AI Agent Exposure Management | Zenity AI Security Platform
Predicting Agent Risk Isn’t the Same As Proving It
Zenity's AI Exposure Management validates which agents an attacker could actually exploit and prioritizes the risk so teams know where to focus
Recognized by
Seeing Agents Isn’t the Same As Knowing Risk
Traditional exposure management was built for infrastructure, identities, endpoints, and cloud assets, resources whose risk lives mostly in how they're configured. AI agents break that model.
Zenity correlates identity, data, and behavior signals into complete attack paths, then validates what’s actually reachable. Each proven path contains a risk score and a fix ready to apply in Boundaries, Zenity's runtime policy rules, that allow, modify, or block what an agent does, so teams are closing real business risk instead of chasing noise.
Proven Then Prioritized
When every issue is validated, security teams stop spending time on findings that might not even be real. Instead of triaging thousands of raw misconfigurations, teams work a short, ranked list of paths that are actually exploitable today, each with a defensible score and a fix already mapped to it.
Less noise, more signal
The default view shows only complete, exploitable paths, not every configuration finding that could theoretically go wrong, so what appears is always worth acting on.
A score teams can defend
Every issue gets a risk score from 0 to 100 with a clear severity: critical, high, medium, or low. The same input always produces the same score, so prioritization holds up when leadership or an auditor asks why.
Remediation in minutes, not weeks
Every issue ships with a fix already mapped to a specific step in the chain, ready to apply in Boundaries without opening a developer ticket.
How a Raw Signal Becomes a Proven Fix
CoverageDetectionIntelligenceRemediation
One risk language for every platform
A misconfigured identity in Salesforce and a misconfigured identity in Azure look identical to an attacker. Zenity normalizes every agent into a consistent risk language.
Key Features
- Canonical detection IDs: The same violation maps to the same ID on every platform, so severity comparisons hold up across environments.
- Unified agent profile: See platform, creator, permissions, identities, and behavior for any agent in one place, in under two minutes.
- Identity from Entra ID and Okta: Every agent's assumed identities are pulled in, with managed status and privilege, and mapped to the OWASP Non-Human Identity Top 10.
- Cross-platform attack paths: A chain can span integrations, so a Copilot Studio agent that hands off to an Amazon Bedrock agent is one clear path, not a blind spot.
Find the Path Before It’s an Incident
AI Exposure Management correlates identity, data, and behavior across every agent platform into complete attack chains, then only surfaces the ones that are reachable end-to-end. The examples below are some of the exposure types commonly found live in production, not a theoretical risk.
AI Agent Exposures We Regularly Find:
Data exfiltration via untrusted trigger
An agent ingests untrusted input, like an email, a webform, or a ticket, and that same tainted context flows into a sensitive data pull and out through an external send.
Cross-agent data poisoning
One agent writes untrusted content into a shared system; a second agent reads it as trusted and acts on it, including destructive actions like delete or reassign.
Privileged action by untrusted trigger
A delete, modify, or write executes while untrusted external content is still in the agent's scope.
Credential access through agent
An agent passes secrets, tokens, or API keys to a destination or log influenced by untrusted input.
Sensitive data crossing tenant boundary
PII, financial, or regulated data leaves an approved region, tool, or tenant.
Records exfiltrated to an out-of-policy destination
An agent reads CRM or ticketing records and writes them somewhere outside approved policy.
Trusted by Forward-Looking Security Leaders
“With Zenity we were able to build a program to remediate existing vulnerabilities with a product that relies on self service and auto-fix so we can scale.”
Fortune 20 Technology
90%
Existing vulnerabilities remediated within 4 months with 2 FTEs
Fortune 20 Technology
280%
Tenant grew over 12 months
Fortune 20 Technology
“We needed a way to partner with the business. Zenity gives us confidence to continue enabling our employees to innovate with AI Agents and applications.”
Fortune 50 Pharmaceuticals
82%
People developing these systems are not professional developers
Fortune 50 Pharmaceuticals
2,000
Instances of agents and apps that were shared across the entire org
Fortune 50 Pharmaceuticals
"Zenity provided a preventative layer to proactively reduce security violations of our Agentic AI use. As a result, we saw tremendous growth in cross-departmental adoption of AI Agents."
Fortune 200 Consulting
90%
Reduction in security violations
Fortune 200 Consulting
95%
High-risk violations automatically remediated
Fortune 200 Consulting
"With Zenity, we identified and managed risks from a huge attack surface containing over-shared resources that had access to sensitive data, DLP bypass routes, and misconfigured AI Agents."
Fortune 50 Financial Services
80%
Risk reduction across the tenant containing 150k+ total resources
Fortune 50 Financial Services
180%
Growth in agent, app, and automation volume
Fortune 50 Financial Services
Analyst Recognition & Research Coverage
Gartner Securing Agent Actions Not Prompts White Papers
Gartner® Names Zenity as the Company to Beat in AI Agent Governance Company News
Zenity Named Gartner® Cool Vendor in Agentic AI TRiSM
Start Securing Your AI Agents Today
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