AI-SPM
AI posture to action. Every agent, MCP server, model, and dataset discovered in code. Mapped to your architecture, governed before it becomes a production risk.
https://www.paloaltonetworks.com/blog/2025/06/genais-impact-surging-adoption-rising-risks/
Narrow tools flag AI issues in isolation, disconnected from APIs, secrets, and data flows. Another scanner, another backlog, no risk picture.
Palo Alto Networks, 2025
AI Discovery
No accountability
890%
Unapproved frameworks and models blocked at the pull request. Every AI component tied to a business service and an accountable owner, with audit-ready, code-based evidence.
Explore the Data Fabric that powers it →
Shadow AI sprawl
Guardian Agent
Same finding: a Hugging Face client detected in code. Opposite risk reality. Both verdicts are possible only with architectural context in the Software Graph. Cloud-only tools never see the code. Siloed AI scanners can't rank either.
AI BOM
Guardian Agent
Escalated: internet-exposed service, PII flows to model, unsanitized output
Cloud scanners see AI only after deployment. The risk was born at design and code, weeks earlier, and has already shipped by the time it's found.
Who approved the model, which service depends on it, and who owns the fix stays a manual hunt. Inventory without ownership governs nothing.
What AI-SPM delivers
Risk Correlation
Toxic combinations decide priority: a GenAI framework next to a sensitive API and a PII flow is critical. The same framework in a sandbox is noise. The Risk Graph tells them apart.
Governance
AI enters through code: a prompt, a pip install, an MCP config. GenAI traffic surged 890% in a single year while data loss incidents jumped 250%. Tools that watch deployed cloud services discover AI weeks after the risk was born. Four systemic failures follow.
Read: why GenAI security is the AppSec blind spot →
Threat Modeling
Read: introducing AI Threat Modeling →
Focus on real risk
How AI-SPM works
Why siloed tools flag it: the framework matches, so the alert fires at the same severity. The Software Graph proves no sensitive data, no exposure, and no production deployment. Apiiro deprioritizes it with evidence, and your team works the payments API instead.
Every AI agent, MCP server, model, and dataset mapped into your Software Graph
Read: secure and govern your AI early →
Unsanctioned frameworks, models, and MCP servers enter through commits and transitive dependencies. No review, no inventory, no governance.
Every prompt, plugin, and model expands the attack surface. Adoption has outpaced AppSec readiness, and the blind spot grows with every commit.
One GenAI framework. Two verdicts.
Siloed AI scanners
You can't govern what you can't see. Apiiro inventories every AI component at the source, continuously, with code-to-runtime context.
Apiiro AI BOM
https://apiiro.com/blog/secure-and-govern-your-ai-early-before-it-becomes-a-production-risk/
Cloud AI-SPM tools see deployed services. Guardian Agent sees where AI is born: the code. It reasons over your Software Graph and Risk Graph like an AppSec engineer: discovers every AI component on every commit, maps how it touches APIs, secrets, and sensitive data, and governs it from the first prompt to production.
AI Threat Modeling extends AI-SPM upstream to the design phase: prompt injection, insecure outputs, and excessive agency surfaced as threats with mitigations on new features, before a single line is written.
Cloud-only AI-SPM was built for yesterday's AI
Deprioritized: research sandbox, public data, never deployed
Five capabilities secure AI from the first commit to production: automated, continuous, at enterprise scale.
20%
Stanford study
Discovered too late
Of breaches involved shadow AI, adding $670K to average breach costs
AI security shifts from discovering AI in production to governing it at the source. Three outcomes follow.
AI posture to action. Every agent, MCP server, model, and dataset discovered in code. Mapped to your architecture, governed before it becomes a production risk.
Prevent AI risks before code exists
https://techcrunch.com/2022/12/28/code-generating-ai-can-introduce-security-vulnerabilities-study-finds/
More security flaws introduced by engineers using AI coding tools
Why siloed AI scanners can't fix it: they flag a framework, full stop. Apiiro correlates it with the sensitive API and the PII flow in the same service, confirms attacker reachability code-to-runtime, escalates to Critical, and assigns the code owner with the fix.
40%
Surge in GenAI traffic in a single year
1 graph
Govern at the source
AI-SPM
https://www.ibm.com/reports/data-breach
AI is entering your codebase faster than you can see it
IBM Cost of a Data Breach 2025
AI agents, MCP servers, GenAI frameworks, models, datasets, and AI-related secrets inventoried from code on every commit. Shadow AI surfaced before it ships.