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Secure code training · November 2026 Edition

SecureFlag vs Veracode Security Labs

Four of fourteen models named SecureFlag first on the direct prompt; zero named Veracode Security Labs. SecureFlag was named by fourteen of the fourteen models and Veracode Security Labs by twelve and SecureFlag carries 41 labels and Veracode Security Labs 23, so the shares are not directly comparable.

SecureFlag

accepted challenger

Named in one category this edition.

Veracode Security Labs

criticized challenger

Named in one category this edition.

First-choice share12%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%35%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#8A position in a field of 13; printed, not drawn.
Labels4123A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, SecureFlag reading right to left. Rank and label count are printed, not drawn.Secure Code Warrior Learning Platform was named alongside these two in fourteen of the fourteen direct answers. Secure Code Warrior Learning Platform vs SecureFlag · Secure Code Warrior Learning Platform vs Veracode Security Labs · SecureFlag vs Snyk Learn

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the secure code training page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
SecureFlagFirst choices, of fourteen modelsVeracode Security Labs
Direct401 against Veracode Security Labs
Paraphrase21
Comparative30
Budget-constrained002 against SecureFlag · 1 against Veracode Security Labs
Scale-constrained00
Negative201 against SecureFlag · 6 against Veracode Security Labs
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, SecureFlag and Veracode Security Labs were named in the same answer thirty-five times, of the 137 answers naming SecureFlag and the 69 naming Veracode Security Labs. In those answers Veracode Security Labs took the first choice one time and SecureFlag six.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where SecureFlag and Veracode Security Labs stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
SecureFlag Veracode Security Labs first choice named as an alternative argued againstblank: not namedEach cell is one answer, SecureFlag on the left and Veracode Security Labs on the right.

The direct prompt

The plain question, one answer per model, grouped by where SecureFlag and Veracode Security Labs stood in it.

SecureFlag first, Veracode Security Labs an alternative

4 of 14 modelsVeracode Security Labs was named in the answer but not as the choice, or not at all.
Perplexity SonarSecureFlag alternatives: Secure Code Warrior Learning Platform
Llama 4 MaverickSecureFlag alternatives: Avatao, ImmersiveLabs, KnowBe4, Secure Code Warrior Learning Platform, Veracode Security Labs
GLM 4.7 FlashXSecureFlag alternatives: AppSecEngineer, Secure Code Warrior Learning Platform, Security Journey
GPT-6 LunaSecureFlag alternatives: Secure Code Warrior Learning Platform, Security Journey

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Secure Code Warrior Learning Platform alternatives: AppSecEngineer, Avatao, SecureFlag
GPT-5.4 miniSecure Code Warrior Learning Platform alternatives: AppSec Education Platform, Avatao, SafeStack Academy, SecureFlag
Gemini 3.5 FlashSecure Code Warrior Learning Platform alternatives: AppSecEngineer, Checkmarx Codebashing, Kontra, SecureFlag, Security Journey
Grok 4.20Secure Code Warrior Learning Platform alternatives: SecureFlag, Security Journey, Snyk Learn
Mistral SmallSecure Code Warrior Learning Platform alternatives: SecureFlag, Security Journey
DeepSeek V4 FlashSecure Code Warrior Learning Platform alternatives: SecureFlag, Security Journey

Neither was named

4 of 14 modelsThe answer made no first choice from these two in this category.
Qwen 3.7 FlashSecure Code Warrior Learning Platform alternatives: Hack The Box Academy, Pluralsight
Kimi K2Secure Code Warrior Learning Platform alternatives: Avatao, Immersive Labs, Security Journey
MiniMax M2.5Secure Code Warrior Learning Platform alternatives: SafeStack Academy, Security Journey
Muse Glimmer 30BSecure Code Warrior Learning Platform alternatives: Checkmarx Codebashing, SafeStack Academy

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
SecureFlag leads by twenty-five points.
SecureFlag25%#1 of 11
Veracode Security Labs0%#9 of 11
The full small business standing →
Mid-marketThe figures above
SecureFlag leads by ten points.
SecureFlag12%#2 of 13
Veracode Security Labs2%#8 of 13
The full mid-market standing →
Enterprise
SecureFlag leads by thirteen points.
SecureFlag13%#2 of 7
Veracode Security Labs0%#6 of 7
The full enterprise standing →

What the models said about SecureFlag

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“Avoid premium platforms such as Secure Code Warrior or SecureFlag” Perplexity Sonar · budget prompt · hard negative
“competitors like Secure Code Warrior or SecureFlag (which often start in the $10k+ range)” Qwen 3.7 Flash · budget prompt · soft negative
“Labs may have issues when using a VPN, and initial setup can feel overly complex” Claude Haiku 4.5 · negative prompt · soft negative
“Choose SecureFlag if you need a comprehensive solution that covers AI security, provides auditor-ready reports, and mirrors real coding workflows.” Qwen 3.7 Flash · comparative prompt · first choice
“Choose SecureFlag if you want realistic hands-on remediation, stronger workflow realism, and AI-era secure coding/threat modeling.” GPT-5.4 mini · comparative prompt · first choice
“prioritize platforms that let developers work in actual IDEs with real code (like SecureFlag, which gets high marks for this approach)” Kimi K2 · negative prompt · first choice

What the models said about Veracode Security Labs

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“Paid enterprise platforms like Secure Code Warrior, Veracode Security Labs, or Immersive Labs are highly rated for depth and integration but often start at thousands of dollars annually” Grok 4.20 · budget prompt · soft negative
“Veracode Security Labs, Synopsys, and Checkmarx Codebashing, which are considered to be high-cost and high-friction” Llama 4 Maverick · negative prompt · soft negative
“they can feel more bolted-on than dedicated platforms like SCW, and pricing may be higher for mid-market” Grok 4.20 · direct prompt · soft negative
“SANS and Veracode are both excellent choices” Mistral Small · paraphrase prompt · first choice
“Best For: Teams already standardized on Veracode scanning who want training that aligns with their existing tooling.” GLM 4.7 FlashX · comparative prompt · alternative
“Best for: Existing Veracode customers wanting training that complements their scanning and remediation workflows.” DeepSeek V4 Flash · comparative prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.