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A useful free cyber risk assessment connects four things that are often reviewed separately: what is exposed to the internet, who can access it, what AI browsers and agents can do with it, and how SaaS providers handle the data. Start with inventories, trace the paths between them, prioritize risks by potential impact and likelihood, and give every finding an owner and review date. The result is a practical first-pass risk register—not proof that every vulnerability or hidden service has been found.
What should a free cyber risk assessment include?
Assess the systems and relationships that let people, software, and external services reach your data. Include browser activity and AI agents alongside conventional infrastructure: an agent may read an exposed page, use a connected account, and take an action through a SaaS service. Reviewing those pieces in isolation can miss the path between them.
- Assets and entry points: public IP addresses, domains, remote-access services, cloud consoles, APIs, SaaS applications, browser extensions, AI agents, plugins, and connectors.
- People and identities: users, administrators, service accounts, third parties, authentication and recovery methods, federation, and privileged roles.
- Data and activity: what data is accessed, where it flows, which actions are permitted, and what is retained or logged.
- Threats and controls: plausible misuse or compromise paths, existing safeguards, gaps, accountable owners, target dates, and accepted residual risks.
Keep assumptions visible. A free review can identify known assets and obvious control gaps, but it cannot establish that an undocumented shadow SaaS service does not exist or fully characterize a closed-source AI model’s behavior.
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Build an inventory from the sources available to your organization, such as asset records, cloud consoles, domain records, remote-access configurations, and SaaS administration pages. Record what is reachable from the internet and why it needs to be reachable. CISA’s Internet Exposure Reduction Guidance, published June 4, 2025, warns: “Many organizations unknowingly leave common vulnerabilities and weaknesses exposed to the internet, making them easy targets for exploitation.”
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For each exposed item, capture its owner, purpose, access path, data or process at risk, and whether public access is necessary. Then check whether unnecessary exposure can be removed and whether remaining access is protected and monitored. CISA recommends mitigating retained exposure with patching, changed default passwords, monitored access, MFA, and traffic monitoring, then repeating the assessment routinely.
- Look for forgotten test or administrative services, public cloud consoles, externally reachable APIs, and SaaS sign-in routes.
- Confirm that exposed systems have an accountable owner and a business reason to remain reachable.
- Record unknown ownership or purpose as a finding to investigate, not as evidence that the asset is safe.
How should I assess identity and weak MFA?
Map the full identity journey rather than checking only whether a login prompt exists. Include how identities are established, authenticated, federated across services, granted privileged access, recovered after lockout, and extended to vendors or other third parties. For each path, note the account type, privilege level, authentication method, recovery route, and systems or data it can reach.
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NIST’s Digital Identity Risk Management process asks organizations to identify affected entities, impact categories, and impact levels. Relevant consequences include unauthorized access, financial loss or liability, reputational damage, and safety harms. NIST SP 800-63 Revision 4, finalized in July 2025, is the current revision identified here and updates guidance on risk management, fraud, and continuous evaluation.
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Is my AI browser agent safe?
Do not treat a browsing agent as safe merely because it is built into a browser or uses a known model. Assess the entire system: model, browser extension, agent, plugins, connectors, data sources, and permitted actions. Web pages, images, comments, and documents can contain untrusted instructions. The 2025 paper The Hidden Dangers of Browsing AI Agents describes prompt injection as an end-to-end threat: hostile page content may steer an agent toward disclosing information or taking an unauthorized action.
For each agent, document what it can read, what information it can send, which accounts or tools it can use, and what actions it can take without confirmation. Then examine whether untrusted content could cross into those capabilities. Useful safeguards identified in the paper include input sanitization, isolation between planning and execution, formal analyzers, and session safeguards. Treat these as design and evaluation areas, not as a guarantee that prompt injection can be eliminated.
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NIST SP 800-218A adds GenAI-specific secure-development tasks for model and system producers and acquirers. OWASP’s GenAI Security Project provides an open risk and framework crosswalk for application teams. Together, these are useful references for lifecycle governance and application-level review; neither replaces an assessment of the particular agent, permissions, and data flows in use.
What SaaS risks should I check?
Make one record per SaaS application, including business owner and purpose, data classification, SSO or federation, OAuth scopes, administrator roles, vendor logging, retention, model-training terms, incident notification, and offboarding. Connect each app to the identities and agents that can access it. A broad OAuth permission or persistent third-party connection can matter as much as a person’s direct login.
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Use the same impact logic as for identity and AI systems: identify affected people, data, business processes, financial exposure, trust or reputation, and potential safety consequences. Review changes to permissions, integrations, terms, or ownership as they occur rather than relying only on an annual inventory. NIST’s identity risk approach supplies a way to think about impact; GenAI development guidance and OWASP’s crosswalk can inform AI-related governance.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do I run the assessment?
- Discover: export or assemble inventories for assets, identities, browser extensions, AI agents, OAuth connections, and SaaS applications. Note the source and date of each inventory so gaps are visible.
- Map people, data, and paths: for each important service or workflow, record who uses it, what data it touches, how access is granted, and what actions are possible. Include the path from web content through an agent to a connected account or SaaS service where applicable.
- Classify impact: identify affected people and data, business processes, financial consequences, trust or reputation effects, and safety implications. State the likely consequence if access is abused or a system is unavailable.
- Assess likelihood and blast radius: give priority to internet-facing systems and high-privilege paths, and consider how far a compromised identity, integration, or agent could reach. Use documented qualitative judgments rather than inventing precise scores unsupported by evidence.
- Check controls: review patching and unnecessary exposure, changed default passwords, MFA, least privilege, session isolation, input handling, logging and detection, backups, and recovery testing. Record what is in place and what has not been verified.
- Assign action and acceptance: give each finding an accountable owner, a remediation date, and a decision on residual risk. If remediation is deferred, record who accepted the risk and why.
- Reassess: repeat the review routinely and after material changes to SaaS, identity, browsers, models, or networks. CISA explicitly recommends routine reassessment of internet exposure.
How should I prioritize findings without pretending to have a precise score?
Compare findings using consistent questions, then explain the judgment in plain language. These dimensions help distinguish a serious risk from a long list of equally weighted technical observations:
| Dimension | Assessment question |
|---|---|
| Exposure visibility | Can the organization identify the asset, account, integration, and path involved? |
| Identity assurance | How are identities established, authenticated, recovered, and federated? |
| Privilege scope | What data or actions can the identity, agent, or integration reach? |
| Data-handling transparency | Are data flows, retention, logging, and model-training terms understood? |
| Prompt-injection resistance | Could untrusted content influence an agent’s decisions or actions? |
| Logging and detection | Would suspicious access or activity be recorded and noticed? |
| Remediation effort | What change is needed, who can make it, and what dependencies could delay it? |
| User friction | What operational burden or workflow change would the control create? |
| Vendor dependency | Which safeguards depend on a provider, and what can the organization verify? |
| Residual risk | What remains after planned controls, and who has authority to accept it? |
A useful finding ties a specific path to a consequence and a corrective action. For example: identify an internet-reachable service or high-privilege integration, explain what an attacker or misdirected agent could access, name the missing safeguard, and assign a person and date to address it. Avoid numerical ratings unless the organization has a defined method and evidence to support the scores.
What should the final risk register contain?
Keep the output actionable and reviewable. A spreadsheet is sufficient for a first pass if each row links an asset or workflow to its people, data, risk, and decision.
- Asset, application, account, agent, or data flow, with inventory source and review date.
- Business owner and affected users, processes, or third parties.
- Data classification, access path, privilege, and permitted actions.
- Threat scenario, potential impact, likelihood rationale, and assumptions.
- Existing controls, evidence checked, identified gap, and proposed remediation.
- Accountable owner, target remediation date, status, and residual-risk decision.
- Next review date and the event that should trigger an earlier review.
What a free first-pass assessment cannot prove
An inventory-based review is a starting point, not an assurance audit. It may miss undocumented assets, shadow SaaS, unrecorded integrations, or behavior that cannot be observed in a closed-source model. A paper review of controls does not by itself prove they work under attack. Record these limits in the risk register, seek authorization before testing systems, and use deeper technical or vendor assessments where the potential impact warrants them.
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