DDactic.net VS DevGhost.pro

DDactic.net's answer

DDactic is the only platform that combines automated attack-surface discovery with multi-vector L3-L7 attack simulation from a fleet across 23+ cloud providers, and validates the customer's protection vendor configuration with stage-reprobe after each hardening change.

The Open Protection Index (OPI), Apache 2.0, gives customers a vendor-neutral 0-100 score they can benchmark over time. Most DDoS testing services run a single-vendor appointment-based simulation; DDactic runs continuous, multi-vendor, attacker-perspective testing.

DevGhost.pro's answer:

DevGhost estimates the substantive work behind Git changes using a consistent reference: a mid-level developer who knows the codebase and works without AI. This makes contributions comparable beyond commit counts and lines of code. Teams can explore individual output, repository-wide trends, and changes in productivity as development workflows evolve. DevGhost also offers fully local analysis: both code processing and analytics run on your machine, with source code and results staying local.

DDactic.net's answer

Three reasons:

1. Real bot-detection bypass research, with 25 vendor fingerprints catalogued (PerimeterX, DataDome, Akamai BotManager, Cloudflare Challenge, etc.), so attacks are not blocked by trivial defenses and customers see what their CDN/WAF actually allows through.

2. Protection-group-aware testing that maps which subdomains share fate with which origin, exposing the shared-fate risk that most teams miss because they only think about their flagship asset.

3. Vendor-specific hardening playbooks (Cloudflare, AWS Shield, Imperva, Akamai, Radware) validated by stage-reprobe after the customer applies them, not generic recommendations from a paper questionnaire.

DevGhost.pro's answer:

Choose DevGhost when you need to understand the work delivered by a development team or contractor and compare contributions on a shared scale. It combines effort estimates, developer breakdowns, and productivity timelines in an interactive report. This helps founders and engineering leaders connect progress discussions to actual code changes. With cloud, local, and on-premises options, you can choose a deployment model that fits your workflow and confidentiality requirements.

DDactic.net's answer

Security teams at companies that already pay for CDN/WAF protection (Cloudflare, Akamai, Imperva, AWS Shield, Radware) but have never validated whether the protection actually covers their full attack surface.

Typical buyer: CISO or VP of Security at mid- to large-sized enterprises in finance, gaming, e-commerce, healthcare, and government. Secondary audience: blue-team engineers and SRE teams running incident-response drills who need a controlled way to exercise their playbooks.

DevGhost.pro's answer:

DevGhost is built for founders, CTOs, engineering managers, and product owners who need visibility into software development. It is especially useful for organizations working with outsourced development teams, agencies, or freelancers, and for leaders trying to understand how AI-assisted development is changing their team's output.

DDactic.net's answer

After 4 years in DDoS engineering, I (Stav David) noticed the same gap in every customer engagement: enterprises pay six- and seven-figure sums for DDoS protection (Cloudflare Magic Transit, Akamai Prolexic, Imperva, AWS Shield Advanced, Radware DefensePro) and almost nobody actually tests whether the protection holds.

The industry-standard alternative is a vendor-led "DDoS test" delivered as an appointment: 4 hours, scheduled weeks ahead, run from a single ASN against the production target. That misses the entire L7 surface, does not probe IP rotation, and gives no per-vector data.

DDactic was built to fix that, with continuous distributed simulation across 23+ cloud providers, per-vector attribution, and stage-reprobe validation after every hardening change. Founded in 2026, based in Tel Aviv.

DevGhost.pro's answer:

DevGhost is built around a simple question: how much substantive work is actually being delivered? Busy teams, frequent commits, and detailed status reports do not always make that clear. AI-assisted development makes the question even more important, as one developer's output can change dramatically. DevGhost brings code changes onto a common reference scale so founders and engineering leaders can see contributions, follow trends, and have more concrete conversations about delivery.

DDactic.net's answer

Python/Flask backend on Dedibox bare-metal, TypeScript frontend on Cloudflare Pages, Go-based bot fleet orchestration across 23+ cloud providers, raw-socket + uTLS attack emitters for fingerprint-faithful testing, AWS Batch for ephemeral scan workers.

DevGhost.pro's answer:

DevGhost is built with TypeScript, React, Next.js, and Node.js. Its Python analysis engine uses Git, Tree-sitter, NumPy, and scikit-learn to process and analyze code changes. The web platform uses PostgreSQL with Prisma, while the local edition uses SQLite. The VS Code and Cursor extension combines TypeScript with React-based webviews. The Windows desktop application is built with Electron and shares the local analysis engine. Cloud and on-premises deployment options are supported through Modal and Docker-based infrastructure.

DevGhost.pro's answer:

We do not publish customer names. Engineering productivity and team contribution data can be sensitive, particularly when it involves individual developers or external contractors. We respect the confidentiality of these assessments and the reputations of the people and organizations involved.