Insights

Why Process Intelligence, not just model security, is your best defense

A bug report comes in.

Looks normal. Well-written, even. Tags the right files. Includes a suggested fix.

Your AI agent picks it up, logs it in Jira, opens a branch, writes a patch, creates a pull request. The tests pass. Your human reviewer hits “approve.” The code ships.

Everything worked exactly as designed.

Except the bug report was fake.

The patch injected a silent exploit.

The agent shipped it without question.

And just like that—your entire codebase is exposed.

Two new reports, Double Agents and Composio’s breakdown of MCP vulnerabilities, reveal the true scope of the risk:

Your AI tooling isn’t just a productivity booster. It’s a threat surface.

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From Autocomplete to Autonomous and Exploitable

AI agents aren’t just suggesting lines of code anymore. They’re executing real workflows: reading source files, accessing APIs, filing tickets, modifying databases, and in some cases, deploying to prod.

The researchers behind Double Agents show that it takes just one fine-tuned model to open the floodgates. The agent looks normal, acts helpful, passes all your evals… until a single hidden trigger flips it into extraction mode.

And what can it do then?

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‍Yes, Your Agent Can Leak Your Codebase

With the right prompt injection, a compromised AI agent can:

• Dump your source code into a disguised “debug log” or external file
• Email internal documents to a malicious address via an integrated email plugin
• Exfiltrate credentials or tokens by chaining tools together
• Extract sensitive comments, secrets, or production data embedded in your code
• Send sanitized-looking PRs that silently inject backdoors

This isn’t theoretical. The primitives exist today.

All it takes is a smart enough prompt or a bad enough integration.

And because these agents are designed to operate quietly and independently, you may not even realize what happened until weeks later…if at all.

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Process Blindness Is The Problem, Not AI

The problem isn’t the model itself. It’s how we’ve embedded it into our workflows without the visibility or controls to monitor what it’s really doing.

We’ve handed over real power — tool access, permissions, plugin chains — to agents with no embedded judgment, no sense of context, and no guardrails beyond static policies.

When agents can move laterally across systems with no process-level oversight, you don’t just have an automation tool. You have a ghost in the machine.

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Orchestration as a Security Layer

This is where process inteligence, like what Bloomfilter and Celonis provide, comes in.

Process intelligence doesn’t just help you track delivery velocity or cycle time. We give you visibility into the full software development lifecycle across humans, agents, tools, and systems.

When you orchestrate your SDLC with process intelligence with a platform like Bloomfilter, you gain:

• End-to-end traceability of what’s happening, when, and why
• Behavioral baselines that detect when an agent goes off-script
• Risk-aware visibility into how work flows, not just who triggered it
• Governance built into your process, not bolted on after the fact

Security isn’t a checklist. It’s a system of awareness. And process intelligence gives you that system.

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Trust, But Instrument

Let’s be clear: AI agents aren’t inherently malicious. But they are inherently risky, especially when plugged into high-permission, low-oversight environments.

You wouldn’t let a junior dev run deployment solo with root access.

Why are you letting an LLM?

The future of software delivery is AI-accelerated. But it has to be process-aware.

Because the next breach won’t come through the front door.

It’ll come through your agent’s cheerful Jira comment.

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Secure the model.

Lock down your tool calls.

But more importantly: Orchestrate the process.

Because in this new world, security starts with visibility.

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