HafezSecure

AI Workflow Automation Security

Security assessment for AI-assisted business workflows and automation platforms

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About This Service

Our AI Workflow Automation Security Assessment tests business processes where an AI model reads data, makes or shapes a decision, and triggers actions through connectors and tools. The risk is not only what the model says; it is what the automation does on its own authority. We test whether an attacker can steer those decisions through the content the workflow ingests (indirect prompt injection), whether the tools and connectors the automation can call are properly authorized and least-privileged, whether a trigger can be fired by someone who should not, and whether a human-in-the-loop control can be bypassed. The work follows the OWASP AI Testing Guide and the OWASP Top 10 for LLM Applications — with attention to excessive agency and insecure tool use — and draws on MITRE ATLAS and the NIST AI RMF. Every finding is proven, rated with CVSS alongside its real impact, and written up with a concrete fix.

What's Included

Indirect prompt injection through content the workflow ingests: documents, emails, tickets, form fields, and webhook payloads

Excessive agency: whether the automation can take actions beyond what the task needs

Tool and connector authorization: least privilege of the automation identity, and whether each action checks who it acts for

Trigger security: who or what can start a workflow, and whether that entry point is authenticated

Human-in-the-loop and approval-step bypass

Business logic of the automated decision, including approvals, thresholds, and branching

Secrets and credential handling inside workflow steps and integrations

Data flow and exfiltration across the systems the workflow connects

Input validation and output handling where the workflow's output drives another system

Auditability: whether automated actions are logged in a way that lets you reconstruct what happened

Unbounded consumption: cost and denial-of-service through the automated path

How It Works

1
Workflow Discovery & Mapping
We map the workflow: its triggers, the data it reads, each point where the AI makes or shapes a decision, and every tool, connector, and system it can act on. This sets the boundary of what the automation should and should not be able to do.
2
Injection & Data-Path Testing
We plant attacker-controlled instructions in the content the workflow ingests — a document, an email, a ticket, a webhook — and test whether the model follows them over the task it was given. This is where an automated process quietly turns into an attacker's tool.
3
Agency & Authorization Testing
For every tool and connector the automation can call, we test whether the action checks who it is acting for and stays inside their permissions, and whether the automation's own identity is scoped down to exactly what the task needs.
4
Trigger, Logic & Exfiltration Testing
We test whether a workflow can be started by someone who should not, whether an approval or human-in-the-loop step can be skipped, whether the decision logic can be pushed off its intended path, and whether data can be moved across the connected systems in a way it should not.
5
Validation, Reporting & Re-testing
Every finding is proven with a reproducible case, rated with CVSS and the real impact, mapped to the OWASP Top 10 for LLM Applications, and written up with a concrete fix. After you remediate, we re-test to confirm the fixes hold.
Deliverables
  • Executive summary with a risk overview for decision-makers
  • Detailed technical report, each finding with a reproducible case
  • Indirect prompt-injection findings across the ingested data paths
  • Excessive-agency and tool-authorization findings
  • Trigger, approval-bypass, and business-logic findings
  • Data-flow and exfiltration findings across the connected systems
  • Findings mapped to the OWASP Top 10 for LLM Applications, with CVSS and business impact
  • Prioritized remediation guidance and re-testing after remediation

Why HafezSecure

The Action, Not Just the Answer
We do not stop at making the model produce wrong text; we test the actions the workflow can take on its own authority, which is where an automated process turns into real-world damage.
Indirect Injection Focus
Automations read data from many sources, and any of them can carry a hidden instruction. We test the ingested data paths that a chat-only assessment never touches.
Least-Privilege by Design
Most workflow damage comes from an automation identity that can do far more than its task. We check whether each connector is scoped to exactly what the process needs.
Reproducible and Actionable
Every finding comes as a case you can replay, mapped to a recognized standard, with a concrete fix for the trigger, the guardrail, the connector, or the authorization gate.

Frequently Asked Questions

What is an AI Workflow Automation Security Assessment?

It evaluates a business workflow in which an AI model reads data, makes or shapes a decision, and triggers actions through connectors and tools. It looks for weaknesses in the ingested data paths, the tool and connector authorization, the triggers, and the automated decision logic, following the OWASP AI Testing Guide and the OWASP Top 10 for LLM Applications, with each finding proven and rated.

What is indirect prompt injection, and why does it matter for a workflow?

Indirect prompt injection is a hidden instruction placed inside content the workflow reads — a document, an email, a ticket, a webhook — rather than typed by the user. Because a workflow ingests data from many sources and then acts on it, an instruction hidden in that data can steer the automation into doing something it was never meant to do. It is the injection path that matters most for automated processes.

What is excessive agency?

Excessive agency is when the automation can take actions, or reach systems, beyond what its task actually needs — an identity with broad permissions, a connector that can write where it only needs to read. It turns a single bad decision into a large blast radius, so we check that every tool and connector is scoped down to the task.

What access and information do you need to start?

Ideally a description of the workflow and its triggers, access to run it end to end, the list of tools and connectors it can call with their intended permissions, and sample inputs. With the workflow definition and the connector configuration (a white-box view) we cover far more than by probing from the outside; we scope the depth of access with you before we start.

Do you test in black-box, grey-box, or white-box mode?

All three. Black-box mimics an outsider with no inside knowledge, white-box works from the workflow definition and connector configuration, and grey-box sits in between with partial knowledge. For automated workflows, a grey-box or white-box view usually finds the authorization and agency flaws that matter most, so we recommend it where possible.

Should the assessment run against production or a staging environment?

A staging environment that mirrors production is safest, because a workflow assessment triggers real actions through connectors and can create, change, or send data. When we must test against production, we agree on non-destructive boundaries first and stay within them. We scope this with you before any action is taken.

How are findings rated?

Each finding is scored with CVSS and presented next to its real business impact, so a technically interesting issue with little consequence is not mistaken for one that hands an attacker a critical action. That pairing is what lets you fix in the right order.

Do you re-test after we fix the findings?

Yes. Re-testing after remediation is part of the engagement: we confirm each fix actually closes the issue and did not open a new path, and the report is updated to reflect the remediated state.

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