Index › IT › Developer platform › DAST › StackHawk vs Probely
Dynamic application security testing · November 2026 Edition

StackHawk vs Probely

Three of fourteen models named StackHawk first on the direct prompt; one named Probely. StackHawk was named by fourteen of the fourteen models and Probely by six and StackHawk carries 41 labels and Probely 10, so the shares are not directly comparable.

StackHawk

accepted challenger

Named in three categories this edition.

Probely

accepted challenger

Named in two categories this edition.

First-choice share11%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate2%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 13; printed, not drawn.
Labels4110A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, StackHawk reading right to left. Rank and label count are printed, not drawn.Invicti was named alongside these two in twelve of the fourteen direct answers. Invicti vs StackHawk · Invicti vs Probely · OWASP ZAP vs StackHawk

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 dynamic application security testing page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
StackHawkFirst choices, of fourteen modelsProbely
Direct31
Paraphrase20
Comparative00
Budget-constrained00
Scale-constrained10
Negative001 against StackHawk
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.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where StackHawk and Probely 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
StackHawk Probely first choice named as an alternative argued againstblank: not namedEach cell is one answer, StackHawk on the left and Probely on the right.

The direct prompt

The plain question, one answer per model, grouped by where StackHawk and Probely stood in it.

StackHawk first, Probely not the choice

3 of 14 modelsProbely was named in the answer but not as the choice, or not at all.
GPT-5.4 miniStackHawk alternatives: Burp Suite, Invicti
Gemini 3.5 FlashStackHawk alternatives: Acunetix, Bright Security, Escape, Invicti
GPT-6 LunaStackHawk alternatives: Burp Suite DAST, Invicti

Probely first, StackHawk an alternative

1 of 14 modelsStackHawk was named in the answer but not as the choice, or not at all.
GLM 4.7 FlashXOWASP ZAP, Probely alternatives: Burp Suite, Invicti, StackHawk

Neither was the first choice, one was named

7 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Invicti alternatives: Acunetix, Bright Security, StackHawk
Perplexity SonarInvicti alternatives: Bright Security, Escape, StackHawk
Grok 4.20Invicti alternatives: Escape, Intruder, Probely, StackHawk
Mistral SmallAcunetix, Invicti alternatives: OWASP ZAP, StackHawk
DeepSeek V4 FlashAcunetix alternatives: Invicti, OWASP ZAP, StackHawk
Llama 4 MaverickInvicti alternatives: Burp Suite, OWASP ZAP, StackHawk
Muse Glimmer 30BInvicti alternatives: Acunetix, StackHawk

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Qwen 3.7 FlashInvicti alternatives: Acunetix, Apidog, Postman, Veracode DAST
Kimi K2Acunetix, Intruder alternatives: Bright Security, Detectify
MiniMax M2.5Acunetix, Bright Security alternatives: Detectify, Intruder

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
StackHawk leads by nine points.
StackHawk13%#3 of 13
Probely4%#5 of 13
The full small business standing →
Mid-marketThe figures above
StackHawk leads by nine points.
StackHawk11%#4 of 13
Probely2%#7 of 13
The full mid-market standing →
Enterprise
Level: the same share of first choices.
StackHawk0%#12 of 14
Probely0%#– of 14
The full enterprise standing →

What the models said about StackHawk

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

“its own docs acknowledge that scan results can include false positives, so findings still need review and confirmation” GPT-5.4 mini · negative prompt · soft negative
“Modern mid-market / DevSecOps native | StackHawk, Escape, Bright (NeuraLegion)” Kimi K2 · scale prompt · first choice
“the best DAST tool is usually StackHawk if your team is developer-driven” GPT-5.4 mini · direct prompt · first choice
“StackHawk — Best for Developer-Centric & Modern API-First B2B SaaS” Gemini 3.5 Flash · paraphrase prompt · first choice

What the models said about Probely

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

“Best Overall Value: Probely ... My top recommendation: Start with a trial of Probely or OWASP ZAP” GLM 4.7 FlashX · direct prompt · first choice
“Top-Rated Options (from 2023–2025 reviews): Probely, StackHawk, Rapid7 InsightAppSec” Grok 4.20 · negative prompt · alternative
“StackHawk or Probely — Developer-friendly, strong CI/CD focus.” Grok 4.20 · scale 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.