Shadow Agents

Shadow agents are AI systems, bots, or automated workflows that operate outside formal governance, security controls, and organisational oversight — often without their owners fully realising they exist.

They are the AI equivalent of shadow IT: quietly deployed, loosely connected to systems, and capable of making decisions, taking actions, and moving data without central visibility.

As organisations race to integrate AI into operations, shadow agents are becoming one of the most dangerous and least understood risk vectors.

How Shadow Agents Emerge

Shadow agents are rarely created with malicious intent. They usually appear through:

Internal experimentation

• Engineers deploying AI scripts for testing

• Analysts connecting models to internal data

• Teams automating workflows without security review

Third-party tools

• Browser plugins

• SaaS automation platforms

• Embedded AI assistants

Agent frameworks

• Auto-GPT style agents

• Tool-connected LLMs

• Workflow orchestration systems

Once connected to APIs, documents, credentials, or production systems, these agents begin acting independently — often with little or no logging, auditing, or lifecycle management.

Why Shadow Agents Are Dangerous

Shadow agents create risk in three ways:

They bypass security controls
Agents may have direct access to internal systems, cloud services, or databases without going through traditional authentication and approval paths.

They leak data unintentionally
AI agents frequently transmit prompts, files, and results to external services — creating silent data exposure.

They can be hijacked
An attacker who finds a poorly secured agent can redirect it to:

• Exfiltrate data

• Execute commands

• Modify records

• Automate abuse

In effect, a shadow agent becomes a remote-controlled insider.

Warning Signs of Shadow Agent Activity

Common indicators include:

• Unknown API calls in logs

• AI services accessing internal systems

• Automation running without owners

• Unexpected data flows to external providers

• Cloud resources created by non-standard tooling

Most organisations do not discover shadow agents until:

• A breach occurs

• Compliance audits fail

• Or costs suddenly spike

How Fortaris Tracks Shadow Agents

Fortaris monitors the open AI ecosystem to detect:

• New agent frameworks

• Tool integrations

• Emerging abuse techniques

• Real-world exploitation patterns

We connect these signals to:

• Cloud risk

• Model misuse

• Automation abuse

• Data leakage pathways

This gives security teams and regulators visibility into what AI agents are doing outside the perimeter — not just inside it.

Final Thought

Every AI agent you do not know about is a potential attacker you did not invite.

If you cannot see how autonomous systems are operating in the wild, you cannot secure them.

Fortaris exists to make the invisible visible.