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Hunting Vulnerabilities Using Frontier Models
Okta used frontier AI models GPT-5.5 Cyber and Mythos via OpenAI and Anthropic programs to scan millions of code lines for vulnerabilities.
Okta describes using frontier AI models, including GPT-5.5 Cyber Preview (TAC) and Mythos Preview, through OpenAI's Daybreak Cyber Partner Program and Anthropic's Project Glasswing to hunt vulnerabilities across its product codebase. The team built a custom Python orchestrator with strong isolation, vendor-agnostic model support, and four distinct scanning pipelines executed as isolated Codex or Claude Code sessions with progressive context loading to reduce context bloat. Human experts and AI agents worked both autonomously and in paired hunts, and Okta reports the best results when humans and agents taught each other.
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Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America
Unit 42 documents two AI-assisted intrusion campaigns against Latin American government, utility, and financial organizations using LLM-orchestrated tooling.
Palo Alto Networks Unit 42 tracks two ongoing intrusion clusters, CL-CRI-1131 (Mexican transportation, federal ministries, municipal water utilities) and CL-CRI-1163 (Brazilian financial sector), both using living-off-the-land techniques, SOCKS5 relays, and custom RATs. The attackers appear to orchestrate operations via commercial LLMs like Claude and GPT-4.1, evidenced by iterative batch scripts and AI-generated tunneling tool naming. The Mexican campaign (also reported as Operation Escaneo by CloudSEK) exfiltrated sensitive data via dynamic-DNS infrastructure with rotated multi-SAN TLS certificates between February and June 2026. This signals broader adoption of AI-enhanced operations by diverse threat groups in the region.
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Hackers Use LLMs to Generate Exploit Scripts and Automate Post-Exploitation Across Latin America
Unit 42 says Latin American attackers used LLMs to automate post-exploitation in campaigns hitting Mexican government, water utilities, and Brazilian financial firms.
Unit 42 identified two campaigns in Latin America whose operators used commercial LLMs (Claude, GPT-4.1) behind a self-hosted NextChat interface to generate and debug post-exploitation scripts. Cluster CL-CRI-1131 compromised a transportation organization, Mexican federal ministries, and water utilities in Mexico and Ecuador, using native Windows tools and Volume Shadow Copies to dump the SAM registry hive and NTDS.dit. Cluster CL-CRI-1163 targeted Brazilian financial organizations with job-themed phishing, custom RATs, and a Go-based reverse SOCKS5 tunneling utility called SockTz, with nine versions deployed within roughly two hours. Trend Micro tracks related AI-augmented activity as SHADOW-AETHER-040 and SHADOW-AETHER-064.
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FulcrumSec Claims Responsibility for Manchester Airport Group Breach
FulcrumSec leaked ~549GB of Manchester Airport Group data, claiming 8.7M customer profiles exposed via exposed Iterable admin keys.
FulcrumSec posted around 549GB of uncompressed stolen Manchester Airport Group (MAG) data on its leak site, claiming nearly 8.7 million customer profiles with email, name, phone, home town, postcode and residential IP. The group said initial access came from Iterable platform admin keys exposed in the root-domain JavaScript of the Manchester, Stansted and East Midlands airport websites. Allegedly stolen data also includes ~1.2 billion marketing events, 2.5 million bookings, 461,000 SMS records, 108,000 vehicle plates and ~191,000 future bookings. MAG has provided no update since August 27 and the claims remain unverified.
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Extortion Group FulcrumSec Claims 86GB Manchester Airports Data Theft
Extortion group FulcrumSec claims stealing 86GB of Manchester Airports Group data, exposing 8.7 million customers' personal and booking details.
Manchester Airports Group disclosed a breach on August 27 affecting parking, lounge, Fast Track and WiFi registrations at Manchester, London Stansted and East Midlands airports, impacting 8.7 million customers, most exposed only email addresses. FulcrumSec claims it stole about 86GB via airport-specific Iterable API credentials exposed in client-side JavaScript, including a 21.5GB Manchester export with booking histories, marketing data and nearly 200,000 records on upcoming 2026 travel. BleepingComputer verified sample records against a real traveler's Fast Track history; MAG declined to address the group's specific claims. Researchers warn the combination of UK postcodes, vehicle registrations and booking details could enable convincing targeted phishing, and MAG says no payment card or banking data was exposed.
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