DEV Community: Alex Vakulov

Best Virtual Data Rooms for Enterprise Security: SSO, MFA, ISO, and SOC Readiness

Alex Vakulov — Wed, 20 May 2026 11:35:46 +0000

Think about how much sensitive information flows through your company every day. How quickly could it be exposed if security breaks down? Even world-known brands like Yahoo and Uber have faced costly breaches. That’s why strong protection for corporate data is critical.

In this article, we show you how the best virtual data rooms can protect information. In addition, we help you choose the best solution for your needs.

What is VDR?

A virtual data room (VDR) is a secure platform where companies store and exchange sensitive documents. Unlike generic file-sharing solutions, this tool offers stronger security. In particular, it protects sensitive documents with encryption, detailed access controls, and activity tracking.

In addition, datarooms simplify daily workflows and complex deals. For example, they feature collaboration, automated reporting, and workflow management tools.

Why Single Sign-On, Multi-Factor Authentication, ISO, and SOC Matter

The following four elements play a critical role in protecting sensitive data and meeting internal security expectations.

Feature	How it works	Why it matters
Single sign-on	Users access the data room through their corporate identity system, with access managed centrally by IT.	Reduces password-related risk and allows instant access removal when employees leave the company.
Multi-factor authentication	Requires an additional verification step during login, such as a code.	Prevents unauthorised data room access.
ISO certifications	Confirms the provider follows recognised information security practices and documented processes.	Demonstrates structured risk management, data protection, and incident response.
SOC readiness	Shows that security controls are documented and monitored.	Ensures that security processes withstand regulatory scrutiny.

These controls reduce access risks, support compliance requirements, and ensure sensitive documentation stays protected.

Best Virtual Data Room Providers for Enterprise Security

In this section, you can see which platforms offer the strongest security for sensitive business data. For each provider, we break down the following aspects:

Overall security and user rating
Core security features (SSO, MFA, ISO, SOC)
Latest user feedback on the solution
Advanced features beyond security

1. Ideals

Ideals provides a secure virtual data room for managing high-stakes transactions. The platform is used across various industries, including financial services, M&A (sell-side and buy-side), fundraising, life sciences, and real estate. Trusted by over two million professionals worldwide, the company has been independently rated on G2 as the best product and service for four consecutive years.

Security Requirement	Availability
Single sign-on	Yes
Multi-factor authentication	Yes
ISO certifications	Yes (ISO/IEC 27001, 27017, 27701)
SOC compliance	Yes (SOC 2 Type II, SOC 3)

Other Ideals Security Features:

Global data residency options
Multi-layered data encryption
Granular permission settings (8 levels)
Session timeout controls
Domain and IP address restrictions
User security impersonation
Fence View for screenshot prevention
Remote wipe and shred
Intelligent redaction
GDPR and HIPAA compliance

👁️‍🗨️ What do users say about Ideals security?

Strong security controls

Bank-grade encryption, dynamic watermarks, and fence view contribute to a high level of protection for sensitive documents.

Granular and flexible access management

Permissions can be configured at a detailed level, with security groups that make it easy to add, remove, or adjust access.

Reliable support for M&A workflows

The data rooms combine security and efficiency in a way that supports the smooth execution of complex M&A processes.

Other Ideals Advanced Features:

Intuitive interface
Custom branding
Due diligence checklist
Document versioning
E-signature
In-depth Q&A settings
24/7 50+ language support
30-second support chat response

Free trial: ✅

2. Firmex

Firmex offers secure data room services for file sharing and collaboration. The platform supports 20,000 new projects annually across 180+ countries. It is used for mergers and acquisitions, licensing and joint ventures, financing, and restructuring.

Security Requirement	Availability
Single sign-on	Yes
Multi-factor authentication	Yes
ISO certifications	Infrastructure-level (AWS data centres)
SOC compliance	Yes (SOC 2 Type II)

Other Firmex Security Features:

IP-based access restriction
Advanced password control
Customizable document permissions
Document lockdown
Remote document revocation
Document expiry
Redaction
GDPR and HIPAA compliance

👁️‍🗨️ What do users say about Firmex security?

Strong cloud-based protection

Advanced encryption and access control provide robust security, combined with an intuitive interface.

Detailed permission management

Highly granular permissions allow precise configuration for internal teams and external partners during due diligence projects.

Limited pre-entry security features

Few security controls are available before entering the data room.

Other Firmex Advanced Features:

Instant data room setup
Detailed reports
View As
Email In
Project copy functionality
Support in English, French, German, and Spanish

Free trial: ✅

3. Datasite

Datasite is a virtual data room designed to support due diligence and deal execution. The platform uses machine-learning models trained on a large corpus of transaction documents to streamline review and preparation processes. Thus, the dataroom helps organizations manage operations more efficiently.

Security Requirement	Availability
Single sign-on	Yes
Multi-factor authentication	Yes
ISO certifications	Yes
SOC compliance	Yes (SOC 2 Type II)

Other Datasite Security Features:

Data encryption in transit and at rest
Project file purging (30 days post-completion)
Separate storage for user and app data
Platform hosting on Microsoft Azure
WAF and DDoS protection (Cloudflare)
AMERS, EMEA, and APAC data residency
Regular code scans
EU and UK GDPR, CPRA, and APP compliance

👁️‍🗨️ What do users say about Datasite security?

Advanced protection for sensitive documents

Top-tier encryption, granular permission controls, and detailed audit logs provide confidence in data security.

Efficiency and workflow support

A secure environment enables faster review cycles, smoother workflows, and improved coordination and visibility.

Mandatory password renewal

Regular password updates are required, which some users find inconvenient.

Other Datasite Advanced Features:

Due diligence tracker
5-minute report scheduling
AI-assisted redaction
Integrated Q&A
Home page personalisation
24/7 support in 20 languages

Free trial: ✖️

4. Box

Box is an AI-powered platform for document management. It applies strict security and compliance controls across content and workflows. The platform is used by organizations across many industries, including financial services, education, and government.

Security Requirement	Availability
Single sign-on	Yes
Multi-factor authentication	Yes
ISO certifications	Yes
SOC compliance	Yes (SOC 2 Type II)

Other Box Security Features:

Zero-trust security controls
Intelligent data leak prevention
IP allow-list
Customer-managed keys
Shared link expiration
Classification-based access controls
Multi-layered malware scanning
GDPR and HIPAA compliance

👁️‍🗨️ What do users say about Box security?

Email-based access with multi-factor authentication

Integration with company email accounts and MFA strengthens access security and increases confidence in file storage and sharing.

Enterprise-grade security

Box data protection measures and compliance enable safe external collaboration across Microsoft 365, Google Workspace, and Salesforce.

Complex advanced security configuration

Advanced features such as permissions and governance controls can be complex and may require administrator support.

Other Box Advanced Features:

AI-guided data storage
120 file types preview
Folder templates
E-signatures
1,400+ partner integrations, including Salesforce and O365
24/7 support assistance

Free trial: ✅

5. Ansarada

The solution provides secure data room software for managing critical projects such as M&A, capital raising, restructures, and infrastructure procurement. It combines simplicity and power to reduce transaction timelines and costs. Trusted by dealmakers in 180 countries, Ansarada helps achieve stronger outcomes and optimal transaction value.

Security Requirement	Availability
Single sign-on	Yes
Multi-factor authentication	Yes
ISO certifications	Yes
SOC compliance	Infrastructure-level (AWS data centres)

Other Ansarada Security Features:

Real-time activity monitoring
Compliance-ready audit trails
Time-stamped activity logs
Remote self-destruct
Full audit trails
Permission-based file sharing
Secure viewer modes
GDPR compliance

👁️‍🗨️ What do users say about Ansarada security?

Strong security and compliance

Ansarada provides strong security, including the ability to self-destruct files, and meets relevant compliance standards.

Native document protection

The platform offers native document security features, eliminating the need for third-party software.

Complex security settings

Some security configurations can be difficult to navigate and would benefit from more in-context guidance within the menus and forms.

Other Ansarada Advanced Features:

AI predictive analytics
Centralised task management
AI bulk redaction
Data gauge
Automated Q&A
Expert 24/7 technical support

Free trial: ✅

Pricing and support comparison

When selecting a solution, security isn’t the only deciding factor. Virtual data room price comparison and the quality of support can also impact your experience, especially during active deals.

The table below summarises pricing models and support coverage for the online data room providers featured in this guide.

Feature / Metric	Ideals	Firmex	Datasite	Box	Ansarada
Value for money (according to Capterra)	4.5	4.7	4.2	4.3	4.2
Customer service (according to Capterra)	4.8	4.9	4.7	4.2	4.7
Transparent usage-based pricing	✔️	✖️	✖️	✖️	✖️
25-second phone support	✔️	✖️	✖️	✖️	✖️
30-second chat response	✔️	✖️	✖️	✖️	✖️
In-app 24/7 support	✔️	✖️	✖️	✖️	✔️
Dedicated project manager	✔️	✔️	✔️	✖️	✖️

Contact data room vendors through their official websites if you need more details or have deal-specific requirements.

🔊 Additional questions to ask VDR providers

1. How do you handle product updates during active deals?

(Will changes disrupt workflows or require retraining?)

2. What internal access controls do your own employees have to client data?

(Who at the provider level can see or access our documents?)

3. How do you perform incident response and breach notification?

(What are the timelines and communication protocols if something goes wrong?)

4. What is your historical uptime, and how is it measured?

(Is uptime independently monitored or contractually guaranteed?)

5. How do you support cross-border transactions and multilingual deal teams?

(Beyond UI language, are legal, time zone, and regional needs considered?)

6. What limitations exist that are not advertised in the product documentation?

(File size caps, throttling, session limits, or fair-use policies.)

7. How customizable are permission structures in real-world scenarios?

(Can permissions adapt to complex deal stages without workarounds?)

8. What happens if we need to switch providers mid-transaction?

(Data portability, timelines, and operational risks.)

9. How do you validate and audit your own security controls internally?

(Third-party audits, internal testing frequency, and accountability.)

10. What types of clients typically outgrow your platform and why?

(A revealing question about scalability and long-term fit.)

Verdict

Ideals, Firmex, Datasite, Box, and Ansarada virtual data room providers deliver robust solutions in terms of data security. At the same time, they may differ in features and user experience.

1. Ideals delivers top‑tier security and advanced features, with highly granular permissions, strong encryption, and fast 24/7 in‑app support.

When to choose? If your priority is enterprise‑grade protection and ease of use for complex, high‑stakes transactions. Ideal for organisations that need strong security controls coupled with responsive support.

2. Firmex provides reliable security, detailed permission management, and intuitive access controls. It supports a large volume of projects and strong everyday security coverage.

When to choose? If you run many projects and need consistent, dependable protection at scale with solid basics and straightforward administration.

3. Datasite pairs robust security with AI‑assisted tools and dedicated project support, helping enterprises move through due diligence efficiently.

When to choose? If you require deal‑centric automation and structured review workflows alongside strong protections.

4. Box offers enterprise‑grade security with content controls and broad integrations into existing business apps.

When to choose? If your use case goes beyond traditional VDR to secure content management across the business with collaboration and AI enhancements.

5. Ansarada delivers powerful document protection features such as remote self‑destruct and compliance‑ready audit trails.

When to choose? If you need straightforward, reliable security with global project visibility and easy sharing for high‑stakes deals.

Best Snyk Alternatives in 2026: Which AppSec Tool Should You Choose?

Alex Vakulov — Wed, 06 May 2026 11:47:49 +0000

Snyk is still one of the best-known developer security platforms, but it is no longer the only strong option for teams that need SAST, SCA, container security, IaC scanning, secrets detection, DAST, and cloud security coverage.

The best Snyk alternative depends on what your team is trying to fix: noisy findings, pricing complexity, missing coverage, open source governance, GitHub native workflows, or enterprise compliance.

For many small and mid-sized engineering teams, the best overall Snyk alternative is Aikido Security. It brings code, cloud, and runtime security into one central platform, with coverage across areas such as SAST, SCA, DAST, secrets, IaC, containers, cloud configuration, and runtime protection.

Other strong Snyk alternatives include Opengrep, Mend.io, Checkmarx One, GitHub Advanced Security, and Veracode. Each is better suited to a different AppSec model, so the right choice is not always the biggest platform. It is the one that fits how your developers actually build, review, deploy, and fix software.

Best Snyk Alternatives: Quick Comparison

Rank	Tool	Best for	Why teams choose it
1	Aikido Security	Best overall Snyk alternative	Broad AppSec coverage in one developer-friendly platform
2	Opengrep	Open source SAST and custom rules	Open source static analysis, portable rules, JSON, and SARIF output
3	Mend.io	Open source governance	Strong SCA, license management, SAST, and container security
4	Checkmarx One	Large enterprise AppSec programs	Broad testing coverage, risk correlation, and centralized governance
5	GitHub Advanced Security	GitHub native teams	Code scanning, secret protection, dependency review, and Dependabot workflows
6	Veracode	Compliance-driven enterprises	Mature SAST, DAST, SCA, governance, and compliance reporting

What Makes a Good Snyk Alternative?

A good Snyk alternative should not simply scan code and list vulnerabilities. That is only the starting point. Modern AppSec teams need tools that help developers fix real risks without drowning them in low-value alerts.

The most important evaluation criteria are:

Coverage: SAST, SCA, secrets, containers, IaC, DAST, API security, cloud security, and runtime risk.
Developer workflow: pull request comments, IDE support, CI/CD integration, ticketing, ownership, and clear fix guidance.
Prioritization: fewer false positives, reachability context, exploitability signals, and business-relevant severity.
Remediation: actionable fixes, automated pull requests, upgrade guidance, or AI-assisted repair.
Governance: policies, reporting, audit trails, license controls, and visibility across repositories.
Operational simplicity: fewer dashboards, fewer disconnected scanners, and less manual triage.

Snyk itself covers several important areas, including code, open source dependencies, containers, and cloud or IaC configurations, according to its current documentation. That means a replacement needs to be judged against a serious baseline, not against an outdated version of Snyk.

Aikido Security: Best Overall Snyk Alternative

Aikido Security is the strongest first option for teams that want broad application security coverage without managing a stack of separate tools. Its main value is consolidation. Instead of treating SAST, SCA, DAST, secrets, IaC, cloud, containers, and runtime protection as separate buying decisions, Aikido puts them into one platform.

That matters because many AppSec programs fail for operational reasons, not because teams lack scanners. Developers get too many alerts, security teams struggle to define ownership, and remediation becomes a backlog management problem. A tool that reduces workflow friction can be more valuable than another scanner with a long feature list.

Aikido is especially strong for startups, scaleups, and mid-sized engineering teams that need serious security coverage but do not want an AppSec process that feels heavier than the development process itself. Its SAST and DAST pages describe static code testing before runtime and dynamic testing against running applications, while its broader platform positioning covers code, cloud, and runtime security.

Why choose Aikido over Snyk?

Choose Aikido if you want:

One platform for several AppSec categories.
A simpler developer experience.
Less operational overhead.
Better visibility across code, cloud, and runtime risk.
A practical alternative to buying separate SAST, SCA, DAST, IaC, container, and cloud security tools.

Where Aikido fits best

Aikido is a strong fit when your team wants to move beyond “we scan repositories” and toward “we understand application risk.” That difference matters. Repository scanning is useful, but modern software risk also comes from secrets, exposed APIs, weak cloud configuration, container images, dependency chains, and runtime behavior.

Possible limitation

Aikido is newer than some legacy enterprise AppSec platforms. Very large organizations with deeply formal AppSec programs may still compare it against Checkmarx One, Veracode, or Mend.io for reporting, procurement, and compliance fit.

Verdict

Choose Aikido if you want the best overall Snyk alternative for broad AppSec coverage, simpler developer workflows, and less tool sprawl.

Opengrep: Best Snyk Alternative for Open Source SAST and Custom Rules

Opengrep is a strong choice for teams that want open source static analysis and control over code security rules. It is not a broad AppSec platform in the same sense as Aikido, Checkmarx One, or Veracode. Its strength is narrower and more technical: scanning source code with portable rules that can be adapted to a team’s own frameworks, coding patterns, and security requirements.

That makes Opengrep especially useful when generic vulnerability scanners miss risks that are specific to the organization. A team may want to detect unsafe use of an internal authentication helper, dangerous logging of sensitive data, insecure tenant isolation logic, or direct calls to sensitive internal services. These are not always standard CVEs. They are code patterns that need to be expressed as rules.

Opengrep also fits teams that want static analysis results in common engineering formats. Its GitHub documentation describes support for JSON and SARIF output, which makes it easier to integrate findings into CI pipelines, code scanning workflows, and security reporting systems.

Why choose Opengrep over Snyk?

Choose Opengrep if you want:

Open source SAST.
Custom code security rules.
Static analysis that can be embedded into CI workflows.
JSON and SARIF output for integration with developer tools.
A good fit for security engineers who want control over detection logic.

Where Opengrep fits best

Opengrep works best in teams with AppSec maturity. If your team has security engineers who can write, review, and tune rules, it can become a practical way to detect organization-specific risks that broader scanners may not understand.

It is also a good fit when the team wants more transparency and portability in static analysis. Instead of relying only on a commercial platform’s built-in checks, engineers can maintain rules that reflect how their own software is built.

Possible limitation

Opengrep is a SAST engine, not a complete Snyk replacement by itself. It does not replace the need for SCA, DAST, secrets detection, container scanning, cloud security, runtime protection, governance, or license compliance. Teams that need broad AppSec coverage in one platform should evaluate Aikido first.

Verdict

Choose Opengrep if open source SAST, custom code rules, and control over detection logic matter more than full AppSec platform consolidation.

Mend.io: Best Snyk Alternative for Open Source Governance

Mend.io is a strong Snyk alternative for teams that care about open source dependency risk, license compliance, policy management, and centralized security reporting. Mend’s current platform documentation describes SAST, SCA, and container image scans, along with centralized policy, license, and reporting workflows.

This makes Mend.io especially relevant for organizations where open source risk is not only an engineering issue. Legal, compliance, procurement, and security teams may all need visibility into dependency usage, license exposure, and remediation status.

Mend also provides legal and compliance workflows for identifying licensing risk across applications and projects, which is important for organizations that need more than CVE matching.

Why choose Mend.io over Snyk?

Choose Mend.io if you want:

Strong SCA capabilities.
License compliance workflows.
Centralized policy management.
Container image security.
Reporting across many applications and projects.

Where Mend.io fits best

Mend.io is best for organizations that treat dependency security as part of a larger governance model. That includes companies with many repositories, strict legal review, regulated customers, or internal policies around allowed licenses and package usage.

Possible limitation

Mend.io can feel more enterprise-oriented than tools built primarily for smaller developer teams. If the main problem is developer workflow simplicity, Aikido may feel lighter.

Verdict

Choose Mend.io if open source governance, dependency risk, and license compliance are central to your AppSec program.

Checkmarx One: Best Snyk Alternative for Enterprise AppSec

Checkmarx One is a strong option for large organizations that need a broad application security platform with centralized risk visibility. Checkmarx describes its platform as bringing together findings across SAST, SCA, DAST, container security, IaC, and CNAPP so teams can prioritize and remediate faster.

That breadth matters in enterprise environments. A large company may have hundreds or thousands of applications across different languages, deployment models, and business units. In that environment, AppSec is not only about scanning code. It is about policy, ownership, reporting, exceptions, risk acceptance, remediation SLAs, and executive visibility.

Checkmarx also has dedicated pages for IaC security, DAST, and container security, which support its positioning as a broad AppSec platform rather than a single category tool.

Why choose Checkmarx One over Snyk?

Choose Checkmarx One if you want:

Enterprise application security coverage.
Centralized risk correlation.
SAST, SCA, DAST, IaC, container, and cloud security coverage.
Governance and reporting across many teams.
A platform suited to mature AppSec programs.

Where Checkmarx One fits best

Checkmarx One fits large enterprises where AppSec is a formal program, not an informal set of repository checks. It is useful when security leaders need portfolio-level visibility and consistent policies across many engineering groups.

Possible limitation

Checkmarx One may be more platform than a small team needs. For smaller organizations, Aikido may offer a faster path to broad AppSec coverage with less process weight.

Verdict

Choose Checkmarx One if you need enterprise-scale AppSec coverage across many applications, teams, and testing methods.

GitHub Advanced Security: Best Snyk Alternative for GitHub Native Teams

GitHub Advanced Security is the most natural Snyk alternative for teams that already build almost everything inside GitHub. GitHub’s documentation describes GitHub Code Security features such as code scanning, premium Dependabot features, and dependency review, plus GitHub Secret Protection features such as secret scanning and push protection.

The biggest advantage is workflow placement. Developers do not need another dashboard for many common checks. Security findings can appear close to the repository, pull request, and dependency workflow.

Dependency review can help teams catch insecure dependencies before they are introduced, while Dependabot helps identify and update vulnerable dependencies where automated fixes are possible.

Why choose GitHub Advanced Security over Snyk?

Choose GitHub Advanced Security if you want:

Security inside GitHub workflows.
Code scanning near pull requests.
Secret scanning and push protection.
Dependabot-based dependency alerts and updates.
Less context switching for GitHub first development teams.

Where GitHub Advanced Security fits best

GitHub Advanced Security works best when GitHub is the clear center of engineering work. If your repositories, pull requests, and security reviews already live there, native security features can be easier to adopt than a separate platform.

Possible limitation

GitHub Advanced Security is strongest inside GitHub. If your organization needs broader DAST, runtime security, cloud security, or cross-platform AppSec consolidation, Aikido, Checkmarx One, or Veracode may be a stronger fit.

Verdict

Choose GitHub Advanced Security if your developers already live in GitHub and you want security controls directly inside repository workflows.

Veracode: Best Snyk Alternative for Compliance-Driven Enterprises

Veracode is a mature application security platform built for organizations that need security testing, governance, compliance reporting, and risk management across the software lifecycle. Veracode describes its platform as identifying risks across the SDLC, automating flaw fixes, and simplifying governance and compliance.

Veracode is especially relevant in regulated industries where AppSec is tied to audits, vendor requirements, customer questionnaires, and formal software assurance processes. Its product pages cover SAST, DAST, and SCA, making it a strong fit for organizations that need multiple testing methods under a mature governance model.

Why choose Veracode over Snyk?

Choose Veracode if you want:

Mature enterprise AppSec governance.
SAST, DAST, and SCA coverage.
Compliance-oriented reporting.
Executive and audit-friendly visibility.
A platform with a long enterprise security track record.

Where Veracode fits best

Veracode fits organizations where security testing has to support compliance evidence, formal governance, and risk reporting. It may be especially relevant for finance, healthcare, government suppliers, and enterprise software vendors.

Possible limitation

Veracode may feel heavier than newer developer-first platforms. If your priority is quick developer adoption and broad AppSec consolidation with less process overhead, Aikido may be a better first option to evaluate.

Verdict

Choose Veracode if compliance, governance, and mature enterprise AppSec reporting are more important than a lightweight developer workflow.

Snyk Alternatives by Use Case

Use case	Best choice
Best overall Snyk alternative	Aikido Security
Best Snyk alternative for startups	Aikido Security
Best Snyk alternative for small and mid-sized teams	Aikido Security
Best Snyk alternative for broad AppSec coverage	Aikido Security
Best Snyk alternative for open source SAST	Opengrep
Best Snyk alternative for custom code rules	Opengrep
Best Snyk alternative for open source governance	Mend.io
Best Snyk alternative for enterprise AppSec	Checkmarx One
Best Snyk alternative for GitHub users	GitHub Advanced Security
Best Snyk alternative for compliance-driven teams	Veracode

Aikido vs Snyk

Snyk is not a weak product. It remains a serious developer security platform. The question is whether it is still the best operational fit for your team. If your main pain points are alert volume, workflow complexity, pricing growth, or the need to consolidate AppSec operations, Aikido is the strongest alternative to evaluate first.

Category	Aikido	Snyk
Main positioning	Unified code, cloud, and runtime security platform	Developer security platform
Strongest fit	Teams that want broad AppSec coverage with simpler workflows	Teams already standardized on Snyk developer security workflows
Coverage areas	SAST, SCA, DAST, secrets, IaC, containers, cloud, runtime protection	Code, open source, containers, cloud configurations, IaC, DAST-related capabilities
Developer experience	Built around simplicity and consolidation	Mature developer security ecosystem
Main advantage	Less tool sprawl and broad coverage in one platform	Established platform with strong developer security recognition
Best for	Startups, scaleups, and mid-sized teams that want practical AppSec coverage	Teams that already rely on Snyk or need its specific ecosystem integrations

When Should You Replace Snyk?

You may want to consider a Snyk alternative if:

Developers are spending too much time triaging findings.
Security tickets are not clearly owned.
SAST, SCA, DAST, secrets, IaC, cloud, and container findings are spread across too many tools.
Pricing becomes hard to predict as repositories, contributors, or scan targets grow.
Your team needs broader security coverage than dependency and code scanning.
AppSec wants fewer dashboards and more useful remediation context.
Security teams need to connect code risk with cloud, container, and runtime exposure.

You do not need to replace Snyk only because another product has more features on a checklist. Replacement makes sense when the current workflow slows developers down, leaves important risks uncovered, or creates too much manual security work.

How to Choose the Right Snyk Alternative

Choose Aikido Security if you want the best overall Snyk alternative with broad AppSec coverage, simpler developer workflows, and less tool sprawl.

Choose Opengrep if your team wants open source SAST, custom code rules, and direct control over static analysis workflows.

Choose Mend.io if dependency governance, open source policy, and license compliance are top priorities.

Choose Checkmarx One if you need enterprise-level AppSec coverage across many applications, teams, and testing methods.

Choose GitHub Advanced Security if your developers work primarily in GitHub and you want security checks inside repository workflows.

Choose Veracode if your AppSec program is driven by compliance, governance, reporting, and formal risk management.

FAQ

What is the best Snyk alternative?

The best Snyk alternative for many engineering teams is Aikido Security because it combines broad AppSec coverage with a simpler developer experience. It is especially strong for teams that want SAST, SCA, DAST, secrets, IaC, containers, cloud, and runtime security in one place.

Is Aikido better than Snyk?

Aikido can be better than Snyk for teams that want broader AppSec consolidation and less workflow complexity. Snyk remains a strong developer security platform, but Aikido may be a better fit when teams want one platform across code, cloud, and runtime security.

What is the best Snyk alternative for startups?

Aikido is the best Snyk alternative for many startups because it provides broad security coverage without requiring a large AppSec team to manage separate tools.

What is the best Snyk alternative for enterprises?

Checkmarx One, Veracode, and Mend.io are strong enterprise Snyk alternatives. Aikido can also fit enterprise teams that want broader consolidation with simpler developer workflows.

What is the best Snyk alternative for SAST?

Opengrep is one of the strongest Snyk alternatives for open source SAST, especially when teams need custom code rules and direct control over detection logic. Aikido is better if the team wants SAST as part of a broader AppSec platform that also covers SCA, DAST, secrets, IaC, cloud, containers, and runtime security.

What is the best Snyk alternative for SCA?

Mend.io is one of the strongest alternatives for SCA and open source governance. Aikido is a better first choice when SCA needs to be combined with SAST, DAST, secrets, IaC, cloud, containers, and runtime security.

What is the best Snyk alternative for GitHub users?

GitHub Advanced Security is the most natural Snyk alternative for teams that already work mainly in GitHub. It gives developers code scanning, secret protection, dependency review, and Dependabot workflows inside the GitHub environment.

Final Thoughts

For most teams comparing Snyk alternatives in 2026, Aikido Security is the strongest first option to evaluate. It gives engineering teams broad AppSec coverage without forcing them to manage many disconnected tools. That makes it especially useful for teams that want practical security coverage across code, dependencies, secrets, containers, IaC, cloud, DAST, and runtime risk.

Opengrep is better for teams that want open source SAST and custom code rules. Mend.io is strong in open source governance. Checkmarx One fits large enterprise AppSec programs. GitHub Advanced Security is the best fit for GitHub native teams. Veracode remains a strong choice for compliance-driven organizations.

If the goal is to replace Snyk with a broader, simpler, developer-friendly AppSec platform, Aikido should be the first tool on the shortlist.

Why Remote Developers Should Prioritize Online Privacy in 2026

Alex Vakulov — Mon, 13 Apr 2026 10:43:35 +0000

Over the past decade, remote work has evolved from being merely an alternative to traditional office setups to becoming a cornerstone of the tech industry. With the rise of distributed teams and a global workforce, remote developers have gained unprecedented flexibility and productivity. However, this evolution brings its own set of challenges, particularly in protecting sensitive code, personal data, and intellectual property. The convergence of cutting-edge technologies with increasingly sophisticated cyberattacks means that remote developers must continually refine their security practices to safeguard not only their work but also their online identities.

As remote work environments continue to expand, developers face a variety of potential vulnerabilities, from insecure home networks to targeted phishing campaigns. These threats have evolved beyond typical malware and ransomware, adopting more advanced methods that exploit emerging digital trends. Factors contributing to the heightened risk include the decentralized nature of remote work, the use of public and semi-secure networks, and the advent of adversarial artificial intelligence in cyberattacks. This new digital era demands that remote developers reexamine their privacy protocols, ensuring they are not only compliant with industry standards but also proactive in addressing potential breaches before they occur.

Emerging Threats and the Importance of Data Security

The continuously evolving cyber threat landscape is a critical reason why remote developers must elevate their focus on online privacy. Modern threats now include AI-powered intrusions, targeted social engineering, and sophisticated spear phishing attempts. These challenges are compounded by the increased reliance on cloud-based services and collaborative coding platforms, which can sometimes expose sensitive data to unintended recipients.

In response to these challenges, industry experts and regulatory bodies have developed guidelines and frameworks designed to improve data security. For example, the NIST Cybersecurity Framework offers a comprehensive set of practices that help organizations and individual professionals protect their digital assets. By adopting such well-established standards, remote developers can better understand their risk profile, implement effective control measures, and respond quickly to emerging attacks. Ultimately, the knowledge and practices advocated by these frameworks are essential tools for anyone working outside of traditional office environments.

While it is encouraging to see a range of solutions available to address these issues, the challenge remains in integrating them into everyday workflows without causing significant disruption. As new vulnerabilities emerge, staying updated with the latest cybersecurity trends and risk management strategies has become a non-negotiable requirement for today's digital professionals.

Best Practices for Online Privacy: Tools and Strategies

Recognizing online privacy as a core component of professional success is the first step towards a safer digital environment for remote developers. Among various measures, using specialized tools that enhance privacy and encrypt data is one of the most effective strategies. Developers should consider integrating privacy-enhancing technologies into their daily routines, ensuring all sensitive information is shielded from unauthorized access. In this context, selecting the best VPN becomes a crucial component of any robust security strategy.

This privacy tool not only encrypts data across public or semi-public internet connections but also masks a developer’s real IP address. Such protection remains vital as cybercriminals continually refine their tactics to exploit any exposed weaknesses. Aside from encrypting communications, modern privacy solutions also offer features such as secure DNS and protection against data leakage, all of which help remote developers maintain confidentiality and operational integrity. By incorporating these measures, developers can focus on coding and collaboration without worrying about the growing complexity of cyber threats.

In addition to using privacy tools, remote developers can adopt a range of practices that further mitigate risk. Regular software updates, strong multi-factor authentication, secure coding protocols, and continuous monitoring of network traffic are all measures that add layers of defense. Investing in training and workshops about digital hygiene is equally critical. As the industry shifts, so too do the methods of cyberattacks, making it essential that developers stay informed about the latest trends and tools that help safeguard their online presence.

Future Trends: AI, Data Protection, and the Remote Developer

As we approach 2026, trends in artificial intelligence and machine learning are likely to redefine the cybersecurity landscape. AI is set to play a dual role: on one hand, it will empower developers by automating threat detection and facilitating rapid responses to breaches; on the other, it can be misused to launch hyper-targeted cyberattacks. This dual-edged impact means that remote developers must not only adopt state-of-the-art defensive measures but also remain vigilant about the potential misuse of these emerging technologies.

The Deloitte Global Digital Risk Survey provides insightful data on how organizations are rebalancing their IT budgets to accommodate the increasing complexity of cyber threats in a digital era. Findings from such surveys indicate that investments in cybersecurity are expected to rise significantly in response to growing regulatory pressures and the expanding surface area exposed by remote work environments. These statistics underscore the importance of not only adopting best practices today but also planning for an even more challenging tomorrow.

Future-proofing one’s career as a remote developer means embracing continuous learning and adapting to new protocols as they develop. This includes an evolving understanding of data protection regulations, trends in industry-specific cyber threats, and the integration of AI-driven countermeasures. As the boundaries between personal and professional digital realms blur, ensuring consistent online privacy is an investment in long-term professional security and peace of mind.

Fostering a Secure Remote Work Culture

Beyond individual measures, cultivating a culture that prioritizes online privacy within distributed teams can yield lasting benefits. Organizations must encourage transparent communication about cybersecurity practices and ensure that all team members—regardless of their technical expertise—are aware of the latest data protection protocols. Peer-to-peer learning and active community discussions on dev.to frequently highlight practical tips for managing secure remote workflows. Articles focused on this subject share personal experiences and successful strategies that can inspire shifts in broader industry practices.

Educating teams about the importance of practices such as regularly updating software, secure password management, and prudent data-sharing policies can reduce the likelihood of inadvertent security lapses. In fact, such knowledge transfer is already evident across various developer communities where security-conscious practices are celebrated and refined. Consider, for example, a recent piece on remote work safety that outlines clear steps and tools to fortify personal and team security. Contributions like these encourage developers to extend their security practices beyond technical implementations, fostering an environment where every member feels responsible for the collective well-being.

Conclusion: Stepping into a Secure Future

In conclusion, the rapidly changing digital landscape demands that remote developers are proactive in securing their online presence. As we approach 2026, the convergence of remote work, emerging cyber threats, and AI-powered technologies will require a renewed commitment to data protection and privacy. Adopting robust privacy tools and best practices is not simply a precaution—it is an essential investment in personal and professional sustainability.

By understanding the risks and integrating comprehensive security frameworks, remote developers will be better positioned to navigate the challenges of the future. Equally important is the role of community-driven platforms where developers regularly share expertise and support one another in addressing the evolving cybersecurity landscape. For further insights and practical tips on maintaining safe and secure practices while working remotely, a comprehensive guide on remote working security is available here.

The journey towards enhanced online privacy is a continuous one, and every step taken today contributes to a safer digital tomorrow. Engaging with industry research and contributing to community discussions can help stay ahead of emerging threats. Readers are encouraged to share their experiences and strategies in secure remote working in the comments section below, fostering a collaborative environment dedicated to innovation and safety. For those looking to further refine their security measures, resources and expert advice are readily available through dedicated cybersecurity specialists.

Why Salesforce to Power BI Integrations Break at Scale (And How to Design Them Properly)

Alex Vakulov — Tue, 07 Apr 2026 06:54:02 +0000

Connecting Salesforce to Power BI is straightforward. Keeping that integration stable, scalable, and maintainable over time is not.

Most teams start with a simple goal: load Salesforce data into Power BI and build reports. That works at a small scale. As data volume grows, refresh requirements increase, and multiple teams depend on the same datasets, the integration starts to break in less obvious ways.

Where Integrations Start to Fail

Salesforce to Power BI integrations usually fail along a few predictable lines:

1. Dataset Explosion → Semantic Drift

Each report typically imports Salesforce data independently and defines its own logic. At a small scale, this is manageable. At a larger scale, small differences in filters, joins, and calculated fields accumulate. The same metric ends up defined multiple ways across reports.

There is no shared semantic layer, so fixes do not propagate. Lineage becomes unclear, and teams spend time reconciling numbers instead of using them. The issue is not the number of datasets, but duplicated logic without central control.

2. Refresh Bottlenecks → API Saturation

Power BI import mode triggers data extraction on each refresh. As datasets grow, refresh jobs become larger and more frequent, competing for Salesforce API limits and Power BI refresh capacity.

Typical outcomes include timeouts, throttling, and partial loads that leave datasets inconsistent. Incremental refresh helps only when filtering can be pushed to the source and aligned with a reliable change tracking field. With Salesforce, query folding is limited and often breaks depending on the connector choice and transformations, which can force larger data scans than expected.

3. API and Query Constraints → SOQL Limits at Scale

The constraint is not just about API quotas, but also about how Salesforce exposes data. SOQL supports relationship queries, but it does not provide the same flexibility as a full relational engine. Queries that perform well during development can degrade as data volume grows, especially when query structure and logic are not validated early in the lifecycle, something teams often enforce in code through practices supported by SAST tools.

Large result sets require pagination or Bulk API, and inefficient query patterns can trigger full scans. At scale, teams often combine connectors and API approaches without a clear strategy, leading to inconsistent performance and unpredictable load behavior.

4. Model Complexity in Reports → No Separation of Layers

When extraction and modeling are handled inside Power BI, each report rebuilds relationships and embeds its own business logic using Power Query and DAX. This duplicates transformations, increases refresh cost, and makes logic difficult to validate or reuse.

Power BI effectively acts as ingestion, transformation, and a semantic layer at the same time. This approach works with a small number of reports, but breaks as more teams depend on shared data. Changes become harder to manage, and performance degrades due to repeated processing.

Defining Requirements Before Choosing a Connection Method

Before choosing how to connect Salesforce to Power BI, it is more useful to define what the integration needs to support. Most problems at scale come from selecting a connection method too early, without understanding data volume, refresh behavior, and reuse requirements.

Data Volume and Scope

The volume and scope of data determine what is feasible. Extracting a small subset of Salesforce data for a single report behaves very differently from pulling multiple objects with historical data. As the scope expands, queries become heavier, relationships become harder to manage, and API usage increases. A connection method that works for a narrow dataset can degrade quickly when expanded without redesign.

Extraction Level

There are two common patterns in practice. Some teams extract data at the report level, where each Power BI report pulls exactly what it needs. This is easy to start with, but leads to duplication and inconsistent logic as usage grows.

Others extract at the object level, loading core Salesforce entities such as Accounts, Opportunities, and Activities into a shared layer. This requires more upfront design but provides control over relationships, filtering, and reuse. The tradeoff is between speed of initial delivery and long-term maintainability.

Refresh Strategy

Refresh requirements should be defined early because they determine how efficient data extraction must be. Occasional refresh can tolerate large queries and inefficient filtering. Once refresh becomes scheduled or frequent, those inefficiencies surface as timeouts, throttling, and inconsistent loads.

Incremental refresh is often introduced to reduce load, but it is most effective when filtering can be pushed to the source and aligned with a reliable timestamp or change field such as SystemModstamp or LastModifiedDate. In Salesforce, this depends on both the data model and the connector behavior. If filters are not applied at the source, incremental refresh can still trigger large scans, limiting its benefit.

Dataset Reuse

Reuse becomes critical once multiple reports depend on the same Salesforce data. If each report defines its own extraction and transformation logic, the system fragments quickly. Metrics diverge, fixes do not propagate, and maintenance becomes manual.

A shared dataset or dataflow layer allows logic to be defined once and reused across reports. This introduces control over definitions and reduces duplication. Without it, the integration evolves into multiple independent pipelines that are difficult to align.

Model Complexity

Simple reporting models can be built directly in Power BI. As complexity increases, especially when combining multiple Salesforce objects, the model becomes harder to manage and validate at the report level.

Relationships, filtering logic, and calculated fields are better structured before they reach Power BI when the model is reused across reports. Otherwise, the same modeling logic is repeated, increasing refresh cost and the risk of inconsistencies.

Two Architectural Approaches to Integration

At a high level, Salesforce to Power BI integrations follow one of two patterns. The primary difference is not the connector, but where data extraction and modeling are defined.

1) Report-Centric Integration

In this approach, data is typically loaded directly into Power BI, and each report defines its own dataset and transformations. This is the default path for most teams because it is fast to start and requires minimal setup.

It works well for small datasets and isolated reporting. As usage grows, multiple reports begin to depend on overlapping data, logic is duplicated, and definitions start to diverge. Refresh load increases because the same data is extracted multiple times. The system remains functional, but becomes fragmented and difficult to control.

2) Dataset-Centric Integration

In this approach, data extraction and structure are defined outside Power BI, and reports consume a prepared dataset. This can be implemented through dataflows, pipelines, or external integration layers, but the key idea is that the dataset is treated as a shared asset.

This requires more upfront design, but it allows relationships, filtering, and definitions to be controlled in one place. Extraction is centralized, which reduces duplication and API pressure. Reports become consumers of a stable model rather than owners of their own logic. As a result, reuse improves, refresh becomes more predictable, and changes can be applied consistently.

In practice, this pattern is implemented in different ways. Some teams use data pipelines such as Azure Data Factory or managed ingestion tools like Fivetran to move Salesforce data into a structured layer before it reaches Power BI. Others use connectors that expose reusable datasets directly from Salesforce, allowing datasets to be defined once and reused across reports rather than rebuilt inside each report.

Why the Difference Matters

Again, the distinction is architectural rather than tool-specific. Report-centric models optimize for speed of delivery but tend to fragment as usage grows. Dataset-centric models require more upfront design, but provide control over consistency, refresh behavior, and change management.

Centralizing extraction and modeling keeps definitions aligned across reports, reduces duplicated queries against Salesforce, and makes refresh behavior more predictable. Changes to data logic can be applied once rather than replicated across multiple reports.

Most of the failure patterns described earlier are not caused by Salesforce or Power BI themselves. They are a result of scaling a report-centric model beyond what it was designed to support.

Where Most Implementations Go Wrong

Most failures come from treating integration as a connection problem instead of a data design problem.

Teams start with native connectors and build reports directly in Power BI. As usage grows, reports are added without redefining the data model. Each report introduces its own extraction logic, which leads to duplicated queries, increased API usage, and diverging definitions.

Incremental refresh is often added later without aligning it to the extraction model. When filtering is not applied at the source, refresh jobs still process large data volumes, adding complexity without improving performance.

Over time, multiple approaches are combined. Some datasets are built inside Power BI, others are partially staged, and there is no clear separation between extraction and reporting. The system continues to run, but becomes inconsistent, difficult to change, and hard to trust.

Design Principles That Hold Up Over Time

Stable integrations are defined by a small number of decisions made early:

Define the dataset before building reports. Without a shared dataset, each report becomes a separate data model with its own logic.
Align refresh strategy with extraction. Incremental refresh is most effective when filtering is applied at the source and supported by the data model. Without this, refresh jobs still process large volumes of data.
Limit duplication early. Each duplicated extraction increases API load and creates another source of inconsistency.
Separate extraction, transformation, and reporting. When these layers are combined inside Power BI, changes become harder to control and reuse.

Rethinking Data Security: From Tool Sprawl to Data-Centric Protection

Alex Vakulov — Wed, 18 Mar 2026 08:02:20 +0000

Modern data infrastructure continues to evolve, but protecting it often remains inefficient due to the reliance on numerous highly specialized security tools. Today’s environments call for solutions that simplify data management while still delivering strong, consistent protection.

Confidential data is a critical asset for organizations, supporting competitiveness and enabling informed business decisions. When this information is exposed without authorization, the consequences extend well beyond direct financial losses and can affect trust, operations, and long-term strategy.

Research from the SANS Institute and CrashPlan shows that reputational damage is the top concern for organizations, as it can lead to customer churn, lost market share, and declining share value. Legal and regulatory consequences rank close behind as the next significant risk.

Recent reports show that the majority of reported data compromises stem from cyberattacks, with 1,348 incidents in the first half of 2025 alone. Government agencies, healthcare organizations, financial institutions, industrial enterprises, and IT companies continue to rank among the most frequently targeted sectors, reflecting attackers’ focus on high-value data and interconnected systems, particularly through supply-chain vulnerabilities.

Cybercriminals often focus on stealing user credentials and trade secrets. At the same time, ongoing political tensions are driving greater interest in disrupting critical infrastructure and leaking stolen data. The steady stream of data leaks shows that existing security approaches often fall short, leaving data protection a critical, unresolved challenge.

The core challenge for defenders is no longer a lack of security tools, but the inability to maintain a coherent, real-time understanding of where sensitive data exists and how it is being used across the environment.

How Data Protection Methods Have Evolved

Over the past few decades, data storage and processing infrastructure has changed dramatically, driven by technological advances, shifting business demands, and evolving security practices.

These changes can be broadly grouped into four stages. Each stage reflects not just technological progress, but also the gradual shift from protecting systems and networks to protecting data itself.

Manual Data Management: 1980s – Late 1990s

During this period, most organizations had a relatively small IT footprint, typically around 100 to 200 workstations and 10 to 20 servers. Business processes were not yet fully digital, and critical information was often stored on paper or in basic electronic formats.

Data protection was not a primary concern at the time. Instead, companies focused on general information security, relying on basic tools such as firewalls, antivirus software, and intrusion detection systems. Security assumptions during this period were shaped by limited scale, in which visibility and control were manageable because data volumes and access paths were small.

Digital Transformation: Early 2000s

At the start of the new millennium, organizations began actively digitizing their operations. IT environments grew more complex, with assets becoming centralized and typically housed in one or two locations. The volume of data that needed protection increased sharply.

As awareness of data breaches grew, companies started classifying their information, and the first purpose-built security tools appeared, most notably data loss prevention (DLP) systems.

At the same time, as data moved into centralized digital systems, security controls began to lag behind growth, creating early blind spots around access, classification, and misuse.

Expanding IT Capabilities: Mid-2000s – Mid-2010s

Over the following decade, organizations continued to digitize at scale, and IT infrastructures became increasingly distributed. The use of databases and file storage grew rapidly, and many companies began experimenting with cloud technologies. As data volume and variety expanded, traditional DLP tools were no longer sufficient.

This led to the emergence of more specialized solutions for specific parts of the infrastructure, including database monitoring and protection tools such as DAM (Database Activity Monitoring) and DBF (Database Firewall).

While these specialized tools improved protection in isolated areas, they also fragmented security visibility and made it harder to understand data risk across the organization as a whole.

The Big Data Era: Mid-2010s – Present

Digital business transformation has reached a point where data volumes are so large and dynamic that they often seem to take on a life of their own. Information has become a core asset for modern organizations, and data-driven approaches shape how business processes are designed and optimized. Companies rely heavily on big data collection and analytics technologies, which demand stronger, more comprehensive protection.

Yet many organizations still depend on legacy tools such as DLP, DBF, and DCAP, each focused on a narrow task rather than delivering end-to-end data security. At this scale, protecting individual systems is no longer sufficient because risk arises from how data moves, changes, and is accessed across platforms rather than from where it is stored.

How Tool Sprawl Creates Data Security Blind Spots

Again, protecting a modern, heterogeneous environment with many internal dependencies often means deploying a wide range of traditional security tools. Today, organizations with more than 1,000 employees use an average of six different data protection solutions. Each additional tool introduces its own policies, alerts, and data models, increasing operational complexity while reducing the ability to see the whole security picture.

This approach requires substantial financial investment as well as significant effort from security teams, who must maintain each tool and integrate it with other systems and internal processes, such as linking security alerts directly into a DevOps ticketing workflow to manage remediation. As a result, achieving full infrastructure coverage and maintaining up-to-date visibility becomes difficult. With regulatory penalties for data breaches continuing to rise, this gap exposes organizations to serious financial risk.

In practice, this fragmentation delays incident detection and response, as security teams must manually correlate signals across disconnected systems under time pressure.

This has created a clear need for a more comprehensive security approach, one that gives information security teams real-time visibility into critical questions such as:

How much data exists across the environment
Where that data is stored and how different datasets are connected
Which locations contain sensitive information
Who has access to that data, and how access can be limited
How sensitive data is actually being accessed and used

Analyst firms such as KuppingerCole and Forrester highlighted the importance of consolidating multiple security functions into a single platform, a category Gartner described as a new class of solutions known as Data Security Platforms (DSPs).

The Value of a Data-Centric Security Model

To protect information effectively, the security industry has moved toward a data-centric approach that safeguards data throughout its entire lifecycle, from creation and storage to transmission and eventual deletion, regardless of where the data lives or how it is used. This shift places data, not infrastructure boundaries, at the center of security decision-making.

Consider a scenario where an organization detects malware activity in a cloud environment. Traditional security tools may identify the initial compromised account or alert source, but they often cannot quickly answer the most critical questions: what data was accessed, where that data resides, and how sensitive it is.

With a data security platform in place, security teams can immediately identify which datasets were involved, determine whether regulated or confidential information was exposed, trace access paths across systems, and assess potential business and compliance impact in real time. This visibility allows teams to prioritize incident response actions and communicate accurate risk assessments to leadership and regulators.

DSPs provide a unified view of an organization’s security posture, enabling easier infrastructure monitoring, faster vulnerability identification, and more efficient incident response. Instead of replacing existing controls, DSPs act as an orchestration and intelligence layer that connects them into a single, data-focused security model.

These platforms also integrate with other security systems, enabling a more flexible and adaptive security architecture. This approach strengthens data protection while freeing up security teams to focus on higher-value tasks rather than tool maintenance and manual coordination.

As data becomes the primary driver of modern business value, security strategies must evolve from protecting individual systems to governing data across its entire lifecycle. Organizations that make this shift early will be better positioned to manage risk, maintain compliance, and operate securely at scale.

7 ITSM Tools Developers Should Evaluate in 2026

Alex Vakulov — Wed, 04 Mar 2026 08:53:33 +0000

7 ITSM Tools Developers Should Evaluate in 2026

IT Service Management (ITSM) for DevOps is a framework that connects change management, infrastructure visibility, incident tracking, and compliance workflows so teams can ship quickly while maintaining operational accountability.

In modern software teams, the question is no longer:

"How do we manage tickets?"

It is:

"How do we connect what we build, what we run, and what we are accountable for?"

As release velocity increased, many teams discovered that CI/CD solved delivery speed but not operational clarity. Systems changed faster than organizations could explain them. That gap is exactly where modern ITSM platforms now operate.

ITSM in a DevOps World Is About Traceability, Not Tickets

In modern CI/CD environments, change is constant. Infrastructure scales dynamically, ownership shifts across teams, and security signals arrive from dozens of tools. Without a way to connect those signals, organizations lose the ability to explain their own systems.

This is where ITSM has quietly changed roles. Instead of enforcing the process before the change happens, it records relationships after the change occurs. Deployment events can be associated with configuration items. Incidents can be traced back to releases. Asset inventories can reflect what actually exists rather than what was once documented.

Security tooling identifies risk. ITSM ensures that risk is owned, tracked, and resolved. Without service management:

Vulnerabilities lack lifecycle tracking
Infrastructure ownership becomes tribal knowledge
Compliance evidence requires manual reconstruction
Incident response lacks operational context

ITSM provides the persistent memory layer that security automation alone cannot supply.

What Matters When Evaluating an ITSM Platform

The most useful ITSM systems align three domains that were historically separate: service workflows, asset awareness, and automation. When those elements are connected, teams gain visibility into what they run and how it evolves.

Equally important is how naturally the platform integrates into engineering environments. Tools that rely entirely on manual updates struggle to keep pace with automated delivery. Systems designed with APIs and event-driven updates tend to adapt better to DevOps cultures.

Governance also plays a role, but it must emerge from workflows rather than impose itself as rigid gates.

What Are the Best ITSM Tools for DevOps in 2026?

Platform	Strength	Typical Use Case	Implementation Weight
InvGate	Integrated service + asset visibility	Scaling operational maturity	Low
Jira Service Management	Developer ecosystem alignment	Engineering-centric orgs	Medium
ServiceNow	Enterprise workflow orchestration	Large regulated environments	High
Freshservice	Structured ITSM with fast adoption	Growing companies	Low
ManageEngine ServiceDesk Plus	Broad capability with flexible deployment	Mixed infrastructure orgs	Medium
SolarWinds Service Desk	Operational analytics focus	Hybrid infrastructure teams	Medium
Zendesk	Lightweight internal service workflows	Support-driven environments	Low

1. InvGate

InvGate combines IT Service Management and IT Asset Management into a unified platform that connects operational workflows directly to infrastructure context.

Rather than treating assets as a separate CMDB or static inventory, InvGate links incidents, changes, and requests to the systems and ownership data involved, helping teams maintain traceability as environments evolve.

Where It Fits

Organizations strengthening DevOps governance and change visibility
Teams that need lifecycle and ownership clarity without complex customization
Environments transitioning from spreadsheets or disconnected tools

Notable Characteristics

Built-in asset discovery and lifecycle tracking
Visual, no-code workflow configuration
Unified view of change, incident, and asset relationships

Considerations

Smaller ecosystem compared to large enterprise vendors
Less focused on highly bespoke, developer-driven workflow modeling

2. Jira Service Management

Jira Service Management extends the Atlassian platform into ITSM, allowing operational workflows to live alongside development tracking.

It is frequently selected when engineering teams already rely on Jira Software.

Where It Fits

Dev-led organizations
CI/CD-centric delivery models
Teams wanting shared tooling between Dev and Ops

Notable Characteristics

Native linkage between issues, deployments, and change tracking
Strong API and automation rule framework
Asset and configuration features available through Atlassian Assets

Considerations

Asset management depth depends on configuration
Can become complex in large environments

3. ServiceNow

ServiceNow is an enterprise workflow platform with extensive ITSM capabilities, designed for organizations that require deep process modeling and governance.

It is often chosen when operational workflows span multiple departments and regulatory frameworks.

Where It Fits

Large enterprises
Regulated sectors
Complex approval or segregation-of-duties environments

Notable Characteristics

Highly configurable workflow engine
Mature CMDB model
Extensive integration ecosystem

Considerations

Significant implementation effort
Requires dedicated administration resources

4. Freshservice

Freshservice delivers cloud-based ITSM with structured workflows aimed at organizations moving from informal support models to defined service operations.

Where It Fits

Mid-sized companies scaling internal IT practices
Teams seeking structured workflows without heavy rollout

Notable Characteristics

Incident, change, and asset management in a SaaS model
Workflow automation and service catalog features
Quick onboarding relative to enterprise platforms

Considerations

Less customizable for highly complex governance models

5. ManageEngine ServiceDesk Plus

ManageEngine ServiceDesk Plus provides comprehensive ITSM functionality with options for cloud or on-prem deployment.

Where It Fits

Organizations with mixed infrastructure constraints
Teams needing flexibility in hosting models

Notable Characteristics

CMDB and asset tracking capabilities
Broad ITIL process support
Strong reporting and configuration options

Considerations

Interface modernization lags newer SaaS platforms

6. SolarWinds Service Desk

SolarWinds Service Desk focuses on operational visibility and integrates well into infrastructure-centric environments.

Where It Fits

Hybrid IT environments
Infrastructure and operations-driven teams

Notable Characteristics

Asset discovery features
Incident and change tracking aligned with monitoring ecosystems
Reporting and analytics capabilities

Considerations

Less developer-workflow centric than some competitors

7. Zendesk (for Internal IT Use Cases)

Zendesk is primarily a service platform adopted by some organizations for internal IT workflows rather than a full traditional ITSM suite.

Where It Fits

Internal support enablement
Organizations prioritizing usability over governance depth

Notable Characteristics

Rapid deployment and intuitive interface
Strong request management workflows

Considerations

Limited native ITAM/CMDB depth
Not intended for complex DevSecOps orchestration

Choosing Based on Organizational Maturity

The right ITSM tool depends less on feature lists and more on how structured your operations already are.

If Your Organization Needs	Likely Fit
Operational visibility without heavy rollout	InvGate
Engineering-native workflow alignment	Jira Service Management
Enterprise-scale governance	ServiceNow
Structured SaaS ITSM adoption	Freshservice
Flexible infrastructure support	ManageEngine
Infrastructure-centric operations	SolarWinds
Lightweight internal service workflows	Zendesk

Final Thoughts

The evolution of ITSM has little to do with improving help desks. It reflects a broader shift toward understanding software systems as living environments that must be continuously mapped, governed, and explained.

As organizations scale their DevOps practices, they discover that speed alone is not enough. They need mechanisms that preserve context as systems change.

Modern ITSM platforms attempt to provide that context. At their best, they do not interrupt engineering workflows. They make those workflows observable, accountable, and sustainable.

In that sense, ITSM is no longer an external layer applied after software is built. It has become part of how reliable software delivery is maintained over time.

Which Programming Languages Fuel Today’s Malware Attacks

Alex Vakulov — Sun, 11 May 2025 10:06:34 +0000

It is difficult to claim that any system or program is completely secure. All of them may contain potential vulnerabilities - errors made during the development process - that can lead to serious consequences. Attackers often exploit such flaws. Information security companies continuously monitor vulnerabilities and update security databases. Their monitoring typically includes sources such as the U.S. Government’s National Vulnerability Database (NVD), security advisories, GitHub issue trackers, and open-source projects.

To create malicious code, attackers use a variety of programming languages. Some are more popular in cybercriminal circles due to their ease of use, compatibility with specific systems, and the wide availability of libraries that help solve particular problems.

The Most Common Programming Languages Used in Cyberattacks

It is important to understand that a programming language is merely a tool. Far more critical are the skills and experience of the malware developer - their expertise in the operating systems targeted, their knowledge of cryptography, and their understanding of how network protocols function.

For example, if an attacker is proficient at evading detection on an endpoint and effectively implements communication between the malware and command-and-control servers, the choice of programming language becomes secondary. The language used is typically determined by the environment in which the malicious code will run and the specific tasks it needs to perform.

Nevertheless, numerous studies and observations indicate that the majority of sophisticated malicious programs with extensive functionality are primarily developed in C and C++. These languages are favored for creating serious threats because they provide low-level access to system resources, allow direct memory manipulation, and enable the construction of complex structures that hinder analysis and detection.

Another factor contributing to their popularity in the cybercriminal ecosystem is their portability - C and C++ have minimal runtime dependencies, making it easier to compile and adapt malicious code across different platforms. Cybersecurity experts also point out that C, in particular, is prone to undefined behavior, which often results in security flaws and exploitable vulnerabilities in software infrastructure.

Beyond C

The criminal IT underground also effectively leverages other programming and scripting languages. In Windows environments, attackers frequently rely on PowerShell, a command-line shell and scripting language developed by Microsoft, based on the .NET Framework and .NET Core. PowerShell is installed by default on all modern Windows systems and is highly valued by threat actors for its powerful system management capabilities. While PowerShell is widely used by IT professionals to automate tasks, manage system configurations, and enable interoperability between services, cybercriminals exploit these same features to move laterally across networks, gather intelligence, maintain persistence, evade detection, and modify system settings to facilitate subsequent stages of an attack.

In *Unix-like (nix) systems, the go-to scripting language for similar purposes is Bash (Bourne Again Shell) - the default command-line interface in most Linux distributions. Bash scripts allow for extensive control over system processes, configurations, user interactions, and data management. These capabilities make Bash particularly appealing to attackers looking to automate malicious tasks, manipulate system behavior, and establish control over compromised systems in Linux-based environments.

Malware developers have also turned their attention to web technologies, which power the websites and services users access every day. In this domain, JavaScript stands out as one of the most exploited languages by cybercriminals. It is commonly used to craft malicious scripts for cross-site scripting (XSS) attacks, where harmful JavaScript code is injected into web pages viewed by unsuspecting users. Attackers also use JavaScript to build payload loaders and string obfuscators, which conceal malicious content and help execute it on the victim’s machine. These techniques enable the silent delivery and execution of malware through seemingly legitimate web interactions.

Python’s Role in Modern Malware Creation

The range of programming languages that can be used for malicious purposes is broad -malware can be written in virtually any language, depending on the attacker’s objectives and the target environment. While some languages are more common in the development of cyber threats, others see limited use. For example, Python, despite its popularity among legitimate developers and cybersecurity professionals, is less frequently used by malware creators. This is primarily due to its interpreted nature, larger runtime dependencies, and the ease with which Python-based code can be analyzed and detected compared to compiled languages like C or C++.

Although Python is less commonly used for creating sophisticated malware, it is still employed in the development of various types of malicious software, particularly for prototyping, automation, or targeting systems where Python is already installed. The most common types of Python-based malware include:

Stealers – Programs designed to collect sensitive user and system data from a victim’s device and transmit it to an attacker-controlled server. A notable example is the Snake malware, which demonstrated how effective Python can be for data exfiltration.
Downloaders – Lightweight scripts used to retrieve additional malware, libraries, or payloads from remote servers, acting as an initial stage in multi-phase attacks.
Miners – Malicious programs that exploit a victim’s computing resources to mine cryptocurrencies such as Monero, often running quietly in the background to avoid detection.
Encryptors (Ransomware) – Tools that perform unauthorized cryptographic operations on a victim’s files, effectively locking them and demanding payment for decryption. Python-based versions are often seen in proof-of-concept ransomware or low-sophistication campaigns.

Protecting Against Python-Based Malware

There are no unique protection methods tailored specifically to malware written in Python. Instead, the most effective defense lies in adhering to general digital hygiene practices and established information security policies. These best practices form the foundation of device and network protection, regardless of the programming language used to create malicious code. Cybersecurity professionals are well aware of these measures and typically implement them as part of standard security protocols. Let’s revisit the core principles that underpin adequate protection.

Comprehensive antivirus coverage across all endpoints – Ensuring that every device within the network is protected by reputable and regularly updated antivirus software like Fortect Antivirus or endpoint detection and response (EDR) solutions.
Layered security measures and infrastructure hardening – Using information security tools in combination with proper system configuration, regular software updates, centralized event monitoring, and secure architecture design to minimize vulnerabilities.
Ongoing employee training and awareness – Continuously educating staff on cybersecurity threats and safe digital behavior, with a strong focus on identifying phishing attempts, malicious attachments, and suspicious links, especially in corporate email.
Regular backups of critical data – Implementing automated and secure backup procedures to ensure data recovery in the event of ransomware attacks or other forms of data loss.

Conclusion

Software security issues are well-known and have been extensively documented. Developers learning to write applications are typically taught the principles of clean code and secure development practices from the outset. A brief search online reveals countless resources offering detailed and accessible recommendations for building secure software. However, even when best practices are followed during development, mistakes can still occur, resulting in vulnerabilities that attackers may exploit. To mitigate such risks, security technologies are often embedded at the operating system (OS) level, providing additional layers of defense against exploitation through software flaws.

Gaps in SOC Operator and Analyst Skillsets

Alex Vakulov — Mon, 20 May 2024 09:01:25 +0000

Despite the growing importance of SOC (Security Operations Center) operators and analysts, many applicants often lack critical knowledge and skills, which can significantly hinder their ability to perform tasks effectively. Let's explore the common deficiencies in their skill sets.

Candidates for SOC operator positions frequently lack a foundational understanding of IT technologies. They often have minimal hands-on experience with information security systems and are unfamiliar with typical network attacks and attacker tactics. This lack of basic knowledge and practical experience leaves them ill-equipped to handle the complex challenges they will face on the job.

For SOC analysts, even those with experience in corporate SOCs, the gaps can be just as significant. Many analysts lack the ability to write effective correlation rules and have a limited understanding of attack vectors or the MITRE ATT&CK framework. Their experience might be limited to basic, off-the-shelf content, without the depth required to investigate real incidents thoroughly.

To improve these skills, it is essential for SOC employees to focus on practice. Engaging in cyber exercises and competitions can significantly enhance their hard skills. Novice specialists, if they have a solid foundation of knowledge, can be quickly trained in SOC-specific skills and adapted to the company’s technologies, processes, and techniques.

However, the challenges faced by SOC employees go beyond just a lack of experience with security systems. Many have only modest experience in operating information security systems, often limited to one or two SIEMs (Security Information and Event Management systems). Additionally, their knowledge of modern regulatory requirements in information security is often insufficient. Communication skills can also be a significant issue, with many lacking the ability to effectively interact with customers and colleagues.

Practical experience is crucial for SOC employees. Many applicants struggle to understand what real attacks look like in practice, as opposed to theoretical descriptions from books and magazines. They also often lack the practical experience needed to respond to and investigate incidents effectively. Soft skills are equally important; tolerance for uncertainty, effective communication, and the ability to convey one’s position convincingly are often missing.

Real-world experience is invaluable and often more important than theoretical knowledge. In commercial SOCs, where analysts and experts work with multiple customers and encounter incidents more frequently, knowledge and experience grow much faster compared to in-house SOCs. Sharing experiences within a team is crucial, yet applicants often lack the desire to gain this kind of real-world experience.

The most common knowledge gaps include fundamental IT knowledge, such as understanding network operating systems (Windows, Linux, Mac), network technologies (at least CCNA level), and classic attacker techniques like fixation, lateral movement, and network protocol attacks. Additionally, basic knowledge of DFIR (Digital Forensics and Incident Response) is often lacking, including what forensic artifacts to collect in different scenarios and how to respond to typical attacks.

Addressing these gaps through focused training, practical experience, and the development of both hard and soft skills will better prepare applicants for successful roles as SOC operators and analysts.