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Introduction: Artificial Intelligence Is No Longer Just Assisting Hackers, It May Be Replacing Them
Artificial intelligence has become one of the most transformative technologies in modern cybersecurity. While defenders increasingly rely on AI to detect threats faster, cybercriminals are also embracing the technology to automate attacks, reduce operational costs, and expand the scale of their campaigns. The latest allegation involving the Hermes AI agent suggests that this shift is accelerating at an alarming pace.
According to recent cybersecurity reporting, Hermes AI was allegedly deployed in unattended mode during an intrusion targeting Thailand’s Finance Ministry. Instead of merely assisting attackers with isolated tasks, the AI agent reportedly automated several post-exploitation activities after the initial compromise. If confirmed, this incident would represent another major milestone in the evolution of AI-powered cyber operations, demonstrating how autonomous agents can actively participate in real-world attacks with minimal human supervision.
The Reported Incident
Cybersecurity researchers reported that Hermes AI was allegedly involved in a cyber intrusion against Thailand’s Finance Ministry. The AI agent reportedly operated in unattended mode, allowing it to perform actions automatically after the attackers established an initial foothold inside the compromised environment.
Unlike traditional malware that follows pre-programmed instructions, AI agents can dynamically interpret situations, analyze available information, and execute multiple operational tasks with limited human interaction. This capability makes post-exploitation activities significantly more efficient and difficult to monitor.
Although the available public information remains limited, the report indicates that investigators recovered attacker infrastructure containing numerous artifacts associated with the intrusion.
Evidence Found During the Investigation
Researchers reportedly discovered several categories of files left behind by the attackers. These artifacts provide valuable insight into how the operation was conducted and how the attackers maintained access throughout the intrusion.
Among the exposed files were:
Web shells used for persistent remote access.
Stolen credentials collected during the attack.
Various malware payloads prepared for deployment.
Operational logs documenting privilege escalation.
Records showing lateral movement across internal systems.
These findings suggest that the attackers maintained detailed operational documentation while expanding their access throughout the compromised network.
The presence of extensive logs also indicates that portions of the operation may have been monitored or executed automatically, supporting allegations that AI-assisted automation played an important role.
Understanding Post-Exploitation Automation
Post-exploitation begins after attackers successfully breach an
Traditionally, experienced penetration testers or threat actors manually perform these activities.
With AI agents like Hermes, however, many of these repetitive tasks may be executed automatically.
Potential automated activities include:
Mapping internal networks.
Identifying administrative accounts.
Searching for confidential documents.
Deploying persistence mechanisms.
Collecting credentials.
Prioritizing high-value targets.
Generating operational reports.
Recommending the next attack path.
Automation significantly reduces the time required to complete these objectives while allowing attackers to operate across multiple victims simultaneously.
Why This Allegation Matters
If the reported use of Hermes AI is verified, it represents more than just another government cyberattack.
It signals that autonomous AI systems are becoming operational tools inside sophisticated intrusion campaigns.
Historically, attackers relied heavily on human operators to make tactical decisions during an intrusion. AI-driven automation changes that model by enabling software to perform analysis and execute actions at machine speed.
This evolution increases the potential scale of cybercrime while lowering the expertise required to conduct advanced operations.
Organizations must now prepare for attackers capable of operating continuously without fatigue or constant operator involvement.
The Growing Role of AI in Offensive Cyber Operations
Artificial intelligence has already demonstrated value in defensive security through malware detection, anomaly identification, and threat intelligence analysis.
Unfortunately, the same capabilities can be repurposed by threat actors.
Modern AI can assist attackers by:
Writing malicious scripts.
Automating reconnaissance.
Generating phishing content.
Parsing stolen documents.
Prioritizing compromised assets.
Identifying security weaknesses.
Summarizing network intelligence.
Coordinating attack workflows.
As these capabilities mature, cyber operations become faster, cheaper, and increasingly scalable.
Government Organizations Remain High-Value Targets
Finance ministries, tax authorities, and national financial institutions represent attractive targets because they store enormous amounts of sensitive information.
Successful intrusions may expose:
Government financial records.
Taxpayer information.
Employee credentials.
Internal communications.
Budget planning documents.
Procurement data.
National economic intelligence.
Even when no data is publicly leaked, unauthorized access alone can create long-term national security concerns.
Defenders Must Prepare for Autonomous Threats
Security teams can no longer assume attackers will operate only during business hours or rely exclusively on manual decision-making.
Future defensive strategies should include:
Continuous threat monitoring.
Behavioral anomaly detection.
Identity protection.
Zero Trust architecture.
Multi-factor authentication.
Privileged access management.
Endpoint detection and response.
AI-assisted defensive analytics.
Organizations should also prepare incident response procedures specifically designed to detect automated attacker behavior.
What Undercode Say:
The allegation surrounding Hermes AI deserves careful attention because it illustrates where offensive cybersecurity may be heading rather than where it has already fully arrived.
The most significant aspect is not simply that AI was allegedly involved.
The real concern is the reported unattended operation.
Once attackers trust an AI system to continue working without direct supervision, operational efficiency changes dramatically.
Human operators become supervisors instead of technicians.
That reduces operational costs.
It also allows multiple simultaneous intrusions.
Government environments become particularly attractive because they contain interconnected systems with high-value information.
If AI agents can analyze Active Directory structures, recommend privilege escalation paths, and deploy payloads automatically, intrusion timelines could shrink from days to hours.
Another important observation is the recovery of attacker logs.
Logging indicates discipline.
It also suggests automation pipelines where actions are continuously recorded for later review.
Future AI agents may automatically summarize successful compromises.
They could recommend additional persistence methods.
They might classify sensitive documents before exfiltration.
Defenders should expect increasingly adaptive malware capable of changing behavior according to environmental conditions.
Traditional signature detection will become less effective.
Behavioral analytics will grow in importance.
Security teams should prioritize identity monitoring over simple malware detection.
Least privilege principles become even more valuable.
Segmentation limits automated lateral movement.
Privileged account auditing becomes critical.
Continuous authentication can reduce attacker persistence.
Threat hunting should increasingly focus on abnormal sequences rather than isolated indicators.
Machine-speed attacks require machine-speed defenses.
Security automation will become essential rather than optional.
Organizations investing only in perimeter security may struggle against autonomous post-exploitation frameworks.
The cybersecurity workforce must also evolve.
Analysts should understand AI orchestration alongside traditional malware analysis.
Governments should establish policies governing AI security testing.
Vendors must improve transparency surrounding AI-enabled defensive tools.
International cooperation will become increasingly important as autonomous cyber operations cross national borders.
Ultimately, AI is neither inherently defensive nor offensive.
Its impact depends entirely on who controls it.
The Hermes allegation serves as another reminder that cybersecurity is entering an era where software may increasingly fight software, with humans overseeing both sides of the conflict.
Deep Analysis
The reported attack highlights several techniques commonly associated with post-exploitation investigations and defensive validation. Security teams can use the following Linux commands during incident response and threat hunting to inspect systems for suspicious activity:
last lastlog who w id sudo -l ps aux pstree top ss -tulpn netstat -antp lsof -i find /var/www -type f -name ".php" find / -perm -4000 find /tmp -type f crontab -l cat /etc/crontab journalctl -xe grep "Failed password" /var/log/auth.log grep "Accepted password" /var/log/auth.log ausearch -m USER_LOGIN sha256sum suspicious_file file suspicious_file strings suspicious_file objdump -x suspicious_file curl -I suspicious-domain.com tcpdump -i any
These commands help investigators review authentication activity, inspect privileged processes, detect web shells, analyze suspicious binaries, monitor active network connections, and collect forensic evidence. While none of these commands alone can confirm AI-driven attacker activity, they provide a solid foundation for identifying indicators of compromise and reconstructing post-exploitation behavior.
✅ Multiple cybersecurity reports have discussed allegations that Hermes AI was used to automate portions of post-exploitation during a reported intrusion targeting Thailand’s Finance Ministry, though public technical details remain limited.
✅ The discovery of web shells, stolen credentials, payloads, and attacker logs is consistent with artifacts commonly recovered during advanced incident response investigations.
❌ There is currently no publicly verified evidence proving that Hermes AI independently conducted every reported action without human oversight, so claims regarding the full extent of autonomous operation should be treated as allegations until officially confirmed.
Prediction
(-1) Negative Prediction
AI-powered offensive agents will become increasingly common in advanced cyber intrusions over the next few years.
Government agencies and financial institutions are likely to face more automated post-exploitation campaigns designed to accelerate privilege escalation and lateral movement.
Defensive platforms will increasingly incorporate autonomous threat hunting to counter machine-speed attacks, creating an ongoing competition between offensive and defensive AI capabilities.
Organizations that fail to modernize identity security and behavioral monitoring may experience longer attacker dwell times as AI-assisted intrusions become more sophisticated.
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