Category field guide
Security scanners and agents used to model threats, discover weaknesses, validate exploitability, guide remediation, and track accountable outcomes.
My position
Snyk and Codex Security belong beside the development workflow but not inside a generic coding-tool bucket. Their job is to produce security evidence that can survive triage, validation, remediation, and retesting—not simply more code or more findings.
AI security analysis can increase coverage and speed while also creating new failure modes: prompt injection from repository content, severity inflation, unsafe proof-of-concept execution, missed paths, and confident fixes that change behavior. Every consequential result needs an independent gate.
The working set
A field-note label is not a downgrade or a placeholder. It is the honest boundary between useful experience and a completed repeatable review.
A developer-first application-security platform spanning code, dependencies, containers, infrastructure as code, secrets, and developer workflow integrations.
Use Snyk as a structured AppSec signal and remediation layer, not as proof that an application is secure.Read the profile →OpenAI's application-security agent for repository threat modeling, vulnerability discovery, validation, remediation guidance, and security-review workflows.
Treat Codex Security as an evidence-producing security analyst, with every finding validated and every fix reviewed before it becomes a tracked vulnerability or code change.Read the profile →Selection rules
A source-backed security decision that identifies the affected asset, attacker path, impact, owner, remediation, and verification evidence.
