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Pyramid Solutions NetStaX EtherNet/IP Stack
CISA flags critical CVE-2026-78012 (CVSS 9.8) stack buffer overflow in Pyramid Solutions NetStaX EtherNet/IP stacks below v5.6.1, risking crashes or remote attack vectors.
CISA republished Pyramid Solutions' advisory for CVE-2026-78012, a CWE-121 stack-based buffer overflow in the NetStaX EtherNet/IP stack versions prior to 5.6.1, scored CVSS 9.8. Large Class 3 explicit-message requests can exceed the application-side receive buffer without generating a CIP error, potentially causing memory corruption, device crashes, or a silent remote attack vector. All eight adapter and scanner DLL/development kit variants, including CIP Security editions, are affected across critical manufacturing, energy, water, and chemical sectors. No public exploitation has been reported.
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Rockwell Automation 1756-ENBT Module
Rockwell's 1756-ENBT ControlLogix EtherNet/IP bridge (all versions) is vulnerable to DoS via crafted CIP packets, crashing the module until manual restart.
CISA republished Rockwell Automation's advisory for CVE-2025-10478, a CWE-754 flaw affecting all versions of the 1756-ENBT ControlLogix EtherNet/IP bridge, scored CVSS 7.5. A crafted CIP packet can crash the module, and the device requires a restart to recover. Affected critical infrastructure sectors include critical manufacturing, food and agriculture, transportation systems, and water. No public exploitation has been reported; CISA recommends minimizing network exposure.
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We have a year to fix security everywhere
Blog post warns that cheap open-weight GLM 5.3-flash, once abliterated, could enable mass AI-driven vulnerability exploitation, urging industry-wide patching now.
An essay argues that Z.ai's open-weight GLM 5.3-flash—runnable locally on roughly $6k consumer hardware at 20-45 tokens/second—combined with 'abliterated' variants from groups like DeAlignAI that score 0% on HarmBench-320 puts dangerous hacking capability in nearly anyone's hands. GLM 5.3 scores 84.5% on CyberGym and 54.4% on ExploitBench, versus GPT-6 Astra's 100% and GPT-5.6 Sol's 78.5%, and the author cites evidence of frontier models exploiting real-world infrastructure. The author calls for using LLMs (Project Glasswing, Daybreak) to find and fix vulnerabilities industry-wide before adversaries weaponize cheap open models.
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