[Blog](/blog) Show links Resources [Blog](/blog) [Breaches](/breaches) [eBooks, reports, & more](/resources) [Events](/events) [News](/news) [Human Cyber Risk](/category/human-cyber-risk) Show links Categories [Attack Surface Management](/category/attack-surface-management) [Company News](/category/company-news) [Compliance and Regulations](/category/compliance-and-regulations) [Cybersecurity](/category/cybersecurity) [Data Breaches](/category/data-breaches) [DevOps](/category/devops) [Human Cyber Risk](/category/human-cyber-risk) [Risks and Vulnerabilities](/category/risks-and-vulnerabilities) [Third-Party Risk Management](/category/third-party-risk-management) [Vendor Risk Management](/category/vendor-risk-management) [Human Risk Management Platforms: How to Choose the Right Software](/blog/best-human-risk-management-platforms) Publish date August 31, 2026 {x} minute read # Human Risk Management Platforms: How to Choose the Right Software [Get a demo](/contact-sales) [Free trial](/demo) [Download the PDF guide](/resources/the-state-of-shadow-ai) [Free trial](/demo) Written by [Shane Moosa](/team/shane-moosa) Content Writer Shane is a cyber writer with a software development background. Reviewed by [Kaushik Sen](/team/kaushik-sen) Chief Marketing Officer Kaushik has a background in software engineering, enterprise solution architecture, and data analytics. He brings a unique, data-driven perspective to cybersecurity education. Table of contents Report The State of Shadow AI - Trends, Insights & Statistics Free resource ### The State of Shadow AI - Trends, Insights & Statistics [Download now](/resources/the-state-of-shadow-ai) Security leaders can no longer treat workforce cyber risk as a quarterly phishing campaign. Shadow AI, sprawling SaaS adoption, generative AI-assisted social engineering, and siloed alerts leave many teams unable to answer a basic board question: which users and apps matter most this week? Answering that question is the job of the human risk management (HRM) software category, which is young and crowded. Security awareness vendors, email security vendors, and identity platforms have all repositioned into it, which means two products with near-identical marketing can solve completely different problems. In the following sections, we cover what these platforms do, how the leading options differ, and which approach fills the gaps in your HRM program. ## What is a human risk management platform? Human risk is the cyber exposure that workforce behavior and decisions create: application misuse, susceptibility to social engineering, unsafe tool choices, and policy shortcuts under pressure. A human risk management platform scores workforce-driven risk — phishing susceptibility, unsafe SaaS and AI usage, credential exposure, policy violations — and gives you the controls to bring it down. That scope is broader than adjacent controls. Security awareness training (SAT) delivers episodic education and often measures completion. Email security gateways filter inbound threats; they don't inventory how people use apps outside the mail path. Identity and access management risk signals catch sign-in anomalies, not unsanctioned app usage outside single sign-on (SSO). The platforms that earn the category name close the loop by identifying, prioritizing, enforcing, coaching, then measuring whether the risk needle has moved. Training can still be an input, but it isn't the whole product. ## Why human risk management matters in 2026 The operating environment has stacked several pressures at once. Remote and hybrid work expanded SaaS sprawl. Employees adopted generative AI faster than most security teams could approve tools (the Shadow AI problem), and attackers scaled personalized phishing and impersonation to match. Meanwhile, security stacks kept emitting alerts from email, endpoint, identity, and SaaS tools that rarely resolve into a single user or team priority list. For security leaders and program owners, the job is no longer only "run awareness." Boards want evidence that you measure human-layer risk and that it's moving, as the costs associated with human risk are on the rise. [IBM's 2026 Cost of a Data Breach report](https://www.ibm.com/think/x-force/2025-cost-of-a-data-breach-navigating-ai) found that security incidents involving Shadow AI reached 43% this year, more than double the previous year's share, at an average cost of $5.39 million. Resource-constrained teams need to know where to intervene first, and these three gaps show up over and over: * **Visibility gap:** Signals sit in separate tools, so no one sees the full user-and-app picture. UpGuard's [Shadow Supply Chain](https://www.upguard.com/resources/user-risk-supply-chain) research found that 31.4% of vendor interactions happen through direct browser access, producing no identity log. * **Measurement gap:** Teams treat training completion as success even when behavior doesn't change. * **Enforcement gap:** Policies exist on paper, but there's little control when someone pastes data into an unapproved AI tool. The scale is not marginal. UpGuard's [State of Shadow AI](https://www.upguard.com/resources/the-state-of-shadow-ai) report found that 81% of employees and 88% of security leaders use AI tools their employer hasn't approved, and 45% of workers find workarounds when those tools are blocked. [Verizon's 2026 Data Breach Investigations Report](https://www.verizon.com/business/resources/reports/2025-dbir-data-breach-investigations-report.pdf) found the human element present in 62% of breaches, up from 60% the year before. After a decade of awareness investment, the number is still climbing. That gap is why leaders are consolidating point solutions into platforms that score users continuously and connect findings to action. For deeper category framing, see why [human risk management is important](https://www.upguard.com/blog/why-human-risk-management-is-important) and the [user risk puzzle](https://www.upguard.com/blog/the-user-risk-puzzle). ## Key features to evaluate in human risk management software Before you compare logos, decide what "good" looks like. The market still mixes true continuous risk platforms with SAT products that added a score and new branding. Use these criteria to assess any platform on your list: * **Unified risk scoring:** Prefer one score that rolls up cleanly from user to team to organization, fed by multiple signals, over disconnected module metrics that never add up to anything. * **Continuous detection:** Look for ongoing behavioral and usage signals, not quarterly phishing tests alone. * **Shadow app and AI visibility:** Confirm that discovery covers non-SSO SaaS and AI, including tools employees only ever touch in the browser. Those never appear in your identity directory, so ask the vendor how they get detected. * **Prioritization and coaching:** Check for ranked action plans and real-time nudges at the moment of risk, rather than a raw alert firehose and an annual video. * **Governance and policy:** App usage rules should support clear states such as approved, blocked, nudged, and tolerated, with role and team exceptions layered on top. * **Identity breach correlation:** Compromised credentials should map to active employees rather than sit in a separate dark web report. * **Validation and reporting:** Closed-loop metrics should show risk reduction, not enrollment counts, and dashboards must support board and audit conversations without a week of spreadsheet work. For more on closing blind spots, see [closing the visibility gap](https://www.upguard.com/blog/closing-the-visibility-gap) and how teams [automate governance and prioritize action](https://www.upguard.com/blog/automate-governance-prioritize-action). ## Best human risk management platforms Use this list as a shortlist starting point. Each entry names who it's best for, then covers strengths and trade-offs. We've ordered them by approach, not by rank: visibility- and governance-first, training-first, email-centric, then identity-native. Analyst coverage has also moved: [Forrester's Human Risk Management framing](https://www.forrester.com/blogs/the-future-is-now-introducing-human-risk-management/) treats the category as distinct from legacy security awareness and training. ### 1. UpGuard User Risk **Best for:** Visibility-led programs UpGuard User Risk is the human risk management product inside UpGuard's cyber risk posture management platform. Vendor Risk and Breach Risk manage exposure from the outside in, across your supply chain and attack surface. User Risk works from the inside out, across your workforce. A browser extension discovers Shadow SaaS and Shadow AI, along with the permissions employees have granted to connected apps. User Risk then correlates identity breach data against your current employee list. An AI Analyst then ranks the riskiest users and behaviors. Policy runs on four states — Approved, Blocked, Nudged, and Tolerated — with role and team rules layered on top, and those policies drive browser-level enforcement at the moment of action. **Pros:** * Discovers non-SSO app usage that SSO catalogs and network logs miss, including apps employees sign into with personal credentials, and surfaces Microsoft Entra-approved apps in the same inventory * Browser-level controls that fire under each app's policy: paste blocking on risky sites, file upload blocking, and personal account sign-in blocking. Alongside these, UR tracks OAuth grants, non-SSO sign-in attempts, and credential breach exposures. * Cross-references every discovered app against Vendor Risk, so a new Shadow SaaS finding immediately shows whether that vendor is already monitored and how it scores. None of the other platforms in this list documents that connection publicly * Four-state policy replaces blunt approve-or-block, so you can be strict with Finance and flexible elsewhere without becoming the "department of no" * One risk score covering app usage, permissions, and breach exposure. It rolls up from the individual user to the whole organization, and daily scans confirm remediation is holding **Cons:** * Not a legacy learning management system (LMS) and doesn't carry the largest off-the-shelf training library * Phishing simulation isn't part of the product. Pair it with a SAT vendor if simulation coverage is a hard requirement [Explore User Risk](https://www.upguard.com/product/user-risk) ### 2. KnowBe4 **Best for:** Training-first programs at scale KnowBe4 is the vendor most buyers still associate with security awareness and phishing simulation, and more recently with a human risk management narrative built on analytics and AI-assisted personalization. **Pros:** * Extensive content library and mature simulation operations * Broad market familiarity for auditors and awareness teams * Strong fit when the primary gap is phishing susceptibility and training coverage **Cons:** * The center of gravity remains SAT even as HRM features expand * Less emphasis on Shadow AI discovery and browser enforcement than visibility-first platforms ### 3. Mimecast Human Risk **Best for:** Email-centric stacks already on Mimecast Mimecast extends email security into human risk, pairing awareness content with behavioral signals and threat context drawn from the mail channel. **Pros:** * Natural fit for organizations standardized on Mimecast email security * Useful when human risk prioritization should reflect real email threat pressure * Bundled procurement cuts your vendor count **Cons:** * The story remains primarily email-behavior and awareness oriented * Standalone HRM depth may lag purpose-built visibility platforms outside the Mimecast ecosystem ### 4. Hoxhunt **Best for:** Engagement-led phishing resilience Hoxhunt is known for gamified, adaptive phishing training and high reporting engagement, with human risk framing built around behavior change metrics. **Pros:** * Strong user engagement model and adaptive simulation difficulty * Clear focus on reporting behavior and measurable phishing resilience * Good option when culture and habit change around social engineering is the top priority **Cons:** * App-level governance and Shadow SaaS inventory aren't the core narrative * Broader workforce risk beyond phishing will need complementary tools ### 5. Living Security **Best for:** Culture programs and enterprise signal aggregation Living Security positions itself as an AI-native human risk platform that unifies behavioral and security-stack signals, then layers personalized interventions and culture-oriented training on top. **Pros:** * Emphasizes correlated risk signals beyond training completion * Strong story around predictive interventions and engagement formats * Attractive for enterprises investing in cross-stack human risk indexes **Cons:** * Value depends heavily on integration maturity and security-stack breadth * App-level governance depth isn't publicly documented. Ask for a walkthrough in the demo. ### 6. usecure **Best for:** Small and mid-market SAT automation with a risk score usecure packages personalized training, phishing, policy attestation, and credential monitoring into a human risk score with low administrative overhead. **Pros:** * Practical operating model for teams without dedicated human risk staff * Includes policy acknowledgment and dark web credential monitoring alongside training * Transparent mid-market positioning **Cons:** * Closer to automated SAT plus scoring than full Shadow IT and browser governance * Enterprises needing deep non-SSO AI control should validate discovery limits ### 7. Guardey **Best for:** Small-business gamified awareness Guardey uses short weekly challenges and competition mechanics to drive participation in security awareness, with lightweight risk visibility for admins. **Pros:** * High engagement format for time-constrained employees * Lightweight administration and a phishing simulation add-on * Approachable for smaller organizations building baseline habits **Cons:** * Feature depth for enterprise governance and Shadow AI control is limited * Not a substitute for continuous multi-signal workforce risk platforms ### 8. Proofpoint **Best for:** Email-security-led enterprises Proofpoint ties awareness and people risk insights to its email threat protection business, including tools that highlight highly targeted or susceptible users. **Pros:** * Strong email threat intelligence context for people risk * Enterprise scale and compliance-oriented training options * Useful when human risk prioritization should follow real attacker targeting **Cons:** * Best results typically assume a broader Proofpoint footprint * Engagement and continuous app governance often trail specialized HRM-native tools ### 9. Adaptive Security **Best for:** Multi-channel simulation and emerging deepfake readiness Adaptive Security emphasizes behavioral risk scoring and realistic simulations across email, SMS, voice, and deepfake-style scenarios. **Pros:** * Forward-leaning coverage of voice and deepfake social engineering * Risk scoring tied to simulation and behavior outcomes * Useful for preparing executives and finance teams for impersonation pressure **Cons:** * Newer market presence than long-standing SAT incumbents * Simulation breadth doesn't translate into app or AI governance, so discovery still has to come from elsewhere ### 10. Microsoft Entra ID Protection and Defender **Best for:** Identity-native Microsoft estates Microsoft's identity protection and Defender capabilities provide native risk signals inside Microsoft environments, covering sign-in anomalies and compromised credentials alongside endpoint-linked detections. **Pros:** * Deep integration for Microsoft-centric identity and endpoint stacks * Strong starting point for identity threat detection and response * Efficient when most workforce apps already sit under Entra SSO **Cons:** * Limited view of non-SSO Shadow SaaS and consumer AI tools without complementary controls * Not a full human risk management platform on its own for browser-level AI governance. If AI is the driver, review [dedicated AI governance platforms](https://www.upguard.com/blog/best-ai-governance-platforms) alongside it. ## Human risk management platform comparison table Every rating below comes from each vendor's own public documentation and analyst coverage as of August 2026. These ratings are directional strengths drawn from public positioning and don't reflect hands-on testing. Scope in this category shifts fast, so check current product documentation before you commit. Use the table to build a shortlist, then pressure-test the rest in a demo. | Platform | Primary focus | Unified user-level risk score | Shadow SaaS and AI visibility | Policy enforcement | Phishing and SAT | Identity breach correlation | Executive reporting | | ---------------------------- | ------------------------------ | ----------------------------- | ----------------------------- | ------------------ | ---------------- | --------------------------- | ------------------- | | UpGuard User Risk | Visibility and governance | Strong | Strong | Strong | Not a focus | Strong | Strong | | KnowBe4 | Training-first HRM | Partial | Limited | Partial | Strong | Partial | Strong | | Mimecast Human Risk | Email-centric | Partial | Limited | Partial | Strong | Partial | Strong | | Hoxhunt | Engagement-led behavior change | Partial | Limited | Limited | Strong | Limited | Strong | | Living Security | Culture and signal aggregation | Strong | Partial | Partial | Strong | Partial | Strong | | usecure | Automated SAT and score | Partial | Limited | Partial | Strong | Strong | Strong | | Guardey | Gamified awareness | Limited | Limited | Limited | Partial | Limited | Partial | | Proofpoint | Email threat and people risk | Partial | Limited | Partial | Strong | Partial | Strong | | Adaptive Security | Multi-channel simulation | Partial | Limited | Partial | Strong | Limited | Strong | | Microsoft Entra and Defender | Identity-native risk | Partial | Limited | Partial | Limited | Strong | Strong | Training-first vendors generally lead on content libraries and simulation breadth. Visibility- and governance-first platforms pull ahead when the question is which apps and AI tools people use, and how you enforce policy in the browser. ## Training-first vs visibility- and governance-first: which do you need? Most shortlists collapse every logo into one HRM bucket. Buyers get better outcomes when they name the gap. Choose training-first platforms such as KnowBe4, Hoxhunt, or usecure when the main problem is phishing susceptibility and low engagement with awareness content. You will also need compliance evidence of training completion. These products excel when your program is still building baseline habits and reporting culture. Opt for visibility- and governance-first platforms such as UpGuard User Risk when leadership can't answer two questions: which apps and AI tools people are using, and which users concentrate the most risk this week. That's the path when SSO inventories feel incomplete, and completion metrics no longer satisfy the board. Many enterprises run a hybrid stack. SAT covers education and simulation, while a workforce risk platform handles discovery and scoring, then enforces the result. Learning-program design still benefits from frameworks such as the National Institute of Standards and Technology's [NIST SP 800-50 Rev. 1](https://csrc.nist.gov/pubs/sp/800/50/r1/final). Continuous scoring and enforcement cover the operational gap awareness alone leaves open. Integration and API quality matter so scores and interventions don't create another silo. If your awareness numbers look good but your risk numbers haven't moved, here's [where security awareness training falls short](https://www.upguard.com/blog/security-awareness-training-isnt-working). Common decision scenarios: * **After a Shadow AI incident:** Prioritize discovery, browser controls, and policy states over another annual course refresh. * **Board asked for human risk metrics:** Opt for unified scoring and executive-ready trend reporting. * **SSO-only inventory feels incomplete:** Ensure you have visibility into non-SSO SaaS and AI. * **Lean team with too many completion reports:** Prioritize ranked actions on the top users and apps first. ## How to implement human risk management successfully A durable rollout is a loop, not a launch event. For the longer version of this sequence, see our [seven-step human risk mitigation framework](https://www.upguard.com/blog/how-to-mitigate-human-risk). Pair platform controls with practical phishing defense habits from the Cybersecurity and Infrastructure Security Agency's guidance on recognizing and reporting phishing, so people and tooling reinforce each other. Here's how to get started in five steps: 1. **Baseline discovery:** Inventory users, apps, AI tools, permissions, and known credential exposures so you know the real starting surface. 2. **Policy definition:** Translate acceptable use into enforceable states for AI and SaaS: what's approved, blocked, nudged, or tolerated. If you're starting from a blank page, UpGuard's free [AI Policy Generator](https://www.upguard.com/tools/ai-policy-generator) drafts a tailored baseline in about five minutes. 3. **Pilot nudges:** Start with high-impact groups and in-workflow coaching before organization-wide enforcement. 4. **Measure score movement:** Track user and team risk trends and repeat policy violations rather than course completion. 5. **Expand rules:** Widen coverage as false positives drop and managers trust the signal. Lean teams should start with the top users and apps rather than covering everything at once. Automate what you can, then widen coverage as trust in the signal grows. ## How UpGuard User Risk reduces workforce risk with continuous visibility If your shortlist prioritizes measurement and control, not another content library, User Risk discovers hidden workforce apps and AI, prioritizes what matters, and intervenes in the browser when risky behavior happens. * **Discover:** Uncover Shadow AI, untracked SaaS, risky app permissions, and breached credentials tied to current employees, including the non-SSO usage that network blockers and identity catalogs miss. * **Prioritize:** Let the AI Analyst rank the users, teams, and apps that need attention first, and cross-reference every discovered app against your monitored vendors in Vendor Risk. * **Intercept:** Block paste attempts and unapproved file uploads into unapproved apps and halt personal account sign-ins at the moment of risk. * **Guide:** Redirect people to approved corporate tools with real-time nudges. * **Govern:** Set Approved, Blocked, Nudged, or Tolerated policy per app, with role and team rules on top, then use daily scans to confirm the risk dropped. [Start a free trial](https://www.upguard.com/demo) to see continuous workforce risk visibility in your environment. ## Frequently asked questions ### What is a human risk management platform? A human risk management platform scores the cyber risk your workforce creates, then gives you the controls to reduce it. That risk includes phishing susceptibility, unsafe SaaS and AI use, credential exposure, and policy violations. It does this through continuous detection and intervention, not training completion alone. The practical test is that if a product can't tell you which 10 users are riskiest today and why, it's a training tool with a dashboard attached. ### How is human risk management different from security awareness training? Security awareness training educates people and usually measures completion. Human risk management measures behavior and exposure continuously, prioritizes the riskiest users and tools, and applies coaching or controls so risk declines over time. Most organizations end up running both: SAT for compliance evidence, HRM for the operational picture. ### What is the best human risk management software? There's no single answer, because these products solve different problems. Choose training-first software when phishing susceptibility and content coverage are the gaps. Prioritize visibility- and governance-first software when you can't answer which AI and SaaS tools people are using, or when your SSO inventory is demonstrably incomplete. ### How do you score human cyber risk? Effective scoring combines several inputs. These inputs can be simulation and real behavior outcomes, app and AI usage, credential exposure, permissions, and policy adherence. They are then combined into risk levels that update as behavior changes, at every level from the individual to the whole organization. Ask vendors how often the score refreshes, and whether remediation is validated automatically or self-reported. ### Can human risk management platforms detect Shadow AI? Platforms with browser-level discovery can find non-SSO AI and SaaS usage and enforce policy against it. Training-only tools generally can't see unsanctioned AI activity outside the learning environment. If AI governance is the main driver, review [dedicated AI governance platforms](https://www.upguard.com/blog/best-ai-governance-platforms) alongside your HRM shortlist. ### How much do human risk management platforms cost? Pricing varies by employee count, modules, simulation volume, and enterprise packaging. Evaluate total cost of ownership, including admin time and integrations, rather than the number on the quote. Deployment model matters too: a browser extension rollout and identity integrations carry different internal costs than standing up an LMS. Report The State of Shadow AI - Trends, Insights & Statistics Free resource ### The State of Shadow AI - Trends, Insights & Statistics [Download now](/resources/the-state-of-shadow-ai) ## Related posts Learn more about the latest issues in cybersecurity. Human Cyber Risk #### [Best Shadow AI Governance Tools for Enterprises: Buyer's Shortlist](/blog/best-shadow-ai-tools) Compare top shadow AI governance tools for enterprises, covering key capabilities and how to shortlist the right platform for your organization. [](/team/shane-moosa) [Shane Moosa](#) September 7, 2026 Human Cyber Risk #### [AI Assurance: The Third Head of Your AI Governance Watchdog](/blog/ai-governance-to-ai-assurance) AI governance needs three things: policy, enforcement, and assurance. Most organizations have built the first two. Here's why the third one matters now. [](/team/shane-moosa) [Shane Moosa](#) September 21, 2026 Human Cyber Risk #### [How to Mitigate Human Risk in Cybersecurity: A Practical Framework](/blog/how-to-mitigate-human-risk) Security awareness training alone isn't human risk management. Use this seven-step framework to discover, govern, and coach workforce behavior. [](/team/shane-moosa) [Shane Moosa](#) August 25, 2026 Human Cyber Risk #### [Best AI Governance Platforms and Software (2026 Comparison)](/blog/best-ai-governance-platforms) Compare the top AI governance platforms of 2026 and find the right fit for your workforce and compliance needs. [](/team/shane-moosa) [Shane Moosa](#) August 10, 2026 Human Cyber Risk #### [The Architecture of an AI-Powered Breach: The Shadow Supply Chain](/blog/ai-powered-breach-and-the-shadow-supply-chain) Decode three real-world AI breaches. Learn how Shadow AI pipelines bypass security and how real-time browser guidance can stop data leaks. [](/team/shane-moosa) [Shane Moosa](#) July 6, 2026 Human Cyber Risk #### [Decoding the Copilot Ecosystem](/blog/the-copilot-ecosystem) Don't let Copilot extend its permission sprawl. Learn the structural risks of M365 and GitHub Copilot, and how to enforce real-time browser guardrails. [](/team/shane-moosa) [Shane Moosa](#) August 25, 2026 [All posts](/blog) Experience superior visibility and a simpler approach to cyber risk management [Get a demo](/contact-sales) [Free trial](/demo)