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The Hermes AI agent attack shows how autonomous AI can be used to automate post-exploitation rather than introduce a new exploit. According to Hunt.io and BleepingComputer, the open-source Hermes AI agent operated in unattended “YOLO” mode during activity associated with Thailand’s Ministry of Finance.
Investigators uncovered exposed infrastructure containing exploit code, web shells, HTTP tunnelling tools, stolen credentials, custom scripts, compiled payloads, Hermes logs, and binaries later identified as the previously undocumented Hades implant. Thailand’s Ministry of Finance had not confirmed a breach at publication, and public reporting notes that some recovered artifacts indicate targeting rather than confirmed compromise.
The incident highlights how AI can accelerate reconnaissance, privilege enumeration, and other post-exploitation tasks, reinforcing the need to detect increasingly automated intrusion activity.
Much of the discussion around agentic AI security focuses on defensive use cases. This reported operation shows how attackers may use autonomous AI agents to automate existing post-exploitation workflows.
According to Hunt.io, Hermes was configured to run in YOLO mode, bypassing approval prompts before executing potentially dangerous commands. The recovered logs showed the agent performing tasks commonly associated with post-exploitation, including:
None of these techniques are new individually. The notable aspect is the automation layer, which allows operators to delegate repetitive post-exploitation tasks to an AI agent, potentially reducing manual effort after initial access.
The investigation began when Hunt.io and security researcher Bob Diachenko identified three exposed web directories hosted on infrastructure in Hong Kong.
Researchers recovered 585 files totalling approximately 470 MB, including:
| Recovered artifact | Why it matters |
|---|---|
| Hermes AI logs | Documented Hermes command execution and post-exploitation activity. |
| Web shells | Suggested remote access capability. |
| HTTP tunnelling tools | Included tooling for HTTP tunnelling. |
| Exploit code | Indicated exploitation tooling. |
| Custom scripts | Referenced Ministry infrastructure. |
| Stolen credentials | Indicated operational resources. |
| Hades binaries | Revealed a previously undocumented implant. |
The recovered files referenced Ministry of Finance infrastructure, including Hadoop, Apache Ambari, GlassFish, internal IP addresses, mail systems, and administrative interfaces. However, public reporting does not establish that every referenced system was successfully compromised.
Alongside Hermes, researchers identified Hades, a previously undocumented Go-based implant for Windows and Linux. Hunt.io’s malware analysis found the recovered samples supported:
These capabilities describe the analysed Hades samples rather than confirmed behaviour within the Ministry’s environment. Public reporting has not established which of these capabilities, if any, were used during the reported activity.
Security teams have traditionally looked for human-driven attacker behaviour during investigations. Autonomous AI agents may change that expectation. Instead of manually issuing reconnaissance commands, an operator can delegate tasks to an AI agent that:
This does not make the attack fully autonomous. Public reporting has not identified the initial access method or suggested Hermes independently compromised the environment. Instead, the AI agent appears to have accelerated post-exploitation after access was already available.
For defenders, this may shorten attacker timelines, leaving less time to detect reconnaissance and other post-exploitation activity.
The incident reinforces several operational priorities regardless of whether an organisation uses AI internally. Security teams should review:
Because AI agents can automate repetitive tasks, defenders may observe reconnaissance activity occurring more quickly than during manually driven intrusions.
This incident aligns most naturally with Hexnode XDR and Hexnode UEM from an operational perspective.
For managed Windows endpoints, Hexnode XDR can help security teams:
Hexnode UEM helps organisations:
For incidents such as the Hermes AI agent attack, neither platform replaces forensic analysis, server log reviews, vulnerability management, or vendor-specific remediation. Instead, they provide endpoint visibility and device management capabilities that complement broader incident response efforts.
Discover how Hexnode XDR unifies detection, investigation, response, and endpoint visibility to strengthen enterprise security operations.
DOWNLOADHermes is an open-source AI agent that automates command execution. Hunt.io reported it running in unattended YOLO mode during post-exploitation activity.
No. At publication, the Ministry had not confirmed a breach. Public reporting indicates targeting and post-exploitation activity, but the full scope of compromise remains unconfirmed.
It shows how attackers may use AI to automate reconnaissance and post-exploitation, potentially accelerating intrusion timelines. Organisations should ensure their detection and response capabilities account for AI-assisted attacker activity.
The Hermes AI agent attack shows how autonomous AI can accelerate post-exploitation without replacing traditional attacker techniques. While the reported activity targeting Thailand’s Ministry of Finance does not confirm the full scope of compromise, it highlights how AI may accelerate intrusion workflows.
As organisations adopt AI, defenders should prepare for attackers to do the same. Maintaining endpoint visibility and correlating endpoint, server, and identity telemetry remain key to detecting AI-assisted intrusions.
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