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What the Data Says About AI in Security Operations in 2026
Prophet Security's 2026 survey of 250+ security pros: 40% use AI daily; AI users report 25%+ faster investigations and rising AI-driven attacks.
Prophet Security's State of AI in Security Operations 2026 report, based on a survey of 250+ cybersecurity professionals, found 40% of security teams use AI daily and only 4% have no adoption plans. Teams average 100 daily alerts (up to 1,000 at large firms), leave 28% of alerts uninvestigated, and 60% of respondents said missed alerts led to breaches or downtime. Among AI adopters, 72% report at least 25% faster investigations, 56% observed increased AI-driven attacks, and no respondents grant AI full unsupervised autonomy. Data privacy (44%) and explainability (41%) top the adoption hurdles.
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The best human hacking team still out-solved the best AI team
Hack The Box 2026 benchmark data shows AI agents helped top teams but human-only teams still solved everything while best AI teams stalled at 32 of 36 challenges.
At the 2026 Global Cyber Skills Benchmark (Project Nightfall) run by Hack The Box, 93 designated AI agent accounts across 54 teams held 2.7% of registered accounts but produced 4.2% of submitted flags and 4.6% of awarded points, and appeared in 17 of the Top 25 finishers. Median solve time dropped from 26 hours in 2024 to 13.8 hours in 2026, though the data cannot attribute the change to AI. At the November 2025 NeuroGrid CTF, AI-augmented teams solved challenges 3.2x faster overall but only 1.69x among the Top 5%, and the only team to complete all 36 challenges was human, while the best AI team stopped at 32.
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How to connect AI usage to business value
OpenAI explained how ChatGPT Admin Console analytics link AI usage, spend, and Codex contributions to business outcomes.
OpenAI published guidance describing analytics features in the ChatGPT Admin Console that combine usage, credit, and token data across ChatGPT Work and Codex. The Insights task classifier groups messages into use cases such as software engineering and sales research, while an Outcomes view tracks Codex contributions to merged commits and lines of code. An Admin plugin and Admin API let teams automate reporting and combine AI analytics with business metrics like ticket resolution time or revenue.
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Impersonating IT support: how threat actors turn a remote session into enterprise-wide access
Microsoft details Teams IT-support impersonation campaigns deploying Node.js implants, AD reconnaissance, and WinRM lateral movement toward domain controllers.
Microsoft Threat Intelligence describes a human-operated campaign where attackers impersonate IT/helpdesk staff via Microsoft Teams external collaboration, talk users into granting remote sessions, and use RMM tools for interactive access. During the session they run PowerShell to silently install a malicious MSI that stages a portable Node.js runtime and obfuscated JavaScript implant for C2, executing follow-on payloads via rundll32. Operators then perform host and Active Directory reconnaissance, capture desktop screenshots, and pivot via WinRM on port 5985 to domain controllers and certificate authorities. The hands-on-keyboard chain, which can precede data theft and ransomware, blends into normal operations by relying on Teams, Quick Assist, msiexec, and Node.js; Microsoft shares hunting and mitigation guidance.
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CISA Red Team Fully Compromised Two Critical Infrastructure Orgs
CISA red teams achieved full domain and cloud compromise at two critical infrastructure orgs; one SOC never detected the intrusion.
CISA advisory AA26-237A documents two simultaneous red team assessments. Organization A (Government Services sector) missed the intrusion entirely, as default credentials on a web app, ADCS ESC1 abuse, and thousands of false-positive alerts let the red team reach sensitive business systems and read SOC email. Organization B (Water/Wastewater sector) detected, isolated, and reimaged hosts quickly, but both orgs lacked Conditional Access for workload identities, and B still exposed DCSync, Golden Ticket, and OT network attack paths.
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The inconvenient truth about AI pentesting: someone has to check all the work
Survey of 158 practitioners shows AI pentesting floods teams with findings, creating 'validation debt' most teams cannot process.
The article argues AI pentesting creates 'validation debt': discovery scales far faster than teams' ability to verify AI-generated findings. In a survey of 158 practitioners, only 20.3% had workflows to triage more than 500 AI-generated candidates per engagement, while 29.7% called such volume unmanageable. One respondent spent two days validating 300 AI findings, of which 250 were duplicates, non-exploitable, or nonexistent. The author recommends capacity planning, ruthless deduplication, and risk-based prioritization before adopting AI pentesting tools.
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