Many evaluations go wrong because of a few shared beliefs: more findings means better coverage, a high score means high risk, a demo equals a trial. Each is partly true and often misleading. Here are the common myths and what holds up when you test them on your own code.
Myth: more findings means a better scanner
Fact: more findings can mean more false positives, or duplicates of one issue. Verify a sample by hand and measure what is real. A shorter list that is right serves you better.
Myth: critical severity means fix first
Fact: severity measures how bad a flaw could be. The CVSS guide states base scores measure severity, not risk. Exploitation evidence, exposure and reachability change what matters first.
Myth: a polished demo shows what the tool does
Fact: demos use prepared data. Insist on your own repositories, and let your engineers drive. Our vendor demo script shows how.
Myth: automation removes the need for review
Fact: automation shifts effort from finding and typing to reviewing. Keep humans on merges and on exceptions until your measured results justify less.
Myth: one tool should do everything
Fact: breadth is attractive, but depth in your top asset types matters more. Consolidate where the quality holds, and keep specialist tools where it does not.
Myth: switching tools fixes the backlog
Fact: a new tool may reorder and shrink the list, but ownership and process decide whether items get closed. Fix those in parallel.
Myth: a free scanner is never enough
Fact: for small estates it often is. Be honest about your size before buying.
A last check: ask what would change your mind. Before the trial, write down one result that would make you reject your favorite candidate. It is a cheap guard against falling for a tool because of a good first impression.
Where Safeguard fits
Safeguard covers SBOM and dependency scanning, reachability analysis, policies and gates, and fix pull requests that stay off until you turn them on. You can try a free scan on a repository before you commit to anything.
Try it yourself
Try the check and see how the same finding reads differently once exploitation information is added.
Click through it at your own pace, or open it full screen.
Quick check
What is the single most useful trial habit?
Verify a random sample of findings by hand.
Should I trust vendor benchmarks?
Treat them as questions to test, not answers.
Sources
Last reviewed: 19 October 2026.
