To scan websites for security issues you point a scanner at the running application, let it crawl and probe every reachable request, and then triage the findings by exploitability rather than raw count. The phrase "scan websites" covers everything from a five-minute header check to a full authenticated dynamic test, so the first decision is what depth you actually need.
Most teams start scanning too late, after a site is already public, and treat the report as a compliance checkbox. A better model treats scanning as something you run continuously against staging and production, wired into the same pipeline that ships code.
What a website scan actually looks at
A web scanner works from the outside in. It requests pages, follows links and forms, builds a map of the application's endpoints, and then sends crafted inputs to each parameter to see how the server responds. Nothing about the source code is required, which is why this style of testing is called dynamic application security testing, or DAST.
The classes of issues a scan surfaces fall into a few buckets:
- Injection flaws, where user input reaches a SQL query, shell command, or template engine.
- Cross-site scripting, where input is reflected into a page without encoding.
- Broken access control, where changing an ID or path exposes another user's data.
- Misconfiguration, such as missing security headers, verbose error pages, or default credentials.
- Known-vulnerable components, where a fingerprinted framework version maps to a public CVE.
A scanner is good at the first, second, and fourth. It is weaker at access control, which usually needs a human who understands the app's intended permissions.
Passive versus active scanning
Passive scanning observes traffic without changing it. It flags a missing Content-Security-Policy, a cookie without the Secure flag, or an outdated jQuery version. It is safe to run against production because it never sends attack payloads.
Active scanning sends probes designed to trigger a vulnerability: a quote character to test for SQL injection, a script tag to test for reflected XSS, a path traversal sequence. Active scans can create test data, trip rate limits, or in rare cases corrupt state, so run them against a staging copy first.
If you only do one thing today, run a passive scan. The signal-to-effort ratio is excellent and there is no blast radius.
Choosing a tool
The open-source starting point is OWASP ZAP. It runs as a proxy, a headless daemon, or in CI, and its baseline scan is a well-tuned passive pass you can drop into a pipeline in an afternoon. Nikto is a fast, noisy server-configuration checker that is worth a single run early on. For dependency and component issues that a black-box crawl cannot see, pair the site scan with software composition analysis so you catch vulnerable libraries the site pulls in.
Commercial dynamic scanners add authenticated crawling, single-page-app support, and better false-positive handling. Our DAST product is built for the authenticated, JavaScript-heavy apps that trip up older crawlers, and it correlates dynamic findings with the dependency data from SCA so a single vulnerable request and the library behind it show up as one issue rather than two.
Running a scan in CI
Here is a minimal ZAP baseline scan wired into a pipeline. It exits non-zero when it finds issues above a threshold, which is what turns a scan into a gate.
docker run --rm -v "$(pwd):/zap/wrk:rw" \
ghcr.io/zaproxy/zaproxy:stable \
zap-baseline.py \
-t https://staging.example.com \
-r zap-report.html \
-I
The -I flag keeps the build green on warnings so you can ramp up strictness over time instead of blocking every merge on day one. Once the team trusts the output, drop -I and fail on new findings.
For authenticated scanning you feed the scanner a session token or a login script so it can reach pages behind the login wall. An unauthenticated scan of an app that hides everything behind auth will report almost nothing useful.
Triaging what comes back
A raw scan report is not a to-do list. Every dynamic scanner produces false positives, and severity labels are generic guesses that do not know your architecture. Work the results like this:
- Confirm the finding by hand. Reproduce the request the scanner sent and check the response yourself.
- Judge exploitability. A reflected XSS on an internal admin page behind SSO is not the same risk as one on a public signup form.
- Deduplicate. Ten findings on the same parameter across ten URLs are usually one bug.
- Route the real ones to the owning team with the exact request that triggered them.
The teams that get value from scanning are the ones that keep the confirmed-finding list short and act on it, not the ones that generate the biggest PDF. If you want to build the triage muscle, the Safeguard Academy has walkthroughs on reading scanner output.
Making it continuous
A one-time scan tells you about today. Web apps change every sprint, and each change can reintroduce a fixed bug or add a new endpoint nobody scanned. Schedule a passive scan on every deploy to staging, run a deeper active scan nightly, and reserve manual penetration testing for the high-risk flows a scanner cannot reason about, like multi-step checkout or permission boundaries.
Keep a baseline of accepted findings so the pipeline only alerts on new issues. Without a baseline, the same twenty known items scream on every run and the team learns to ignore the report entirely.
FAQ
Is it legal to scan any website?
Only scan sites you own or have written permission to test. Active scanning sends attack payloads, and running them against a site you do not control can violate computer-misuse laws even if you cause no damage. Get authorization in writing before you point a scanner at anything external.
How long does a website scan take?
A passive baseline scan of a small site finishes in minutes. A full authenticated active scan of a large application can run for hours because it multiplies every payload across every discovered parameter. Scope the scan to the areas that changed to keep runs fast in CI.
Can a scanner find every vulnerability?
No. Automated scanning is strong on injection, XSS, and misconfiguration but weak on business-logic flaws and access-control bugs that require understanding intended behavior. Combine automated scans with periodic manual testing for full coverage.
What is the difference between DAST and SCA?
DAST tests the running application from the outside and finds flaws in how the app handles input. SCA inspects the dependencies your app ships and flags known-vulnerable versions. They see different problems, so mature teams run both.