30
55
30
60
42
30
Patch Tuesday to Pentest Wednesday: How an Equipment Rental Company Is Turning Continuous Testing Into Continuous Exposure Management
An equipment rental company uses Horizon3 NodeZero for continuous exposure management, surfacing an SSH key exposure in eight hours versus annual pentesting.
The company moved from periodic penetration testing to continuous exposure management using the NodeZero Proactive Security Platform, feeding telemetry into a Splunk-based CTEM pipeline via Horizon3 APIs. NodeZero exposed SSH RSA key pairs from a PHP web server change about eight hours after introduction and found more findings in 12 hours than a third-party engagement found in roughly 30 days. An Active Directory password audit of 15,000 passwords found about 300 identical or similar compromised passwords, driving a banned-password list, 12-character minimums, service desk changes, and self-service reset rollout; users with similar passwords later dropped from 880 to 209. NodeZero also validated a suspected Cisco vulnerability as exploitable.
15
30
30
42
30
55
60
30
30
30
55
55
30
55
30
CBTS brings continuous penetration testing to enterprise security
CBTS launched Penetration Testing as a Service built on Horizon3.ai's NodeZero, combining autonomous pentesting with expert review for continuous validation.
CBTS announced PTaaS, a service that runs recurring autonomous penetration tests powered by Horizon3.ai's NodeZero across cloud, SaaS, identity, and AI environments, with CBTS experts reviewing findings for exploitability and remediation guidance. The service supports daily-to-quarterly cadences and aims to support Continuous Threat Exposure Management (CTEM) programs. It cites Verizon's 2026 DBIR finding that re-exploitation likelihood drops roughly 30 days after last observed exploitation.
27
30
55
55
30
30
30
55
55
30
30
60
55
30
Jackrong/Qwopus3.8-27B-Flash-GGUF — new model trending #26 on Hugging Face
Community fine-tune Qwopus3.8-27B-Flash, built on Qwen3.8-27B, cuts agent reasoning latency with 12.8% faster decoding and 80.7% MTP acceptance.
Jackrong released Qwopus3.8-27B-Flash, a fine-tune of Qwen3.8-27B optimized for long-running agent workloads, reporting 12.8% faster decoding and 80.7% multi-token-prediction acceptance. Training used roughly 1.5 million teacher-scored SFT examples filtered to the top 10%, followed by reinforcement training with NVIDIA NeMo-RL and GSPO. The author notes an explicit trade-off: MMLU-Pro mixed-set scores are lower than the base model, and a known bug can produce incorrect Python indentation. Author-provided benchmarks have not been independently verified.
35
60
55
30
55