Leader
38%of answers name it
The most visible vulnerability scanners, October 2026
Most cited source
66citations
From Google AI Mode, Google AI Overviews and ChatGPT
Where engines disagree most
1/4engines put it in their top three
Top three on Gemini, not on Google AI Mode, Google AI Overviews and ChatGPT
Brands
| Rank | Brand | Rank change | Heralded Score | Score trend | Mentioned | Recommended | By engine | Mentioned by | Change |
|---|---|---|---|---|---|---|---|---|---|
| 1 | | New entry | 39 , range 34–45 | 39
| 38% | 10% | | First reading | |
| 2 | | New entry | 32 , range 20–38 | 32
| 22% | 9% | None | First reading | |
| 3 | | New entry | 27 , range 10–35 | 27
| 18% | 6% | None | First reading | |
| 4 | | New entry | 24 , range 9–34 | 24
| 19% | 3% | None | First reading | |
| 5 | | New entry | 13 , range 6–32 | 13
| 13% | 4% | None | First reading | |
| 6 | | New entry | 9 , range 5–30 | 9
| 12% | 2% | None | First reading | |
| 7 | | New entry | 6 , range 3–21 | 6
| 7% | 2% | None | First reading | |
| 8 | | New entry | 6 , range 3–19 | 6
| 7% | 2% | None | First reading | |
| 9 | | New entry | 4 , range 2–9 | 4
| 5% | 0% | None | First reading | |
| 10 | | New entry | 3 , range 2–9 | 3
| 5% | 0% | None | First reading |
“=” marks brands whose score ranges overlap, so the test cannot separate them. Every brand named in at least three answers is ranked. By engine has one dot per engine (ChatGPT, Google AI Overviews, Gemini and Google AI Mode), darker the more often it names the brand.
This month's moves
First reading. No comparable previous month yet.
Biggest risers
No clear rise.
Biggest fallers
No clear fall.
New entries
Drop-outs
No drop-outs.
Most cited sources
| Rank | Source | Type | Cited in | Engines | Pages cited | Brands its pages mention |
|---|---|---|---|---|---|---|
| 1 | | Reference | 1.7% | 1 of 4 | 2 | Not read |
| 2 | | Reference | 3.3% | 2 of 4 | 1 | 0 |
| 3 | Withheld. Run a full Snapshot to see it. | |||||
| 4 | | Reference | 1.7% | 2 of 4 | 2 | 0 |
| 5 | | Reference | 0.8% | 1 of 4 | 1 | 0 |
| 6 | | Reference | 0.8% | 1 of 4 | 1 | Not read |
| 7 | Withheld. Run a full Snapshot to see it. | |||||
The questions, and who wins each
| Question | Language | Wins it |
|---|---|---|
| what vulnerability scanner should a security team use to find software flaws | English | |
| which tool can scan our applications for security vulnerabilities | English | |
| how do small engineering teams scan code for vulnerabilities | English | |
| what can help developers find vulnerabilities before release | English | No brand recommended |
| how can i find vulnerabilities across our applications | English | |
| how do we catch security flaws in code before deployment | English | |
| how can my team find and prioritize software vulnerabilities | English | No brand recommended |
| how do i check whether our software has known vulnerabilities | English | |
| should we scan source code or running applications for vulnerabilities | English | No brand recommended |
| what works better for finding flaws, manual reviews or automated scans | English | No brand recommended |
Each engine's top three
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Method
Each month Heralded asks every engine the same buyer questions, twice each, and reads every answer. An answer counts 0 for a brand it leaves out, 50 for a brand it names and 100 for a brand it recommends, and the Heralded Score is built from those. A brand named in at least three answers gets a score and a place.