Can an AI “False Positive” Decision Close an Alert?
Define what the alert detects before separating benign triggers, blocked attacks, and insufficient evidence. An assistant can propose evidence-linked triage; closure requires predefined criteria.
#authorization
21 postsConnecting an attack agent: planning, execution, and feedback
Build a bounded HTTP testing loop with explicit planner, executor, verifier, trace, and stop conditions.
Can AI compose an attack chain? From CTFs to a public incident
Replay a ticket attack chain and analyze Anthropic’s public incident report, separating evidence, human decisions, evaluation shortcuts, and visibility limits.
How AI turns a target into an attack surface
Turn ticket-service documentation and HTTP observations into a source-linked attack surface and choose the next minimal test.
AI Code Review: Turn Suspicious Code into a Testable Finding
Trace identity, object selection, and the return path before testing allowed and forbidden pairs. Review comments propose hypotheses; an independent policy and observed output establish the finding.
How to verify an AI-generated exploit test
Replay HTTP exploit requests against vulnerable and fixed services, verify exact resource content, and reject status-only success claims.
Who Can Read Which Data After Login? Identity and Authorization for AI Assistants
The backend derives the acting identity from trusted authentication, then checks the requested action against the resource. Test an explicit same-tenant, owner-only policy with allowed and denied reads.
Build an AI-Assisted Incident Timeline Without Inventing Missing Events
Normalize time without discarding provenance. One ticket read establishes that read; an assistant claim, missing logs, and a later denial cannot substitute for the underlying evidence.
An Integrated AI Security Exercise: From Attack Evidence to a Fix and Regression
Compare vulnerable and fixed builds with the same HTTP requests, retaining ticket responses, audit events, and a timeline. Block unauthorized reads while preserving legitimate access.
What Must You Verify After an AI Patch?
A patch must block unauthorized access, preserve legitimate behavior, and pass against the actual target. A cleared alert and a passing local copy each establish only part of that result.
How AI attacks another AI: indirect injection and tool misuse
Trace hostile attachments into tool requests and separate model susceptibility from backend data exposure using a live-LLM training lab and HTTP replay.
Security Assistant Tools: From Read-Only Investigation to Response
Investigation access does not imply response authority. A trusted executor must verify role, incident, exact proposal, and current state before applying a change and recording its result.
An available tool does not authorize this invocation
Bind a ticket export to its caller, resource, action, destination, and approval. Test substituted arguments, revocation, expiry, and replay.
AI Says It Found a Vulnerability. What Evidence Do You Need?
Treat AI suggestions as hypotheses. Preserve actual inputs and outputs, check the target data against the authorization policy, and use normal and patched controls to rule out false positives.
Let AI look for vulnerabilities: from clues to testable hypotheses
Turn AI suspicions into falsifiable authorization hypotheses with same-tenant and cross-tenant controls.
How Can You Demonstrate That AI Helps Security Work?
Freeze independent labels before measuring false positives, false negatives, abstention, human effort, and unsafe actions. Faster closure does not establish correct closure, and rule replay is not model evidence.
Delegated Authorization for AI Agents: Do Not Hand User Tokens to the Model
An agent should execute one task with a short-lived, audience- and permission-restricted credential while preserving user and agent identities, execution-time authorization, confirmation, and audit lineage.
Better Auth: A TypeScript Authentication Framework, Not Application Authorization
Better Auth unifies login, sessions, providers, and plugins; applications still own resource authorization, revocation latency, and policy for agent actions.
Better Auth: Should Authentication Live Inside Your TypeScript App?
Better Auth trades a managed identity platform for an in-app library and your own database; that gives you control, but migrations, security updates, and incident response become your responsibility.
Clerk Authentication Platform: From UI Components and Session Tokens to Organization Authorization
Clerk's real value is an integrated identity lifecycle, not a sign-in box; resource authorization, tenant isolation, and business-data consistency remain your application's responsibility.
Stytch Deep Dive: From B2C Login and Sessions to B2B Organizations and Authorization
Stytch is an API-first managed identity platform: choose the Consumer or B2B model, converge authentication factors into sessions, then enforce organization and RBAC boundaries on the server.