SEE EVERYAI AGENT.GOVERN EVERYDECISION.
Discover every autonomous AI agent, see which ones touch sensitive data, and govern the risk — deterministically. AgentShadow leads, powered by the Valo platform's deterministic scoring core and correlation engine.
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- tools · one platform
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- correlation engine
- 0—100
- deterministic score
Detects agent frameworks, LLM stacks, and SaaS across your estate
AgentShadow leads. The platform powers it.
AgentShadow is the flagship. LLMShadow, SaaSShadow, and Valo Core run beneath it as supporting engines on one deterministic scoring core. Select a tool to open its live console.
Govern every AI agent running across your org.
AgentShadow discovers, inventories, risk-scores, reports on, and governs the AI agents in your codebase and your cloud - by scanning source for agent frameworks and pulling from runtime connectors, then scoring each agent deterministically against your governance policies.
Reaches production CRM data through a standing credential.
AI expanded your attack surface faster than you can see it.
Autonomous AI agents, agentic workflows, and machine identities now act with real credentials — the AI you build and the AI you buy both create risk your existing tools were never designed to measure. Four blind spots, one platform.
Autonomous agents nobody registered
Engineers ship LangChain, CrewAI, and AutoGPT agents with real credentials and tool access. Security never sees them until one goes wrong.
LLM code that ships secrets
Hardcoded provider keys, unsafe prompt construction, and vulnerable AI dependencies slip through review and into production repos.
SaaS-to-SaaS integrations gone rogue
Over-permissioned OAuth grants and stale tokens create data-flow paths between apps that no CASB or SSPM was built to see.
Malicious inputs reaching your models
Prompt injection, jailbreaks, and data-exfiltration attempts hit AI features directly, with no deterministic way to score or block them.
You inventory every employee. You can't see your AI workforce.
Autonomous AI agents and machine identities now act with employee-level access — but no badge, HR record, or offboarding tracks them. AgentShadow inventories the AI workforce you can't see.
Four signals. One incident.
Every tool signs and ships its findings to one tool-agnostic engine. It joins them by canonical entity — so three separate "mediums" collapse into a single, provable attack path.
Hardcoded OpenAI key in payments/service.py
Agent billing-copilot loads this credential at runtime
Same key authorizes a Salesforce → Slack OAuth grant
billing-copilot can exfiltrate CRM data through a leaked key.
Discover, understand, control — then correlate.
The same four-step pipeline runs under every tool, ending in a branded PDF assessment and a live cross-tool asset graph.
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Discover
Scan source code and pull from runtime & SaaS connectors to inventory every agent, LLM call, integration, and AI input across your estate.
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Understand
The shared deterministic engine assigns a reproducible 0-100 risk score with a transparent, CVSS-aligned per-dimension breakdown you can actually read.
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Control
Evaluate each asset against editable YAML policies for an allow / review / block verdict - in monitor mode or inline enforcement.
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Correlate
Every finding feeds one asset graph, so a leaked key in code links to the agent that uses it and the SaaS grant it unlocks.
Built for teams who need evidence, not vibes.
Every finding is deterministic, reproducible, and backed by transparent evidence — ready for security reviews, executive reporting, and audits. Every design decision favors transparency, reproducibility, and control: the things that survive a real audit.
Deterministic scoring
The same input always yields the same 0-100 score. No LLM-graded black boxes — every number is reproducible and defensible in audit.
Self-hostable, Docker-first
Run the whole platform in your own environment with open-source community editions. Your code never leaves your network.
Non-invasive by design
Static scanning and pull-based connectors mean nothing sits in your production request path unless you enable enforce mode.
One core, four tools
A shared rule engine, scoring core, and correlation graph. Adopt one product or all four.
Editable YAML rules
Tune detection and policy in plain YAML with hot-reload. Your team owns the logic, not a vendor's model.
Standards-aligned
Findings map to OWASP LLM Top 10, MITRE ATLAS, and CVSS v3.1 — the language procurement already trusts.
Questions, answered.
Valo Security is a platform of four AI-security tools that share one deterministic scoring core and one correlation engine. AgentShadow is the flagship and governs autonomous AI agents and machine identities, LLMShadow scans code for risky LLM usage, SaaSShadow maps SaaS-to-SaaS integration risk, and Valo Core scores AI inputs. Together they cover the AI you build and the AI you buy.
Talk to Valo Security.
Reach the right team directly. Pick the mailbox that matches your inquiry and we'll route it from there.
General inquiries
For general inquiries, product information, speaking opportunities, media requests, and questions about the Valo Security Suite.
info@valosecurity.aiPartnerships
For design partner applications, technology integrations, strategic alliances, reseller opportunities, and business development inquiries.
partners@valosecurity.aiSecurity
For security research and product security questions.
security@valosecurity.aiYou can't govern AI you can't see.
Discover every AI agent in minutes. Start with AgentShadow and a live map of the agents running in your org, then extend across the full Valo Security platform.