CyberSecurityNews

Chinese Hackers Use AI Agents to Exploit Web Servers and Automate Attacks


A Chinese-speaking cybercrime group is using AI-assisted tools to turn vulnerable web servers into entry points. It shows how familiar flaws become more dangerous when attackers automate the work around them.

The group, tracked as UAT-10147, targeted internet-facing Windows and Linux systems in government, education, media, technology, and gaming. Victims were identified across several countries, while a linked server held a target list of about 170,000 URLs.

Cisco Talos identified the activity and found that the operators mixed public exploits with AI-generated instructions, scripts, and testing steps.

Cisco Talos said in a report shared with Cyber Security News (CSN) that the approach helped the group carry out complex intrusions at greater scale. The immediate concern is not a new flaw alone, but a faster attack process.

AI can help an operator scan a site, adjust a failed exploit, check whether a payload worked, gather system details, and set up a backdoor with far less manual effort. The activity signals a practical shift in criminal operations today.

Chinese Hackers Use AI Agents

UAT-10147 appears to use agent-like AI as an operational assistant rather than a single automated tool. Talos found generated playbooks, troubleshooting logic, exploit scripts, and validation workflows that supported activity before and after a server was compromised.

The group combined these workflows with established offensive frameworks. That blend allowed it to find weaknesses, build payloads, test results, and document the next action, reflecting wider concerns around AI agent security risks.

Commands to split the large list (Source – Cisco Talos)

Initial access relied on publicly known remote-code-execution weaknesses. The campaign included Zimbra, AjaxPro, Nacos, and Telerik flaws, a reminder that web server RCE flaws can create a direct path to takeover.

On Windows, the operators used remote access to install BadIIS, a malicious IIS module associated with search-result manipulation. They also used scripts to raise privileges, weaken endpoint scanning around IIS folders, create high-privilege access, and retain control after the original break-in.

Linux targets followed a similar pattern. After placing a web shell, the group used local privilege-escalation bugs, including Dirty Pipe, to reach root access and install additional implants.

Automation Extends the Damage

The recovered material suggests the AI was involved across the full attack cycle, not merely in writing code. One guide produced a structured route for abusing ASP.NET ViewState deserialization, from checking stolen configuration keys to creating payloads and confirming execution without obvious visible effects.

Open directory on download site (Source - Cisco Talos)
Open directory on download site (Source – Cisco Talos)

The scripts checked writable folders, mapped IIS sites, deployed an implant, placed a web shell, and collected results through callbacks. A failed attack need not stop the operator: the workflow can diagnose an obstacle and try an alternative.

Talos also observed the group use a cloud configuration service to collect basic victim details after exploiting Nacos. By blending stolen information with routine-looking web traffic, attackers may make initial confirmation and follow-up activity harder for defenders to spot.

Organizations should treat public-facing web servers as high-priority assets. Rapid patching, limiting unnecessary exposure, reviewing IIS and application configuration changes, and watching for unusual scheduled tasks, new accounts, outbound connections, and excluded security paths can interrupt this kind of chain.

Windows infection chain (Source - Cisco Talos)
Windows infection chain (Source – Cisco Talos)

Teams should also protect ASP.NET MachineKey material and investigate unexpected server errors rather than dismissing them as noise.

In particular, error responses can reveal whether an attacker is testing deserialization access, while IIS deployment vulnerability risks show why tightly restricting administrative endpoints matters.

The campaign does not mean AI has made attacks fully independent of people. It does show that financially motivated groups can use it to repeat established techniques more efficiently, reducing the time between finding a weakness and turning it into a profitable intrusion.

For defenders, the practical lesson is straightforward: reduce the attack surface before automated tooling reaches it.

Maintaining inventories, applying security updates, protecting secrets, and monitoring web-server behavior remain essential, particularly amid reporting on an actively exploited Magento weakness that similarly turns exposed application flaws into takeover opportunities.

Indicators of Compromise (IoCs):-

TypeIndicatorDescription
IP address139.180.197[.]150Download and secondary staging server linked to UAT-10147 activity
URLhttps[:]//adminapi.tippusoni[.]in/4/dll.zipBadIIS archive download location
URLhttps[:]//adminapi.tippusoni[.]in/4/user.txtExecution script download location
Network endpoint139.180.197[.]150:54321Secondary server used to retrieve the web shell
Domainwebhook[.]siteCallback and exfiltration endpoint used by AI-generated scripts
File nameback.txtMain Windows malware deployment script
File nameback.batAlternate name for the main Windows deployment script
File namebai.batSecondary batch script used for backdoor execution and persistence
File nameprcc1.rarRenamed privilege-escalation utility
File namesvchosts.exeDisguised QuasarRAT payload
File namedll.zipBadIIS archive downloaded to compromised systems
File nameuser.batScript used to create a privileged local account
File nameuser.txtDownloaded form of the user-account creation script
File namecheck_paths.pyAI-generated post-exploitation diagnostic script
File namedeploy_implant.pyAI-generated script used to download and launch an implant
File namedeploy_shell.pyAI-generated script used to install a persistent web shell
File nameexfil.pyAI-generated reconnaissance and data-exfiltration script
File nameup.ashxTemporary ASHX upload handler deployed to compromised IIS servers
File namesss.ashxPersistent ASHX web shell
File name pattern[10 digits].[7 digits].dllRandomized naming pattern used for reverse-shell DLL payloads

Note: IP addresses and domains are intentionally defanged (e.g., [.]) to prevent accidental resolution or hyperlinking. Re-fang only within controlled threat intelligence platforms such as MISP, VirusTotal, or your SIEM.

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