About CyberSanso
General questions about who CyberSanso is, how the platform works, and how to get the most out of it.
CyberSanso reviews and updates vendor profiles, tool listings, pricing, and market data on a quarterly basis. Content that reflects fast-changing information — including CVE data, AI model releases, and regulatory updates — is reviewed more frequently. All pages include a last-reviewed date so you can judge how current the information is before acting on it.
Vendors and tools can be submitted through the Submit a Tool page on CyberSanso. Basic listings are free and open to any verified cybersecurity, AI, or SaaS vendor. Submissions are reviewed before publication for relevance and accuracy. Enhanced and Premium profiles are available for vendors who want a more complete listing with direct contact options and category placement.
Yes. CyberSanso publishes a free weekly digest covering the most important cybersecurity news, AI tool updates, SaaS funding, and breach alerts from the past week. You can subscribe from the homepage or the newsletter page without creating an account. No spam, no vendor promotions, and you can unsubscribe with one click.
CyberSanso does accept sponsored content and paid vendor placements, but these are always clearly labeled as sponsored. No cybersecurity, AI, or SaaS company has ever paid to influence editorial rankings, review scores, or category descriptions. The editorial content — guides, comparisons, glossary entries, and CVE data — is funded independently of vendor relationships.
CyberSanso currently publishes in English only. All content, including the vendor database, glossary, guides, and CVE tracker, is written in English. The material is designed to be accessible to non-native speakers with plain-language explanations throughout.
Use the Contact page or click the feedback option on any vendor profile or content page to flag an issue. We review all submissions and respond within 48 hours. Corrections to factual errors are prioritized. If a vendor profile is incorrect, the vendor can also claim their listing and provide corrections through the vendor portal.
Research, Database & Intelligence
Questions about how CyberSanso researches, verifies, and organises the intelligence it publishes — and how to make the most of the vendor database, CVE tracker, and comparison tools.
Vendor profiles are built from publicly available sources including company websites, regulatory filings, press releases, and verified third-party data. Where CyberSanso cannot independently verify a specific claim — such as a privately held company's revenue — that figure is either omitted or clearly attributed to a named external source. Vendors can claim their profile and provide corrections, but editorial control remains with CyberSanso.
CVE stands for Common Vulnerabilities and Exposures. A CVE is a publicly disclosed security vulnerability assigned a unique identifier by MITRE and scored for severity using the CVSS scoring system by NIST's National Vulnerability Database. The CyberSanso CVE tracker pulls data directly from the NVD API, updated daily, allowing you to search by CVE ID, vendor, keyword, or severity level without wading through raw NVD data.
G2 and Gartner Peer Insights collect user reviews and star ratings from verified customers. CyberSanso focuses on structured vendor intelligence — market positioning, product category, funding history, and technical capabilities — rather than crowd-sourced satisfaction scores. The two approaches complement each other: CyberSanso tells you what a vendor does and how it fits in the market, while review platforms tell you whether real users like it.
Yes. The CyberSanso vendor database includes vendors from across North America, Europe, Asia-Pacific, and other regions. While US market coverage is deepest given the concentration of cybersecurity vendors there, the database includes significant coverage of UK, Israeli, German, Indian, and Australian vendors among others. You can filter by region in the vendor database to narrow results by geography.
CyberSanso's Attack Types and Techniques section covers the major MITRE ATT&CK tactics and techniques in plain language — explaining what each technique does, how defenders typically detect it, and which security tool categories are most relevant to defending against it. This is designed as a reference for practitioners and non-technical security stakeholders alike, not a replacement for the full ATT&CK matrix itself.
Use the Vendor Database to locate each vendor's individual profile, then use the Compare feature to view both profiles side by side across category, platform support, company size, funding stage, and key capabilities. The comparison view is available on both vendor profile pages and through the SaaS Comparisons section for tools that overlap between cybersecurity and SaaS categories.
Understanding Cyber, AI & SaaS Concepts
Plain-language answers to common technical questions about cybersecurity, artificial intelligence, and SaaS — including concepts that come up often but are not always well explained elsewhere.
EDR (Endpoint Detection and Response) monitors and responds to threats on individual devices. XDR (Extended Detection and Response) expands that coverage across endpoints, network, cloud, and email in a single correlated view. MDR (Managed Detection and Response) is a service where a third-party team operates detection and response on your behalf, built on top of either EDR or XDR technology. MDR is about who manages the tooling; EDR and XDR are about what the tooling covers.
Zero trust is a security model built on the principle that no user, device, or system should be trusted by default — even if it is inside your network. Every access request must be verified, authorized, and continuously validated. It matters increasingly because the traditional network perimeter, where everything inside was trusted, no longer reflects how businesses actually operate. Remote work, cloud services, and third-party access have dissolved that perimeter, and zero trust is the architectural response.
Ransomware-as-a-service (RaaS) is a criminal business model where ransomware developers lease their malware and supporting infrastructure to other attackers in exchange for a share of ransom proceeds. It has dramatically lowered the technical barrier to launching ransomware attacks, allowing non-technical criminals to conduct sophisticated attacks by paying for tooling rather than building it. This is a key reason why ransomware attack volumes continue to grow even as individual criminal groups are disrupted.
The EU AI Act is the European Union's comprehensive regulation for artificial intelligence systems, which reached full enforcement in 2026. It applies to any organization that develops, deploys, or uses AI systems within the EU, including non-EU businesses whose AI systems affect EU residents. The Act classifies AI systems by risk level, with high-risk applications such as credit scoring, hiring tools, and law enforcement AI facing the most stringent requirements around transparency, testing, and human oversight.
Shadow AI refers to the use of AI tools by employees without IT or security team knowledge or approval — the AI equivalent of shadow IT. It is a rapidly growing compliance and security risk, since employees using unauthorized AI tools may be entering sensitive business, customer, or regulated data into systems the organization has never reviewed for privacy or security. A basic AI use policy that defines which tools are approved and what data can be entered into them is now a standard security practice for any business using AI.
Retrieval-augmented generation (RAG) is an AI architecture that connects a language model to an external knowledge source — such as a company's documents, database, or knowledge base — at the time a question is asked. Instead of relying only on what the model learned during training, a RAG system retrieves relevant information first, then generates an answer grounded in that retrieved content. This significantly reduces hallucinations for domain-specific questions and lets organizations build AI tools that answer from their own data without retraining the underlying model.