Leader
29Heralded Score, range 22–49
The most visible vulnerability scanners in Spain, October 2026
Most cited source
26citations
From Google AI Mode 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 All | AI | Search | Score trend | Mentioned | Recommended | By engine | Mentioned by | Change |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 11 | | New entry | 5 , range 1–31 | 3#13 | 7#9 | 5
| 4% | 0% | None | First reading | |
| 12 | | New entry | 4 , range 1–30 | 4#12 | 5= #12 | 4
| 4% | 0% | None | First reading | |
| 13 | | New entry | 3 , range 1–27 | 5#10 | 0= #21 | 3
| 5% | 0% | None | First reading | |
| – | | Unranked | Too few answers | Not measured | 4#15 | –
| 1% | 0% | None | First reading | |
| – |  AWS Inspector US | Unranked | Too few answers | Not measured | 0= #21 | –
| 0% | 0% | | First reading | |
| – | | Unranked | Too few answers | Not measured | 0= #21 | –
| 0% | 0% | None | First reading | |
| – | | Unranked | Too few answers | Not measured | 1= #19 | –
| 0% | 0% | None | First reading | |
| – | | Unranked | Too few answers | Not measured | 0= #21 | –
| 1% | 0% | | First reading | |
| – | | Unranked | Too few answers | Not measured | 0= #21 | –
| 0% | 0% | None | First reading | |
| – | | Unranked | Too few answers | Not measured | 0= #21 | –
| 0% | 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. AI and Search give each brand’s score and rank on that side alone. By engine has one dot per engine (ChatGPT, Google AI Overviews, Gemini and Google AI Mode), darker the more often it names the brand.
Most cited sources
| Rank | Source | Type | Cited in | Engines | Pages cited | Brands its pages mention |
|---|---|---|---|---|---|---|
| 1 | | Community | 18.3% | 2 of 4 | 18 | 3 |
| 2 | | Vendor site | 11.7% | 1 of 4 | 18 | 5 |
| 3 | | Regulator | 11.7% | 1 of 4 | 9 | 1 |
| 4 | | Consultancy | 15.0% | 3 of 4 | 2 | 6 |
| 5 | | Community | 8.3% | 1 of 4 | 8 | 1 |
| 6 | | Social | 10.0% | 1 of 4 | 7 | Not read |
| 7 | | Vendor site | 1.7% | 1 of 4 | 5 | Not read |
| 8 | | Vendor site | 8.3% | 3 of 4 | 2 | 4 |
| 9 | | Social | 5.0% | 1 of 4 | 4 | Not read |
| 10 | | Industry authority | 5.0% | 2 of 4 | 3 | Not read |
Questions asked
| Question | Language | Most recommended |
|---|---|---|
| how do application scans compare with dependency checks for finding vulnerabilities | English | No brand recommended |
| should developers or security teams own vulnerability scanning | English | No brand recommended |
| what can replace manual security checks before each software release | English | No brand recommended |
| how can we replace spreadsheets for tracking software vulnerabilities | English | |
| what can replace separate scanners for code and dependencies | English | |
Each engine's top three
Related leaderboards
Method
Each leaderboard ranks brands on two sides. AI is how ChatGPT, Gemini, Google AI Overviews and Google AI Mode answer the board's buyer questions. Search is Google's top 10 results for the keywords behind those questions. All combines the two, where Search is measured.
For the AI side, 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.