Index › IT › Products › Flawfinder · November 2026 Edition
Static application security testing · Named, not ranked

Flawfinder

–Too few to rank
4/14Models named it
0First choices
3Warnings
November 2026 Edition · all company sizes counted.
Ranked inStatic application security testing #75 mid-market
What AI models recommend

Named, too few times to rank.

A product needs 10 labels in a category before a share is stated. Flawfinder has 4.

Why models recommend it

No positive label carried a quote.

What gives them pause

“legacy grep-based scanners (e.g., unmaintained Flawfinder versions or basic keyword detectors)”Gemini 3.5 Flash · Negative question · warning
“dangerous if used as your primary SAST”DeepSeek V4 Flash · Negative question · warning
“marks these tools with warnings (⚠️) indicating they haven't been updated in over a year or are archived”MiniMax M2.5 · Negative question · warning

Also on the shortlist

The products named in the same answers as Flawfinder, over the 4 answers that named it, and how often each was the first choice instead.

A side-by-side page exists where both products are among a category's top eight.

How this is measured

Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.

Gane sells AI visibility software. No company can pay to change a result.

Read the method →

Sources returned with these answers

The sites and pages the answers that named Flawfinder came back with. A fact about retrieval, not a cause of the answer.

Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 3 of the 4 answers that named Flawfinder and are not a share of its labels.

Domains cited

arxiv.org2
dev.to2
dl.acm.org2
github.com2
pmc.ncbi.nlm.nih.gov2
reddit.com2
aicodereview.cc1
analysis-tools.dev1
appsecsanta.com1
augmentcode.com1

No domain is on file for Flawfinder, so its own site is not marked.

Pages cited

Pages are listed as the models cited them.

By model

How each model answered on Flawfinder across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ModelFirst choiceAlternativeMentionWarningLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00011
Perplexity Sonar00000
Grok 4.2000000
Mistral Small00000
DeepSeek V4 Flash00011
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500011
GPT-6 Luna00000
Muse Glimmer 30B00101