.
Verify data restoration, credentials, application dependencies, and business output instead of relying only on successful backup jobs.
Distinguish passwords, access tokens, refresh tokens, and application sessions when verifying that an account reset removes access.
How prompt injection reaches assistants through documents, where business permissions matter, and what a controlled security test can establish.
Check cache keys, response directives, authentication, and invalidation before customer-specific content reaches a shared cache.
Review how untrusted contributions, workflow permissions, artifacts, and release jobs interact in a GitHub Actions pipeline.
Review how signed file links are issued, shared, logged, expired, and invalidated when private documents leave an application’s access checks.
Review enrollment, lost devices, recovery, and session handling when introducing passkeys to employee or customer accounts.