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Researchers observe first ‘near-autonomous’ AI attack on government target in Taiwan
Dream researchers observed the first near-autonomous AI attack on a government target, with suspected Chinese hackers stealing 2,500+ Taiwan records.
Israeli firm Dream reported that suspected Chinese hackers used open-source AI models to run a near-autonomous cyberattack against Taiwan's government, extracting over 2,500 personnel records. The framework, built on Hermes and OpenClaw, adapted mid-operation without human intervention, ran autonomous 'Learning Cycles' researching applicable vulnerabilities, and expanded to supply chain vendors, a nuclear safety agency, a government email system, and seven-plus energy companies. Attackers bypassed safety guardrails by framing the work as authorized penetration testing. Dream discovered the operation via a 160MB online archive of nearly 1,400 files.
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AI-Generated Exploit Scripts Target Siemens S7 PLCs in U.S. Critical Infrastructure
NSA, CISA, FBI, DOE and EPA warn that actors use AI-generated Python scripts to exploit internet-exposed Siemens S7 PLCs at U.S. critical infrastructure.
A joint advisory from NSA, CISA, FBI, DOE and EPA describes an active threat in which AI-generated exploit scripts disguised as legitimate monitoring tools target Siemens S7 Series PLCs (S7-200 through S7-1500, including F-series safety controllers). The actors use Censys and ZoomEye scanning to find internet-exposed, outdated PLCs and a custom Python script using snap7 libraries over the S7comm protocol for initial access, credential access and denial of service; no attribution was given. Targeted sectors include Critical Manufacturing, Energy, Water and Wastewater, Chemical, Food and Agriculture, and Commercial Facilities, with potential for process disruption and cascading impacts. A related Dream report details a near-autonomous AI-agent campaign (July 1-4, 2026, 12 waves) against Taiwan government entities, using Hermes and OpenClaw agents with eight parallel sub-agents to crack 85 accounts via password spraying and exfiltrate over 2,564 personnel records, SSO client secrets and database credentials.
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Treasury sanctions alleged Iranian hackers as part of ‘economic D
US Treasury sanctioned four Iranians linked to MOIS-directed hacks that compromised and exfiltrated data from US critical infrastructure, energy, defense, and financial targets.
The Treasury Department designated four Iranian individuals over alleged hacking and cybertheft against US companies in energy, defense, healthcare, IT, and financial sectors since at least late 2023, as part of an 'economic D-Day' sanctions package. It is the second action in weeks against the group, following an indictment of cybercriminals affiliated with Tehran's Mabna Institute; leadership includes Behzad Mesri, first sanctioned in 2018, and the attacks are described as directed by the Ministry of Intelligence and Security (MOIS). Treasury also expanded secondary-sanction categories across digital assets, technology, gold, aviation, and shipping, and noted some group members pursued personal enrichment, including targeting Iranian companies.
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US sanctions Iranian cyber actors as UK discloses power plant attack
US Treasury sanctioned six Iranian MOIS-linked hackers for breaching US agency and UN email accounts as the UK disclosed a four-day power plant shutdown.
The US Treasury sanctioned at least six Iranian nationals tied to a hacking team inside Iran's Ministry of Intelligence and Security (MOIS) active since 2023; four were indicted last week for breaching employee email accounts at the Department of Labor, the Federal Energy Regulatory Commission and United Nations organizations. Treasury said the group compromised energy, defense, healthcare, IT and financial sector targets, multiple US government offices in summer 2024, and stole cryptocurrency for personal gain. Separately, Iranian actors reportedly shut down a small British power plant for four days without grid impact, days after FBI and NSA warned of hackers targeting programmable logic controllers in energy, water and agriculture.
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