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

Escape vs Probely

Zero of fourteen models named Escape first on the direct prompt; one named Probely. Escape was named by nine of the fourteen models and Probely by six and Escape carries 11 labels and Probely 10, so the shares are not directly comparable.

Escape

accepted challenger

Named in two categories this edition.

Probely

accepted challenger

Named in two categories this edition.

First-choice share2%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 13; printed, not drawn.
Labels1110A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Escape 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 Escape · Invicti vs Probely · OWASP ZAP vs Escape

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.
EscapeFirst choices, of fourteen modelsProbely
Direct01
Paraphrase00
Comparative10
Budget-constrained00
Scale-constrained10
Negative00
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 Escape 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
Escape Probely first choice named as an alternative argued againstblank: not namedEach cell is one answer, Escape on the left and Probely on the right.

The direct prompt

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

Probely first, Escape not the choice

1 of 14 modelsEscape 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

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashStackHawk alternatives: Acunetix, Bright Security, Escape, Invicti
Perplexity SonarInvicti alternatives: Bright Security, Escape, StackHawk
Grok 4.20Invicti alternatives: Escape, Intruder, Probely, StackHawk

Neither was named

10 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Invicti alternatives: Acunetix, Bright Security, StackHawk
GPT-5.4 miniStackHawk alternatives: Burp Suite, Invicti
Mistral SmallAcunetix, Invicti alternatives: OWASP ZAP, StackHawk
DeepSeek V4 FlashAcunetix alternatives: Invicti, OWASP ZAP, StackHawk
Llama 4 MaverickInvicti alternatives: Burp Suite, OWASP ZAP, StackHawk
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
GPT-6 LunaStackHawk alternatives: Burp Suite DAST, Invicti
Muse Glimmer 30BInvicti alternatives: Acunetix, StackHawk

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
Probely leads by two points.
Probely4%#5 of 13
Escape2%#– of 13
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Escape2%#6 of 13
Probely2%#7 of 13
The full mid-market standing →
Enterprise
The order flips: Escape leads at enterprise.
Escape2%#11 of 14
Probely0%#– of 14
The full enterprise standing →

What the models said about Escape

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

“Escape is considered the strongest DAST tool for modern AppSec teams working with APIs and SPAs” Llama 4 Maverick · comparative prompt · first choice
“Modern mid-market / DevSecOps native | StackHawk, Escape, Bright (NeuraLegion)” Kimi K2 · scale prompt · first choice
“consider Bright Security or Escape for similar developer-first or API-focused workflows” Perplexity Sonar · comparative prompt · alternative

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
Invicti vs EscapeInvicti vs ProbelyOWASP ZAP vs EscapeOWASP ZAP vs ProbelyAcunetix vs EscapeAcunetix vs ProbelyStackHawk vs EscapeStackHawk vs ProbelyBright Security vs EscapeBright Security vs ProbelyEscape vs Veracode DASTProbely vs Veracode DASTAll twenty-eight head-to-head pages and the full DAST standing

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.