Threat Intelligence & APT Unit 42 1 month ago

Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America

CN
CyberNew Threat Research Desk
• Original Reporting: Unit 42
CyberNew Threat Intel Assessment
Assessed Severity: MEDIUM
Impacted Surface
Enterprise Perimeter & Network Defense
Intelligence Sector
Threat Intelligence & APT

Analyst Takeaway

"Executive Summary We have analyzed two ongoing, multi-stage network intrusion and data-exfiltration campaigns targeting organizations in Latin America. Corroborating recent findings from the broader threat intelligence community, we observed attackers leveraging artificial intelligence (AI) to enhance their capabilities. Our investigation categorizes this activity as follows: Mexican..."

Recommended Defense & Mitigation

  • Threat Monitoring: Ingest published IOCs into SIEM/EDR detection rules for continuous telemetry monitoring.
  • Security Awareness: Alert staff and maintain baseline endpoint hardening across endpoints.
Curated & Verified by CyberNew Threat Intelligence Desk Standard Defense Framework (NIST / MITRE ATT&CK)

Executive Summary

We have analyzed two ongoing, multi-stage network intrusion and data-exfiltration campaigns targeting organizations in Latin America. Corroborating recent findings from the broader threat intelligence community, we observed attackers leveraging artificial intelligence (AI) to enhance their capabilities.

Our investigation categorizes this activity as follows:

  • Mexican transportation campaign: This campaign impacted a transportation organization, alongside federal government ministries and municipal water utilities in Mexico and Ecuador. Operators relied on living-off-the-land (LotL) techniques. They executed iterative batch scripts to manipulate and exfiltrate sensitive data, and self-hosted NextChat instances on operational infrastructure. We track the activity in this cluster as CL-CRI-1131.
  • Brazilian financial campaign: Attackers targeted the Brazilian financial sector. We observed an expansion of previously reported targeting of vulnerable web servers in a job-themed phishing campaign. The attackers employed custom remote access Trojans (RATs) and tunneling tools, including a Go-based SOCKS5 proxy with iterative filenames that suggest AI-enablement. We track the activity in this cluster as CL-CRI-1163.

We track them as two separate activity clusters with distinct geographic focuses. However, the technical and behavioral overlaps between CL-CRI-1131 and CL-CRI-1163 highlight shifting trends in Latin American targeting and threat actor tooling.

Both clusters have overlapping SOCKS5 relay infrastructure and they both rely on AI to orchestrate operations via commercial large language models (LLMs). This signals a broader evolution in the regional threat landscape. Rather than isolated incidents, these clusters demonstrate how diverse threat groups in Latin America are independently adopting advanced proxy networks and AI integration to streamline their execution.

Palo Alto Networks customers are better protected from the threats discussed here through the following products and services:

If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team.

Related Unit 42 Topics AI, LLM, Phishing, RATs

CL-CRI-1131: Mexican Transportation Campaign

During an April 2026 compromise, the attacker’s host-based operations reflected the trial and error of LLM usage. Infrastructure associated with the campaign persisted into June 2026 and exposed targeting profiles of the attacker.

Initial Host-Based Footprint: Execution Challenges

During an intrusion as part of CL-CRI-1131 activity in April 2026, we observed the attacker struggling to gather sensitive data. After repeated attempts to dump the Security Account Manager (SAM) registry hive and the domain controller NTDS.dit file, the attacker created shadow copies across multiple drives before copying files, as shown in Figure 1.

Figure 1. Volume shadow copy manipulation.

This occurred while the attacker used a series of numbered batch scripts to collect sensitive data from the compromised host, as shown in Figure 2.

Figure 2. Commands used for a series of batch scripts to collect sensitive data.

The attackers inserted a permissions check to ensure successful file writing to the collection directory. These trial-and-error actions and successive script fixes are consistent with LLM usage.

After struggling to collect these files, we observed attackers troubleshooting connectivity with infrastructure at 62.171.185[.]97.

Infrastructure Analysis: Tracing Exfiltration Commands to Exposed Certificates

Subdomain Interpretation
m-doxa-apodo.duckdns[.]org apodo = alias/nickname (Spanish)
m-doxa-geo.duckdns[.]org geo for geolocation
m-doxa-intel.duckdns[.]org intel for intelligence
m-doxa-vacunas.duckdns[.]org vacunas = vaccines (Spanish)
Date Certificate SHA-256 Hash SANs Host
Feb. 27, 2026 7d766942ef34542cee39c852286599958c4c2e23187010c4d38dbf88fcb40bf8 1 165.22.184[.]26
April 20, 2026 4e218e70afdbb116209ec0ebe8fc556e296e69648aa4e0425b83c0e863a8fee5 5 178.128.87[.]160
June 19, 2026 46ac289ce0c13666de616446f5d5a68da8bd150f4f065c3bec02f63776d3899c 5 178.128.87[.]160

Source Verification & Original Intelligence

This threat report was reviewed by CyberNew analysts and cross-referenced with primary security disclosures from Unit 42.

Primary Advisory →