AI agents make decisions. APIs execute them. AppSentinels secures the business logic behind every AI action with a Business Logic Graph that maps and governs every agent, tool, API, and data interaction in real time.

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The Attack Surface Just Became Autonomous

Your APIs can now be exploited by AI agents faster and at greater scale than human attackers, often without triggering the signals your security tools rely on. The real risk is when an over-privileged or manipulated agent makes fully authorized requests that violate your business logic and intent.

The old threat model
Human-driven API abuse
  • Slow, detectable request patterns
  • Anomalous user-agent or IP signals
  • Volume-based rate-limit triggers
  • Session behavior deviations

Legacy WAFs and rate limiters were built for this.

The new threat model
AI agent acting on injected instructions
  • Authenticated, structurally valid requests
  • No anomalous IPs; the agent runs inside your perimeter
  • Low volume; logic abuse, not brute force
  • Chains [PT6.1][SP6.2]5–20 calls across tools and APIs to achieve a goal; sometimes the intended one, sometimes not.

Your existing stack sees nothing wrong.

AppSentinels approach
Business logic-aware enforcement
  • Understands expected API sequences & intent
  • Maps agent-to-tool-to-API execution paths
  • Detects deviations regardless of request validity
  • Blocks at the logic layer, inline or OOB

Built for the agentic era from the ground up.

Every Request was Authorized. The Logic Wasn't.

A BOLA flaw in Lovable.dev, a vibe-coding platform with 8M developers, exposed the source code, database credentials, and AI chat histories of every project created before November 2025.

What broke
Authorized; just not for that.
Lovable’s /projects/{id} API verified every caller’s login token, then returned any project’s data, because it never checked who actually owned the object. A textbook BOLA.  
Why the stack missed it
Valid requests, invisible abuse.

WAFs and SIEMs saw well-formed, authenticated calls and waved them through. They’re blind to BOLA, privilege-escalation chains, and intent violations, the logic layer they were never built to see.

Why it matters now
AI ships it faster.

Vibe-coding accelerates a problem business logic has always had. The flaw sat open 48 days; the next one ships at AI speed. Authorization logic needs its own runtime.

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Secure Every Stage of the Agent Lifecycle

AppSentinels covers the full agentic attack surface through four continuous capabilities: the same pillars that secure your APIs, now extended to the agents that drive them.

Continuous Discovery

Inventory every agent, MCP server, tool, and downstream API the moment it appears, including shadow agents spun up by developers and AI assets, custom runtimes, and SaaS platforms.  

The BLG is built from observed behavior, not declared configs.

  • Agent, MCP server, and tool discovery
  • API and object inventory with ownership mapping
  • Bedrock AgentCore, CloudWatch, and control-plane integration
  • Shadow AI and unauthorized tool detection

AI Security Posture Management

Agentic AI environments change continuously. We continuously assess your AI ecosystem for exposed attack paths, risky configurations, excessive privileges, sensitive data exposure, and policy drift across agents, MCP servers, APIs, and LLM interactions.

  • AI, agent, MCP, and API posture visibility
  • Misconfiguration and excessive-permission detection
  • Sensitive data, prompt leakage, and policy drift analysis
  • Continuous compliance against OWASP LLM, API, and internal governance policies

Continuous Red-Teaming

Continuously probe your agents and the APIs they call, looking for prompt injection paths, tool poisoning, missing authorization, privilege escalation chains, and intent violations that emerge only at the logic layer.

  • Agent-specific adversarial testing (prompt injection, jailbreaks, tool abuse)
  • BOLA, BFLA, and business logic abuse simulation
  • MCP and A2A attack surface coverage
  • Pre-production and production-safe modes

Runtime Protection

Enforce ownership, intent, and sequence on every agent action in real time. When an agent’s chain of calls deviates from legitimate workflows, even if every individual request is authorized, we block at the logic layer.

  • Inline or OOB enforcement
  • MCP proxy instrumentation
  • Agent-to-tool-to-API trace correlation
  • Real-time blocking of BOLA, privilege escalation, and intent violations

Secure Every Stage of the Agent Lifecycle

AI agents don't live at the network perimeter. They run inside your Kubernetes clusters, behind your microservice mesh, inside your cloud VPCs. AppSentinels deploys with them and not in front of them.

  • On-premises
  • Deploy inside your perimeter 
  • Complete control of your data
  • Meets data sovereignty requirements
  • SaaS
  • Fastest deployment model
  • Fully managed operations
  • Analytics powered by the AppSentinels cloud
  • Hybrid
  • Flexible deployment across cloud and on-premises
  • Balance security and flexibility
  • Unified visibility everywhere
  • Air-Gapped Deployment
  • No external connectivity
  • Designed for classified environments
  • Maximum operational isolation

Secure Autonomous AI Systems with
Enterprise-Grade Security

The BLG enforces ownership, intent, and sequence on every agent action in real time. When an agent’s chain of calls deviates from legitimate workflows, even if every individual request is authorized, we block at the logic layer.

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Frequently Asked Questions

What exactly does AI Discovery find that traditional API discovery misses?
Traditional discovery catalogs HTTP endpoints at the edge. It cannot see AI-specific assets, like LLM endpoints, MCP tool registrations, RAG pipelines, agent identity tokens, or which APIs an agent is authorized to call. AppSentinels maps the full agentic interaction graph: agent → tool → API → data. It also surfaces shadow AI; agents deployed without security team knowledge, unauthorized MCP connections, and orphaned AI endpoints still accessible but unmaintained.
Cloud security posture management checks infrastructure config, such as IAM policies, bucket permissions, network rules. It has no concept of AI-specific risk: overprivileged LLM tool bindings, system prompt leakage through public APIs, cross-customer data access via agent tool calls, or untrusted RAG corpora carrying injected instructions. AppSentinels scores posture across five AI-specific dimensions, including model configuration, tool permission scope, prompt security, data access scope, and governance alignment. CSPM was never built to evaluate any of them.

Prompt hardening makes an AI agent’s instructions resilient to injection and manipulation. AppSentinels’ Red-Teamer attacks your prompts using direct injection, indirect injection via documents or tool outputs, multi-turn manipulation, and jailbreak patterns. Where it finds gaps, it generates specific fixes: instruction boundaries, explicit refusal rules, tool output validation, and contextual action constraints.

It learns before it enforces. AppSentinels observes normal traffic to build a baseline, covering expected API sequences, session behavior, data access patterns, role-specific actions. Enforcement rules come from that observed baseline, not hand-written policies, so legitimate workflows are already included. When a deviation is flagged, teams can review and approve edge cases, which fold back into the model. False positive rates drop sharply within the first few weeks.

Yes. Sensors and Controllers deploy entirely within your perimeter. The Controller’s PII Anonymizer strips sensitive data before anything leaves. Only anonymized metadata (call counts, timing, risk scores ) is transmitted outward. In fully air-gapped deployments, the Server can also run on-premises with zero external connectivity. This architecture is live at regulated banks, government entities, and critical infrastructure operators today.