0Day vs. dependency scanners: what’s the difference?
Short answer: a scanner tells you what to patch; 0Day tells you the moment something you ship comes under attack. They solve different problems, and most teams that use 0Day run it alongside the scanning they already have.
What does a dependency scanner actually do?
Dependency scanners (the category is called software composition analysis, or SCA) audit your repositories against a database of published advisories. When a CVE or advisory exists for a package you use, the scanner opens an alert or a patch pull request. Built-in platform scanning and commercial SCA tools all follow this same model: a known advisory in, a remediation task out. They are very good at that, and you should keep one running. The limitation is structural: a scanner can only react after an advisory has been written, reviewed, and published. During an active supply-chain attack, that publication lag is exactly the window attackers exploit.
How is 0Day different?
0Day is the awareness layer that sits in front of your scanner. It ingests raw threat intelligence from 20+ sources (security-research firms, registry monitors, government feeds, advisory databases) and uses AI to triage and corroborate every signal, hours or days before an official advisory or CVE exists. Each signal is matched against your GitHub organization’s dependency graph: every repository, every transitive dependency, down to the exact version (an SBOM-based match). If a flagged package intersects something you actually ship, the engineers who own the affected repositories get a push notification on their phones within minutes. If it doesn’t intersect your code, you never hear about it. That’s the whole product: speed and relevance, not audit coverage.
Side-by-side
| Dimension | Dependency scanners (SCA) | Advisory feeds & newsletters | 0Day |
|---|---|---|---|
| Trigger | Published advisory / CVE | Editorial coverage | Corroborated raw intelligence, often pre-CVE |
| Latency | Hours to days after publication | Hours to days, plus your reading backlog | Minutes after corroboration |
| Relevance filter | Your repos (known advisories only) | None. Everything, for everyone | Your org’s dependency graph, exact package and version |
| Delivery | Dashboard, PRs, CI checks | Inbox, RSS, social media | Push notification to the engineers who own the affected repos |
| Output | Remediation tasks | Reading material | A decision point: pin, patch, or pause a deploy, now |
| Replaces the other? | ← No, complementary → | No, runs alongside both | |
Does 0Day replace my scanner?
No, and it doesn’t try to. Keep your scanner for what it’s built for: systematic auditing, license checks, patch automation, and compliance reporting. 0Day covers the gap your scanner structurally cannot: the hours between a package being compromised and an advisory being published. In incidents like the npm “Shai-Hulud” worm, trojanized package versions spread through the ecosystem well before advisories caught up. Teams with an early-warning layer had time to pin versions and pause deploys while others were still unaware.
Where does 0Day fit in a DevSecOps workflow?
If you run a DevSecOps practice, 0Day slots in as the real-time intelligence input alongside your existing SCA tooling: scanners own remediation cadence and compliance, 0Day owns time-to-awareness. If you’re an engineering lead without a dedicated security function, 0Day is designed to work with zero security staff: connect the GitHub organization once, and every engineer gets alerts for the repos they own. There’s no triage queue to babysit and no dashboard to check. Either way, access is read-only and SBOM-based, and 0Day never reads your source code.