Both platforms train developers to write secure code, and both include hands-on practice. What separates them is whether developers learn by working in real development environments, how much of the development lifecycle the platform covers, and how much of it is built to provide audit-ready compliance evidence.
If you want developers to fix real vulnerabilities in fully working development environments, in the languages and frameworks they actually use, with threat modeling at the design stage and proof of skill you can hand to an auditor, SecureFlag is the stronger choice as a Security Journey alternative. For most buyers, the decision comes down to three questions: how close the practice is to real development work, whether threat modeling is part of the platform, and whether your training evidence shows that developers can actually fix vulnerabilities.
Quick verdict
SecureFlag and Security Journey are both well-regarded secure coding training platforms that mix hands-on practice with structured learning. The difference is in what “hands-on” means and how far each platform reaches beyond training.
SecureFlag runs every lab on a real, fully virtualized computer in the browser. It launches a complete development environment in about 5 seconds, with the compilers, frameworks, and tooling your team actually uses. Developers fix live vulnerabilities in their own stack, and the platform runs the code to verify the fix. ThreatCanvas adds automated threat modeling at the design stage, hands-on AI and agentic coding labs with an embedded coding agent, and enterprise plans with a dedicated customer success manager.
Security Journey combines video lessons with in-browser coding exercises, Break/Fix sandboxes, coding challenges, and CTFs. It has also recently expanded into AI training for the wider workforce.
Choose SecureFlag if you want developers practicing in real development environments, threat modeling built into the platform, hands-on AI and agentic coding content, audit-ready evidence based on demonstrated skill, and a private cloud option.
Choose Security Journey if you prefer a video-led curriculum, where the lesson is the core and exercises follow, and ease of administration.
At-a-glance comparison
| SecureFlag | Security Journey | |
| Training environment | Real, fully virtualized development environments in the browser, with actual compilers, frameworks, and tooling; ready in about 5 seconds | Video lessons plus hands-on exercises in an in-browser code editor and application sandbox |
| Learn by fixing | Developers fix real code in running applications, and the platform runs it to verify the fix | Break/Fix lessons and coding challenges |
| Learning formats | Hands-on labs, learning paths by role, language, and level, hands-on assessments, tournaments | Video lessons, coding exercises, Break/Fix lessons, coding challenges, CTFs, tournaments |
| Agentic coding | Hands-on labs with an embedded AI coding agent: secure prompting and reviewing AI-generated code | AI/LLM lessons, AI-readiness assessment, and guidance on reviewing AI-written code |
| Securing AI in your apps | Hands-on labs: prompt injection, data leakage, RAG, MCP integrations, safe defaults | AI/LLM security lessons and a Break/Fix AI sandbox |
| Citizen developer AI training | Hands-on labs for non-technical staff building apps and automations with low-code and AI tools: spotting sensitive data exposure, keeping credentials safe, managing permissions, and knowing when a project needs IT or security review | Citizen Developers track in AI Advantage, plus a separate AI Access plan for citizen development |
| Threat modeling | Built in and automated at the design stage (ThreatCanvas); models generated in seconds. Hands-on threat modeling labs. | Covered as training content; no threat modeling tool |
| Security requirements and controls verification | Extending across the SDLC with StoryGuard [Availability: November 2026] | Not part of the platform |
| Language and technology coverage | 70+ technologies and frameworks; +1000 labs. | 45+ languages, technologies, and frameworks; 1,000+ lessons |
| Workflow integration | Jira, Azure Boards, GitHub, GitLab, and IDE plugins. | GitHub and GitLab integration; scanner findings mapped to training (Aspen). |
| Compliance and evidence | Mapping and exportable evidence for PCI DSS, ISO 27001, SOC 2, and OWASP ASVS; hands-on assessment; analysis of training coverage against real developer commits | Compliance learning paths (OWASP Top 10, PCI DSS 4.0, ISO 27001) and audit reporting |
| Customer success | Dedicated CSM on enterprise plans: adoption plan, training plans, tournaments, integration support, metrics | Dedicated CSM on Essentials plans and above |
| Deployment | SaaS, private cloud | SaaS |
| G2 rating | 4.8 / 5 | 4.6 / 5 |
| G2 quality of support | 9.7 | 9.3 |
| Gartner Peer Insights rating | 4.7 / 5 | 4.4 / 5 |
| Pricing | Per user per year (unlimited and credits options available) | Custom pricing for secure code training; some AI training plans sold online |
Real computers, not just a code editor
Both platforms say “hands-on,” so it’s worth being specific about what that means.
Security Journey’s hands-on lessons run in an in-browser editor connected to an application sandbox. In a Break/Fix lesson, a developer first exploits a vulnerability, then switches to the defender’s seat, edits the insecure code, and tests the fix.
A SecureFlag lab goes a step further. It’s a real, fully configured development environment on a virtualized computer, delivered in the browser and ready in about 5 seconds. It has the compilers, frameworks, package managers, build tools, and pipelines a developer would use at work, across 70+ technologies. Developers work in a proper IDE, change the code that causes the vulnerability, and the platform runs and tests that change.
That difference shows up the next day. When the lab looks and behaves like the environment developers ship from, the fix they practice is the fix they’ll write in their own pull request.
From understanding to fixing
There’s a complaint that comes up again and again from developers who’ve sat through security training: “they teach us what not to do, but never how to do it right.” Knowing SQL injection is bad doesn’t teach you how to parameterize a query in the framework you actually use.
Security Journey tackles this with a blend: video lessons explain the concept, then short coding exercises and Break/Fix lessons put it into practice. For teams that like a guided, lesson-first rhythm, that works.
SecureFlag uses the concept as a short on-ramp and makes the lab the main event. Learning paths introduce each vulnerability first, through a short video or knowledge base article. Then developers move into the lab, where most of the learning happens: fixing the vulnerability in a working development environment, in their own language and framework, from Java and Python to more specialized stacks. They finish with secure code they wrote themselves, verified by the platform.
Training plugs into the tools they already use (the IDE, Jira, Azure Boards, GitHub, and GitLab), so a finding can send a developer straight to the lab that teaches them to fix it. The goal isn’t awareness. It’s a better next pull request.
The most forward-looking content in the category
AI has changed what developers need to know, and both vendors are responding. Security Journey has added AI/LLM lessons, an AI-readiness assessment, and, in September 2026, AI Advantage, a separate product for AI skills across the whole workforce.
SecureFlag’s focus is making AI skills hands-on for the people who build software as well as citizen developers. It covers three tracks, all taught in real environments:
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Agentic coding. Developers now write code with AI assistants, so the skill is directing them safely and judging what comes back. Labs include an embedded AI coding agent, teach secure prompting as a security skill (specifying constraints, validation, and error handling), and then have developers review AI-generated code for the subtle flaws models produce.
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Securing the AI you ship. Teams are building AI into their products. Labs cover LLM risks, prompt injection, data leakage, retrieval-augmented generation, MCP integrations, and safe defaults.
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Citizen developers. Non-engineers are building apps and automations with low-code platforms and AI tools. Labs teach them to spot sensitive data exposure, keep credentials safe, manage permissions, and know when a project needs IT or security review.
The principle behind all three: it doesn’t matter whether a vulnerability was written by a developer or generated by a model. It still expands the attack surface, and a person is still accountable for it. Auditors don’t accept “the AI wrote it.”
Threat modeling, before the code exists
The cheapest vulnerability to fix is the one you design out before anyone writes it. This is where the two platforms differ most. Security Journey teaches threat modeling as part of its curriculum. It doesn’t include a threat modeling tool.
SecureFlag includes ThreatCanvas, built for developers rather than security specialists. It generates a complete threat model in seconds, for a single feature or an entire application, from a text description, an architecture or data flow diagram, infrastructure as code, or existing code. It identifies threats and matching controls using built-in compliance libraries or your organization’s own standards.
It runs through a GUI, APIs, CI/CD pipelines, native Jira and Azure DevOps integrations, or the SecureFlag MCP server, so that agents can call it too. Threat modeling becomes part of normal development work instead of a scheduled workshop. And every threat it identifies links to a matching hands-on lab, so design-time risks turn into skills that prevent them. That link between modeling and training isn’t something a training-only platform can offer.
Proving it to auditors
For regulated teams, training isn’t only about skill. It’s about evidence. As one practitioner put it, auditors “want to see receipts,” and frameworks like PCI DSS require documented secure development training.
Both platforms take this seriously. Security Journey offers compliance-focused learning paths for OWASP, PCI DSS 4.0, and ISO 27001, with reporting to match. SecureFlag maps training to the frameworks you report against, including PCI DSS, ISO 27001, SOC 2, and OWASP ASVS, and exports the evidence, so proof is a download, not a scramble. It can also analyze how well training covers the vulnerabilities showing up in your developers’ real commits.
The bigger difference is what the evidence proves. SecureFlag assessments are hands-on, in real environments, so a passed assessment shows a developer can fix the vulnerability, not just that they finished a module. That matters under PCI DSS 4.0.1, where Requirement 6.2.2 expects secure coding training that is relevant to each developer’s job function and the languages they use.
Organizations using SecureFlag’s secure coding program typically see (based on customer data):
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21% reduction in new vulnerabilities within the first 12 months.
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27% faster remediation of identified vulnerabilities.
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24% reduction in security rework.
Calculating ROI is straightforward. Compare the cost of the training program (including platform fees and the time developers spend in training) with the cost savings achieved through reduced vulnerabilities, faster remediation, and less security rework. The greater the improvements in these areas, the higher the return on investment.
A partner, not just a platform
Buying a training platform is the easy part. Getting developers to use it, and proving it worked, is where programs quietly stall.
Security Journey includes a dedicated customer success manager on its Essentials plans and above. SecureFlag does the same for every enterprise customer, with a CSM who gets to know your stack, your compliance obligations, and how your teams use AI, then builds an adoption plan around your goals. From onboarding and goal setting through custom learning paths, tournaments, tool integration, and reporting, SecureFlag runs the program with you rather than handing over a license and a login.
Reviewers notice. On G2, SecureFlag scores 9.7 for quality of support, against 9.3 for Security Journey, and support is one of the things SecureFlag reviewers mention most.
How training fits with SAST, DAST, and SCA
Scanners find problems. Training stops them coming back. Most teams running SAST, DAST, or SCA still see the same vulnerability classes recur because scanners flag issues without teaching anyone why they happened or how to prevent them. Some classes, like business logic flaws, slip past scanners entirely.
Both platforms connect to scanner findings to target training. SecureFlag sits alongside your scanners rather than replacing them: the scanner catches an issue, the developer practices fixing that vulnerability class in a real environment, and fewer instances reach the scanner next time.
When to choose SecureFlag
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Security leadership that needs to raise developer competency, cut repeat vulnerabilities, and reduce rework, with evidence to show for it.
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Engineering leadership that wants practice in real development environments and threat modeling in the workflow, without slowing delivery.
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Teams adopting AI-assisted development that need developers and non-technical staff to steer AI toward secure code and judge what it produces.
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Compliance and GRC teams that need audit-ready proof, based on demonstrated skill, mapped to the frameworks they report against.
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Regulated organizations that need a private cloud deployment rather than a shared SaaS platform.
It fits teams of any size, from a single squad to an enterprise rollout across many development teams.
When Security Journey is the better fit
Security Journey’s video-led format, with the lesson as the core and exercises that follow, suits teams that want a guided, lesson-first curriculum, and reviewers rate it highly for ease of administration. It’s also worth a look if you need general AI literacy or EU AI Act awareness training for staff across the business.
If that sounds like your team, it’s worth evaluating. If real development environments, design-stage threat modeling, hands-on AI content, and skill-based audit evidence matter more, SecureFlag is the stronger fit.
What customers say
SecureFlag holds a 4.8 out of 5 on G2, the highest of the platforms most often compared in this category, with Security Journey at 4.6. Reviewers point to the hands-on approach and the support team. One IT security specialist summed it up as “easy to use, extremely interactive labs, high level of technical details, great customer support.” An information security analyst wrote: “They’re more than just vendors; I feel like they work with us and not for us.”
“Unlike traditional secure SDLC presentations, [SecureFlag] offers hands-on, practical training that keeps developers engaged with real-world threats. […] It’s a far more effective way to build a security-first culture, and we’ve seen the results firsthand.”
FAQ
What is the difference between SecureFlag and Security Journey?
Both offer hands-on secure coding training. SecureFlag runs every lab in a real, virtualized development environment and verifies fixes by running the code, and it adds automated threat modeling (ThreatCanvas), hands-on AI and agentic coding labs, and skill-based audit evidence. Security Journey blends video lessons with in-browser exercises, Break/Fix sandboxes, and CTFs in role-based learning paths. The main trade-off is depth of hands-on practice and lifecycle coverage versus a video-led curriculum with exercises attached.
Is SecureFlag a good alternative to Security Journey?
Yes, particularly if you want developers practicing in real development environments, threat modeling built into the platform, and evidence you can take to an audit. SecureFlag is rated 4.8 out of 5 on G2.
Are SecureFlag labs simulations?
No. Labs run in real, fully virtualized development environments with actual compilers, frameworks, and tooling, ready in seconds in the browser. Developers fix live vulnerabilities in their own stack, and the platform runs the code to verify the fix.
Does Security Journey include threat modeling?
Security Journey teaches threat modeling as training content but doesn’t include a threat modeling tool. SecureFlag provides ThreatCanvas, which generates threat models automatically at the design stage and links each threat to a matching lab.
Does SecureFlag cover AI and agentic development?
Yes. SecureFlag has hands-on labs with an embedded AI coding agent for secure prompting and reviewing AI-generated code, plus separate labs on securing the AI you build into your products: LLM risks, prompt injection, data leakage, RAG, and MCP integrations.
Which is better for compliance and audits?
Both support compliance. SecureFlag maps training to PCI DSS, ISO 27001, SOC 2, and OWASP ASVS, exports audit evidence, and assesses developers hands-on, so the evidence shows demonstrated skill rather than course completion.
Can SecureFlag be deployed in a private cloud?
Yes. SecureFlag is available as SaaS or private cloud. Security Journey is offered as SaaS.
How much do SecureFlag and Security Journey cost?
SecureFlag is priced per user per year, with unlimited and credits-based options. Security Journey’s secure code training is custom priced. Both are quoted on request.
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