Every AI Attack Surface. One Security Platform.
AI isn't just chatbots anymore. It's in your IDE, your desktop, your CI/CD pipeline, your agents, and your infrastructure. Proxilion secures every point where AI touches your organization's data but with deterministic enforcement, not probabilistic guessing.
Your employees use AI in ways you can't see: pasting source code into ChatGPT, uploading customer data to Claude, running autonomous agents with unrestricted tool access. Traditional DLP was built for email and USB drives but not for the AI-native world.
Policy rules that produce the same result every time. Regex patterns, allowlists, role checks, and cryptographic verification. Cannot be bypassed by prompt injection or social engineering.
Statistical models that detect anomalies over time. Z-score drift detection, kill chain pattern matching, and usage profiling. Complements deterministic rules for unknown threats.
Every place AI interacts with your organization's data is an attack surface. Here's how Proxilion covers each one.
Desktop AI apps bypass every network-level control. When an employee pastes customer records into Claude Desktop, no proxy or firewall sees that traffic. Proxilion's endpoint agent monitors clipboard activity, file access, and network connections at the OS level.
Code assistants stream your entire codebase to external models. Proprietary algorithms, hardcoded secrets, and internal API endpoints get sent to third-party servers with every completion request. The endpoint agent intercepts and scans this traffic before it leaves.
The simplest attack surface, and the hardest to control. Employees copy-paste sensitive data directly into browser-based chatbots every day. File uploads, conversation context, and multimodal inputs all carry risk. Proxilion catches this at the clipboard and network level.
Your developers build applications that call AI APIs. Without governance, any prompt could contain customer PII, any response could leak credentials, and any cost overrun goes unnoticed until the bill arrives. The Proxilion SDK wraps every API call with policy enforcement.
Autonomous agents make chains of decisions without human oversight. A single compromised step can escalate privileges, exfiltrate data across tool boundaries, or trigger destructive actions. Proxilion enforces policy on every tool call in the chain and detects multi-step kill chain patterns.
The Model Context Protocol gives AI direct access to your systems: databases, filesystems, APIs, and code execution environments. Every MCP tool call is a potential attack vector. The MCP Gateway sits between the AI and your tools, enforcing security before any action is taken.
CI/CD pipelines run unattended, often with elevated permissions and embedded secrets. When a build step calls an AI API, it may send credentials, proprietary code, or training data to external services. Automated calls can also spiral in cost without anyone noticing. The proxy intercepts this traffic transparently.
Production services process real customer data. When they call AI APIs, PII can leak in API payloads, secrets can appear in responses, and costs can multiply across thousands of serverless invocations. The proxy provides infrastructure-level enforcement without any code changes.
When agents delegate tasks to other agents, trust boundaries blur. One agent's context can leak into another's context. Privilege can escalate invisibly as tasks are delegated. Without governance, automated decisions cascade with no audit trail. Proxilion enforces trust boundaries at every handoff.
Your organization might be running models that were never approved, downloaded from untrusted sources, or fine-tuned with data that shouldn't have left the building. Proxilion maintains a model registry and enforces that only attested, approved models are used across the organization.
Every security vendor says they can "secure AI." But can they prove it? The Trust Plane is the answer.
Imagine your auditor asks: "Can you prove that every AI interaction in your organization was governed by policy last quarter?" With most tools, you'd scramble through logs, cross-reference timestamps, and hope nothing fell through the cracks.
With Proxilion's Trust Plane, the answer is a single cryptographic verification. Every enforcement point - endpoint agent, SDK, MCP Gateway, proxy - generates a signed attestation for every action it governs. These attestations form a hash-chained, tamper-evident record that links each AI interaction back to the original policy decision and organizational intent.
This isn't just logging. It's mathematical proof that governance happened. No gaps. No retroactive edits. No "trust us, we checked." The chain of evidence flows from the individual action, through the policy that authorized or denied it, all the way up to the organizational rules that created that policy. An auditor can verify the entire chain independently.
No other AI security vendor offers cryptographic proof of governance across every enforcement point. The Trust Plane is what makes the difference between "we have logs" and "we have proof."
If you're exploring how to protect your organization from AI-related data risks, we'd love to hear from you.
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